索引
All Classes and Interfaces|常量字段值|序列化表格|所有程序包
A
- abortExperiment() - 类中的方法 weka.experiment.RemoteExperiment
-
Set the abort flag
- ABS - 接口中的静态变量 weka.core.mathematicalexpression.sym
- ABS - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- ABSTRACT - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
An abstract of the work.
- AbstractAssociator - weka.associations中的类
-
Abstract scheme for learning associations.
- AbstractAssociator() - 类的构造器 weka.associations.AbstractAssociator
- AbstractClusterer - weka.clusterers中的类
-
Abstract clusterer.
- AbstractClusterer() - 类的构造器 weka.clusterers.AbstractClusterer
- AbstractDataSink - weka.gui.beans中的类
-
Abstract class for objects that store instances to some destination.
- AbstractDataSink() - 类的构造器 weka.gui.beans.AbstractDataSink
- AbstractDataSinkBeanInfo - weka.gui.beans中的类
-
Bean info class for the AbstractDataSink
- AbstractDataSinkBeanInfo() - 类的构造器 weka.gui.beans.AbstractDataSinkBeanInfo
- AbstractDataSource - weka.gui.beans中的类
-
Abstract class for objects that can provide instances from some source
- AbstractDataSource() - 类的构造器 weka.gui.beans.AbstractDataSource
-
Creates a new
AbstractDataSource
instance. - AbstractDataSourceBeanInfo - weka.gui.beans中的类
-
Bean info class for AbstractDataSource.
- AbstractDataSourceBeanInfo() - 类的构造器 weka.gui.beans.AbstractDataSourceBeanInfo
- AbstractDensityBasedClusterer - weka.clusterers中的类
-
Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie.
- AbstractDensityBasedClusterer() - 类的构造器 weka.clusterers.AbstractDensityBasedClusterer
- AbstractEvaluator - weka.gui.beans中的类
-
Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc.
- AbstractEvaluator() - 类的构造器 weka.gui.beans.AbstractEvaluator
-
Constructor
- AbstractFileLoader - weka.core.converters中的类
-
Abstract superclass for all file loaders.
- AbstractFileLoader() - 类的构造器 weka.core.converters.AbstractFileLoader
- AbstractFileSaver - weka.core.converters中的类
-
Abstract class for Savers that save to a file Valid options are: -i input arff file
The input filw in arff format. - AbstractFileSaver() - 类的构造器 weka.core.converters.AbstractFileSaver
- AbstractLoader - weka.core.converters中的类
-
Abstract class gives default implementation of setSource methods.
- AbstractLoader() - 类的构造器 weka.core.converters.AbstractLoader
- AbstractSaver - weka.core.converters中的类
-
Abstract class for Saver
- AbstractSaver() - 类的构造器 weka.core.converters.AbstractSaver
- AbstractStringDistanceFunction - weka.core中的类
-
Represents the abstract ancestor for string-based distance functions, like EditDistance.
- AbstractStringDistanceFunction() - 类的构造器 weka.core.AbstractStringDistanceFunction
-
Constructor that doesn't set the data
- AbstractStringDistanceFunction(Instances) - 类的构造器 weka.core.AbstractStringDistanceFunction
-
Constructor that sets the data
- AbstractTestSetProducer - weka.gui.beans中的类
-
Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
- AbstractTestSetProducer() - 类的构造器 weka.gui.beans.AbstractTestSetProducer
-
Creates a new
AbstractTestSetProducer
instance. - AbstractTestSetProducerBeanInfo - weka.gui.beans中的类
-
BeanInfo class for AbstractTestSetProducer
- AbstractTestSetProducerBeanInfo() - 类的构造器 weka.gui.beans.AbstractTestSetProducerBeanInfo
- AbstractTimeSeries - weka.filters.unsupervised.attribute中的类
-
An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with attribute attribute values of some previous (or future) instance.
- AbstractTimeSeries() - 类的构造器 weka.filters.unsupervised.attribute.AbstractTimeSeries
- AbstractTrainAndTestSetProducer - weka.gui.beans中的类
-
Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
- AbstractTrainAndTestSetProducer() - 类的构造器 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Creates a new
AbstractTrainAndTestSetProducer
instance. - AbstractTrainAndTestSetProducerBeanInfo - weka.gui.beans中的类
-
Bean info class for AbstractTrainAndTestSetProducers
- AbstractTrainAndTestSetProducerBeanInfo() - 类的构造器 weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
- AbstractTrainingSetProducer - weka.gui.beans中的类
-
Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation
- AbstractTrainingSetProducer() - 类的构造器 weka.gui.beans.AbstractTrainingSetProducer
-
Creates a new
AbstractTrainingSetProducer
instance. - AbstractTrainingSetProducerBeanInfo - weka.gui.beans中的类
-
BeanInfo class for AbstractTrainingSetProducer
- AbstractTrainingSetProducerBeanInfo() - 类的构造器 weka.gui.beans.AbstractTrainingSetProducerBeanInfo
- accept(File) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERFileFilter
-
Whether the given file is accepted by this filter.
- accept(File) - 类中的方法 weka.gui.ExtensionFileFilter
-
Returns true if the supplied file should be accepted (i.e.: if it has the required extension or is a directory).
- accept(File, String) - 类中的方法 weka.gui.ExtensionFileFilter
-
Returns true if the file in the given directory with the given name should be accepted.
- ACCEPT - 类中的静态变量 weka.gui.treevisualizer.TreeDisplayEvent
-
States that the user has accepted the tree.
- acceptClassifier(BatchClassifierEvent) - 接口中的方法 weka.gui.beans.BatchClassifierListener
-
Accept a BatchClassifierEvent
- acceptClassifier(BatchClassifierEvent) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Accept a classifier to be evaluated
- acceptClassifier(BatchClassifierEvent) - 类中的方法 weka.gui.beans.PredictionAppender
-
Accept and process a batch classifier event
- acceptClassifier(BatchClassifierEvent) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Accept and save a batch trained classifier.
- acceptClassifier(IncrementalClassifierEvent) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Accepts and processes a classifier encapsulated in an incremental classifier event
- acceptClassifier(IncrementalClassifierEvent) - 接口中的方法 weka.gui.beans.IncrementalClassifierListener
-
Accept the event
- acceptClassifier(IncrementalClassifierEvent) - 类中的方法 weka.gui.beans.PredictionAppender
-
Accept and process an incremental classifier event
- acceptClassifier(IncrementalClassifierEvent) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Accept and save an incrementally trained classifier.
- acceptClusterer(BatchClustererEvent) - 接口中的方法 weka.gui.beans.BatchClustererListener
-
Accept a BatchClustererEvent
- acceptClusterer(BatchClustererEvent) - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Accept a clusterer to be evaluated
- acceptClusterer(BatchClustererEvent) - 类中的方法 weka.gui.beans.PredictionAppender
-
Accept and process a batch clusterer event
- acceptClusterer(BatchClustererEvent) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Accept and save a batch trained clusterer.
- acceptDataPoint(double[]) - 类中的方法 weka.gui.beans.StripChart
-
Accept a data point to plot
- acceptDataPoint(ChartEvent) - 接口中的方法 weka.gui.beans.ChartListener
- acceptDataPoint(ChartEvent) - 类中的方法 weka.gui.beans.StripChart
-
Accept a data point (encapsulated in a chart event) to plot
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Accept a data set
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Subclass must implement
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.Associator
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.ClassAssigner
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.ClassValuePicker
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Accept a data set
- acceptDataSet(DataSetEvent) - 接口中的方法 weka.gui.beans.DataSourceListener
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.DataVisualizer
-
Accept a data set
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.Filter
-
Accept a data set
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.Saver
-
Method reacts to a dataset event and starts the writing process in batch mode
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.TestSetMaker
-
Accepts and processes a data set event
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.TextViewer
-
Accept a data set for displaying as text
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.TrainingSetMaker
-
Accept a data set
- acceptDataSet(DataSetEvent) - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Accept a data set
- acceptDataSet(ThresholdDataEvent) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Accept a threshold data set
- acceptDataSet(ThresholdDataEvent) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Accept a threshold data event and set up the visualization.
- acceptDataSet(ThresholdDataEvent) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Display a threshold curve.
- acceptDataSet(ThresholdDataEvent) - 类中的方法 weka.gui.beans.Saver
-
Method reacts to a threshold data event ans starts the writing process in batch mode.
- acceptDataSet(ThresholdDataEvent) - 接口中的方法 weka.gui.beans.ThresholdDataListener
- acceptDataSet(VisualizableErrorEvent) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Display a scheme error plot.
- acceptDataSet(VisualizableErrorEvent) - 接口中的方法 weka.gui.beans.VisualizableErrorListener
- acceptGraph(GraphEvent) - 接口中的方法 weka.gui.beans.GraphListener
-
Describe
acceptGraph
method here. - acceptGraph(GraphEvent) - 类中的方法 weka.gui.beans.GraphViewer
-
Accept a graph
- acceptInstance(InstanceEvent) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Accept an instance
- acceptInstance(InstanceEvent) - 类中的方法 weka.gui.beans.ClassAssigner
- acceptInstance(InstanceEvent) - 类中的方法 weka.gui.beans.Classifier
-
Accepts an instance for incremental processing.
- acceptInstance(InstanceEvent) - 类中的方法 weka.gui.beans.Filter
-
Accept an instance for processing by StreamableFilters only
- acceptInstance(InstanceEvent) - 接口中的方法 weka.gui.beans.InstanceListener
-
Accept and process an instance event
- acceptInstance(InstanceEvent) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Accept an instance to add to the batch.
- acceptInstance(InstanceEvent) - 类中的方法 weka.gui.beans.Saver
-
Methods reacts to instance events and saves instances incrementally.
- acceptInstance(InstanceEvent) - 类中的方法 weka.gui.beans.StripChart
- acceptResult(ResultProducer, Object[], Object[]) - 类中的方法 weka.experiment.AveragingResultProducer
-
Accepts results from a ResultProducer.
- acceptResult(ResultProducer, Object[], Object[]) - 类中的方法 weka.experiment.CSVResultListener
-
Just prints out each result as it is received.
- acceptResult(ResultProducer, Object[], Object[]) - 类中的方法 weka.experiment.DatabaseResultListener
-
Submit the result to the appropriate table of the database
- acceptResult(ResultProducer, Object[], Object[]) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Accepts results from a ResultProducer.
- acceptResult(ResultProducer, Object[], Object[]) - 类中的方法 weka.experiment.InstancesResultListener
-
Collects each instance and adjusts the header information.
- acceptResult(ResultProducer, Object[], Object[]) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Accepts results from a ResultProducer.
- acceptResult(ResultProducer, Object[], Object[]) - 接口中的方法 weka.experiment.ResultListener
-
Accepts results from a ResultProducer.
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Accept a test set
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.ClassAssigner
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.Classifier
-
Accepts a test set for a batch trained classifier
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.Clusterer
-
Accepts a test set for a batch trained clusterer
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Accept a test set
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.DataVisualizer
-
Accept a test set
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.Filter
-
Accept a test set
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.Saver
-
Method reacts to a test set event and starts the writing process in batch mode
- acceptTestSet(TestSetEvent) - 接口中的方法 weka.gui.beans.TestSetListener
-
Accept and process a test set event
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.TextViewer
-
Accept a test set for displaying as text
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.TrainingSetMaker
- acceptTestSet(TestSetEvent) - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Accept a test set
- acceptText(TextEvent) - 接口中的方法 weka.gui.beans.TextListener
-
Accept and process a text event
- acceptText(TextEvent) - 类中的方法 weka.gui.beans.TextViewer
-
Accept some text
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Accept a training set
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.Associator
-
Accept a training set
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.ClassAssigner
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.Classifier
-
Accepts a training set and builds batch classifier
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.Clusterer
-
Accepts a training set and builds batch clusterer
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Accept a training set
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.DataVisualizer
-
Accept a training set
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.Filter
-
Accept a training set
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.Saver
-
Method reacts to a training set event and starts the writing process in batch mode
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.TestSetMaker
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.TextViewer
-
Accept a training set for displaying as text
- acceptTrainingSet(TrainingSetEvent) - 接口中的方法 weka.gui.beans.TrainingSetListener
-
Accept and process a training set
- acceptTrainingSet(TrainingSetEvent) - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Accept a training set
- accuracy() - 类中的方法 weka.associations.RuleItem
-
Gets the expected predictive accuracy of a rule
- ACCURACY - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
accuracy
- actEntropy - 类中的变量 weka.classifiers.lazy.kstar.KStarWrapper
-
used/reused to hold the actual entropy
- action_table() - 类中的方法 weka.core.mathematicalexpression.Parser
-
Access to parse-action table.
- action_table() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Access to parse-action table.
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
invoked when an action occurs
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
invoked when an action occurs
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.experiment.AlgorithmListPanel
-
Handle actions when buttons get pressed.
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.experiment.DatasetListPanel
-
Handle actions when buttons get pressed.
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.experiment.GeneratorPropertyIteratorPanel
-
Handles the various button clicking type activities.
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.experiment.HostListPanel
-
Handle actions when text is entered into the host field or the delete button is pressed.
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.experiment.RunPanel
-
Controls starting and stopping the experiment.
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.SimpleCLIPanel
-
Only gets called when return is pressed in the input area, which starts the command running.
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.streams.InstanceLoader
- actionPerformed(ActionEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Performs the action associated with the ActionEvent.
- actual() - 类中的方法 weka.classifiers.evaluation.NominalPrediction
-
Gets the actual class value.
- actual() - 类中的方法 weka.classifiers.evaluation.NumericPrediction
-
Gets the actual class value.
- actual() - 接口中的方法 weka.classifiers.evaluation.Prediction
-
Gets the actual class value.
- actualNumBags() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns number of non-empty bags of distribution.
- actualNumClasses() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns number of classes actually occuring in distribution.
- actualNumClasses(int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns number of classes actually occuring in given bag.
- acuityTipText() - 类中的方法 weka.clusterers.Cobweb
-
Returns the tip text for this property
- AdaBoostM1 - weka.classifiers.meta中的类
-
Class for boosting a nominal class classifier using the Adaboost M1 method.
- AdaBoostM1() - 类的构造器 weka.classifiers.meta.AdaBoostM1
-
Constructor.
- add(double) - 类中的方法 weka.experiment.Stats
-
Adds a value to the observed values
- add(double[], double[]) - 类中的方法 weka.experiment.PairedStats
-
Adds an array of observed pair of values.
- add(double, double) - 类中的方法 weka.experiment.PairedStats
-
Add an observed pair of values.
- add(double, double) - 类中的方法 weka.experiment.Stats
-
Adds a value that has been seen n times to the observed values
- add(double, Object) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue
-
Adds a new Object to the queue
- add(double, Object, String) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue
-
Adds a new Object to the queue
- add(int, double[]) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Adds counts to given bag.
- add(int, Object) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Inserts the specified element at the specified position in this list.
- add(int, Instance) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Adds given instance to given bag.
- add(PrintStream) - 类中的方法 weka.core.Tee
-
adds the given PrintStream to the list of streams, with NO timestamp and NO prefix.
- add(PrintStream, boolean) - 类中的方法 weka.core.Tee
-
adds the given PrintStream to the list of streams, with NO prefix.
- add(PrintStream, boolean, String) - 类中的方法 weka.core.Tee
-
adds the given PrintStream to the list of streams.
- add(Class, Method) - 类中的方法 weka.core.xml.MethodHandler
-
adds the specified method for the given class to its internal list.
- add(Object) - 类中的方法 weka.associations.tertius.SimpleLinkedList
- add(String) - 类中的方法 weka.core.Stopwords
-
adds the given word to the stopword list (is automatically converted to lower case and trimmed)
- add(String) - 类中的方法 weka.core.Trie
-
Ensures that this collection contains the specified element.
- add(String) - 类中的方法 weka.core.Trie.TrieNode
-
adds the given string to its children (creates children if necessary)
- add(String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Add the given item of property to the tree
- add(String, Method) - 类中的方法 weka.core.xml.MethodHandler
-
adds the specified method for the property with the given displayname to its internal list.
- add(AlgVector) - 类中的方法 weka.core.AlgVector
-
Returns the sum of this vector with another.
- add(Instance) - 类中的方法 weka.core.Instances
-
Adds one instance to the end of the set.
- add(Matrix) - 类中的方法 weka.core.Matrix
-
已过时。Returns the sum of this matrix with another.
- add(TechnicalInformation) - 类中的方法 weka.core.TechnicalInformation
-
adds the given information to the list of additional technical informations
- add(TechnicalInformation.Type) - 类中的方法 weka.core.TechnicalInformation
-
Adds an empty technical information with the given type to the list of additional informations and returns the instance.
- Add - weka.filters.unsupervised.attribute中的类
-
An instance filter that adds a new attribute to the dataset.
- Add() - 类的构造器 weka.filters.unsupervised.attribute.Add
- ADD_CHILDREN - 类中的静态变量 weka.gui.treevisualizer.TreeDisplayEvent
- addActionListener(ActionListener) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Register a listener to be notified when plotting completes
- addActionListener(ActionListener) - 类中的方法 weka.gui.experiment.GeneratorPropertyIteratorPanel
-
Add a listener interested in kowing about editor status changes
- addActionListener(ActionListener) - 类中的方法 weka.gui.visualize.ClassPanel
-
Add an action listener that will be notified if the user changes the colour of a label
- addActionListener(ActionListener) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Add a listener for this visualize panel
- addAll(Collection) - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Adds all the given elements in the stack.
- addAll(Collection<? extends String>) - 类中的方法 weka.core.Trie
-
Adds all of the elements in the specified collection to this collection
- addAll(SimpleLinkedList) - 类中的方法 weka.associations.tertius.SimpleLinkedList
- addAllBeansToContainer(JComponent) - 类中的静态方法 weka.gui.beans.BeanInstance
-
Adds all beans to the supplied component
- addAllowed(Class, String) - 类中的方法 weka.core.xml.PropertyHandler
-
adds the given property (display name) to the list of allowed properties for the specified class.
- addAndUpdate(Rule) - 类中的方法 weka.classifiers.rules.RuleStats
-
Add a rule to the ruleset and update the stats
- addArc(int, int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
- addArc(String, String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
- addArc(String, FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Add arc between parent node and each of the nodes in a given list.
- addAttributePanelListener(AttributePanelListener) - 类中的方法 weka.gui.visualize.AttributePanel
-
Add a listener to the list of things listening to this panel
- addBatchClassifierListener(BatchClassifierListener) - 类中的方法 weka.gui.beans.Classifier
-
Add a batch classifier listener
- addBatchClustererListener(BatchClustererListener) - 类中的方法 weka.gui.beans.Clusterer
-
Add a batch clusterer listener
- addBean(JComponent) - 类中的方法 weka.gui.beans.BeanInstance
-
Adds this bean to the global list of beans and to the supplied container.
- addBefore(Object) - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListIterator
- addCancelListener(ActionListener) - 类中的方法 weka.gui.GenericObjectEditor.GOEPanel
-
This is used to hook an action listener to the cancel button.
- addCapabilities(String, Capabilities) - 类中的静态方法 weka.gui.PropertySheetPanel
-
generates a string from the capapbilities, suitable to add to the help text.
- addCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - 类中的方法 weka.gui.explorer.Explorer
-
adds the listener to the list of objects that listen for changes of the CapabilitiesFilter
- addChangeListener(ChangeListener) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
Adds a ChangeListener to the panel
- addChangeListener(ChangeListener) - 类中的方法 weka.gui.arffviewer.ArffTable
-
Adds a ChangeListener to the panel
- addChartListener(ChartListener) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Add a chart listener
- addCheckBoxActionListener(ActionListener) - 类中的方法 weka.gui.experiment.DistributeExperimentPanel
-
Enable objects to listen for changes to the check box
- addChild(Splitter, ADTree) - 类中的方法 weka.classifiers.trees.adtree.PredictionNode
-
Adds a child to this node.
- addChild(Edge) - 类中的方法 weka.gui.treevisualizer.Node
-
Set the value of children.
- addChildClique(MarginCalculator.JunctionTreeNode) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
- addChildFrame(Container) - 类中的方法 weka.gui.GUIChooser
-
adds the given child frame to the list of frames.
- addChildFrame(Container) - 类中的方法 weka.gui.Main
-
adds the given child frame to the list of frames.
- AddClassification - weka.filters.supervised.attribute中的类
-
A filter for adding the classification, the class distribution and an error flag to a dataset with a classifier.
- AddClassification() - 类的构造器 weka.filters.supervised.attribute.AddClassification
- AddCluster - weka.filters.unsupervised.attribute中的类
-
A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.
- AddCluster() - 类的构造器 weka.filters.unsupervised.attribute.AddCluster
- addConnectionListener(ConnectionListener) - 类中的方法 weka.gui.sql.ConnectionPanel
-
adds the given listener to the list of listeners.
- addConnectionListener(ConnectionListener) - 类中的方法 weka.gui.sql.SqlViewer
-
adds the given listener to the list of listeners.
- addCons(int[]) - 类中的方法 weka.associations.PriorEstimation
-
generates a class association rule out of a given premise.
- addCVParameter(String) - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Adds a scheme parameter to the list of parameters to be set by cross-validation
- addDataFormatListener(DataFormatListener) - 类中的方法 weka.gui.beans.ClassAssigner
- addDataFormatListener(DataFormatListener) - 类中的方法 weka.gui.beans.ClassValuePicker
- addDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Add a listener
- addDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.ClassAssigner
- addDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.ClassValuePicker
- addDataSourceListener(DataSourceListener) - 接口中的方法 weka.gui.beans.DataSource
-
Add a data source listener
- addDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.DataVisualizer
-
Add a listener
- addDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.Filter
-
Add a data source listener
- addDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
- addDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.Loader
-
Add a listener
- addDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.PredictionAppender
-
Add a datasource listener
- addElement(double) - 类中的方法 weka.core.matrix.DoubleVector
-
Adds an element into the vector
- addElement(int, int, double) - 类中的方法 weka.core.Matrix
-
已过时。Add a value to an element.
- addElement(Object) - 类中的方法 weka.core.FastVector
-
Adds an element to this vector.
- addElement(Object) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Adds the specified component to the end of this list.
- addElement(Literal) - 类中的方法 weka.associations.tertius.LiteralSet
-
Add a Literal to this set.
- addErrs(double, double, float) - 类中的静态方法 weka.classifiers.trees.j48.Stats
-
Computes estimated extra error for given total number of instances and error using normal approximation to binomial distribution (and continuity correction).
- AddExpression - weka.filters.unsupervised.attribute中的类
-
An instance filter that creates a new attribute by applying a mathematical expression to existing attributes.
- AddExpression() - 类的构造器 weka.filters.unsupervised.attribute.AddExpression
- addFile(File) - 类中的静态方法 weka.core.ClassloaderUtil
-
Add file to CLASSPATH
- addFile(String) - 类中的静态方法 weka.core.ClassloaderUtil
-
Add file to CLASSPATH
- addFirst(Object) - 类中的方法 weka.associations.tertius.SimpleLinkedList
- addGraphListener(GraphListener) - 类中的方法 weka.gui.beans.Associator
-
Add a graph listener
- addGraphListener(GraphListener) - 类中的方法 weka.gui.beans.Classifier
-
Add a graph listener
- addGraphListener(GraphListener) - 类中的方法 weka.gui.beans.Clusterer
-
Add a graph listener
- addHeader(String, String) - 类中的方法 weka.experiment.ResultMatrix
-
adds the key-value pair to the header
- addHistoryChangedListener(HistoryChangedListener) - 类中的方法 weka.gui.sql.ConnectionPanel
-
adds the given listener to the list of listeners.
- addHistoryChangedListener(HistoryChangedListener) - 类中的方法 weka.gui.sql.QueryPanel
-
adds the given listener to the list of listeners.
- addHistoryChangedListener(HistoryChangedListener) - 类中的方法 weka.gui.sql.SqlViewer
-
adds the given listener to the list of listeners.
- AddID - weka.filters.unsupervised.attribute中的类
-
An instance filter that adds an ID attribute to the dataset.
- AddID() - 类的构造器 weka.filters.unsupervised.attribute.AddID
- addIgnored(Class, String) - 类中的方法 weka.core.xml.PropertyHandler
-
adds the given class with the display name of a property to the ignore list.
- addIgnored(String) - 类中的方法 weka.core.xml.PropertyHandler
-
adds the given display name of a property to the ignore list.
- addIncrementalClassifierListener(IncrementalClassifierListener) - 类中的方法 weka.gui.beans.Classifier
-
Add an incremental classifier listener
- addInstance(Instance) - 类中的方法 weka.clusterers.Cobweb
-
已过时。updateClusterer(Instance) should be used instead
- addInstance(BallNode, Instance) - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Adds an instance to the ball tree.
- addInstance(BallNode, Instance) - 类中的方法 weka.core.neighboursearch.balltrees.BottomUpConstructor
-
Adds an instance to the ball tree.
- addInstance(BallNode, Instance) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Adds an instance to the tree.
- addInstance(BallNode, Instance) - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Adds an instance to the ball tree.
- addInstanceInfo(Instance) - 类中的方法 weka.core.neighboursearch.BallTree
-
Adds the given instance's info.
- addInstanceInfo(Instance) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Adds the given instance info.
- addInstanceInfo(Instance) - 类中的方法 weka.core.neighboursearch.KDTree
-
Adds one instance to KDTree loosly.
- addInstanceInfo(Instance) - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Adds the given instance info.
- addInstanceInfo(Instance) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Adds information from the given instance without modifying the datastructure a lot.
- addInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Add an instance listener
- addInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.ClassAssigner
- addInstanceListener(InstanceListener) - 接口中的方法 weka.gui.beans.DataSource
-
Add an instance listener
- addInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.Filter
-
Add an instance listener
- addInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
- addInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.Loader
-
Add an instance listener
- addInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.PredictionAppender
-
Add an instance listener
- addInstanceListener(InstanceListener) - 类中的方法 weka.gui.streams.InstanceJoiner
- addInstanceListener(InstanceListener) - 类中的方法 weka.gui.streams.InstanceLoader
- addInstanceListener(InstanceListener) - 接口中的方法 weka.gui.streams.InstanceProducer
- addInstanceNumberAttribute() - 类中的方法 weka.gui.visualize.PlotData2D
-
Adds an instance number attribute to the plottable instances,
- AddInstanceToBestCluster(Instance) - 类中的方法 weka.clusterers.CLOPE
-
Add instance to best cluster
- addInstWithUnknown(Instances, int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Adds all instances with unknown values for given attribute, weighted according to frequency of instances in each bag.
- additional() - 类中的方法 weka.core.TechnicalInformation
-
returns an enumeration of all the additional technical informations (if there are any)
- AdditionalMeasureProducer - weka.core中的接口
-
Interface to something that can produce measures other than those calculated by evaluation modules.
- AdditiveRegression - weka.classifiers.meta中的类
-
Meta classifier that enhances the performance of a regression base classifier.
- AdditiveRegression() - 类的构造器 weka.classifiers.meta.AdditiveRegression
-
Default constructor specifying DecisionStump as the classifier
- AdditiveRegression(Classifier) - 类的构造器 weka.classifiers.meta.AdditiveRegression
-
Constructor which takes base classifier as argument.
- addLayoutCompleteEventListener(LayoutCompleteEventListener) - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
Method to add a LayoutCompleteEventListener
- addLayoutCompleteEventListener(LayoutCompleteEventListener) - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
This method adds a LayoutCompleteEventListener to the LayoutEngine.
- addLiteral(Literal) - 类中的方法 weka.associations.tertius.Predicate
- addMouseListener(MouseListener) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Adds a mouse listener.
- addMouseListenerToHeader(JTable) - 类中的方法 weka.gui.SortedTableModel
-
Adds a mouselistener to the header: left-click on the header sorts in ascending manner, using shift-left-click in descending manner.
- addNode(String, int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Add new node to the network, initializing instances, parentsets, distributions.
- addNode(String, int, int, int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Add node to network at a given position, initializing instances, parentsets, distributions.
- addNodeValue(int, String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Add node value to a node.
- addNoise(Instances, int, int, int, boolean) - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
add noise to the dataset a given percentage of the instances are changed in the way, that a set of instances are randomly selected using seed.
- AddNoise - weka.filters.unsupervised.attribute中的类
-
An instance filter that changes a percentage of a given attributes values.
- AddNoise() - 类的构造器 weka.filters.unsupervised.attribute.AddNoise
- addObject(String, Object) - 类中的方法 weka.gui.ResultHistoryPanel
-
Adds an object to the results list
- addOkListener(ActionListener) - 类中的方法 weka.gui.GenericObjectEditor.GOEPanel
-
This is used to hook an action listener to the ok button.
- addParent(int, int, Instances) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
Add parent to parent set at specific location and update internals (specifically the cardinality of the parent set)
- addParent(int, Instances) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
Add parent to parent set and update internals (specifically the cardinality of the parent set)
- addPlot(PlotData2D) - 类中的方法 weka.gui.visualize.Plot2D
-
Add a plot to the list of plots to display
- addPlot(PlotData2D) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Set a new plot to the visualize panel
- addPrediction(NominalPrediction) - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Includes a prediction in the confusion matrix.
- addPredictions(FastVector) - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Includes a whole bunch of predictions in the confusion matrix.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.AssociatorCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.BeanVisual
-
Add a listener for property change events
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.ClassAssignerCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.ClassifierCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.ClassValuePickerCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.ClustererCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.CrossValidationFoldMakerCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.FilterCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.LoaderCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.PredictionAppenderCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.SaverCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.SerializedModelSaverCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.StripChartCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.TrainTestSplitMakerCustomizer
-
Add a property change listener
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.CostMatrixEditor
-
Adds an object to the list of those that wish to be informed when the cost matrix changes.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.experiment.SetupModePanel
-
Adds a PropertyChangeListener who will be notified of value changes.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.experiment.SetupPanel
-
Adds a PropertyChangeListener who will be notified of value changes.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.experiment.SimpleSetupPanel
-
Adds a PropertyChangeListener who will be notified of value changes.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Adds a PropertyChangeListener who will be notified of value changes.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.GenericArrayEditor
-
Adds a PropertyChangeListener who will be notified of value changes.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.GenericObjectEditor
-
Adds a PropertyChangeListener who will be notified of value changes.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.PropertySheetPanel
-
Adds a PropertyChangeListener.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.SetInstancesPanel
-
Adds a PropertyChangeListener who will be notified of value changes.
- addPropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Adds an object to the list of those that wish to be informed when the date format changes.
- addPropertyChangeListener(String, PropertyChangeListener) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Add a property change listener to this bean
- addPropertyChangeListener(String, PropertyChangeListener) - 类中的方法 weka.gui.beans.DataVisualizer
-
Add a property change listener to this bean
- addPropertyChangeListener(String, PropertyChangeListener) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Add a property change listener to this bean
- addPropertyChangeListener(String, PropertyChangeListener) - 类中的方法 weka.gui.beans.TextViewer
-
Add a property change listener to this bean
- addPropertyChangeListenersSubFlow(PropertyChangeListener) - 类中的方法 weka.gui.beans.MetaBean
- addPSFontReplacement(String, String) - 类中的静态方法 weka.gui.visualize.PostscriptGraphics
-
adds the PS font name to replace and its replacement in the replacement hashtable
- addQueryExecuteListener(QueryExecuteListener) - 类中的方法 weka.gui.sql.QueryPanel
-
adds the given listener to the list of listeners.
- addQueryExecuteListener(QueryExecuteListener) - 类中的方法 weka.gui.sql.SqlViewer
-
adds the given listener to the list of listeners.
- addRange(int, Instances, int, int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Adds all instances in given range to given bag.
- addReference(Instance) - 类中的方法 weka.classifiers.trees.adtree.ReferenceInstances
-
Adds one instance reference to the end of the set.
- addRelation(Instances) - 类中的方法 weka.core.Attribute
-
Adds a relation to a relation-valued attribute.
- addRemoteExperimentListener(RemoteExperimentListener) - 类中的方法 weka.experiment.RemoteExperiment
-
Add an object to the list of those interested in recieving update information from the RemoteExperiment
- addRemoteExperimentListener(RemoteExperimentListener) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanelDistributed
-
Add an object to the list of those interested in recieving update information from the RemoteExperiment
- addRemoteHost(String) - 类中的方法 weka.experiment.RemoteExperiment
-
Add a host name to the list of remote hosts
- addRenderingHints(Map) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- addRepaintNotify(Component) - 类中的方法 weka.gui.visualize.ClassPanel
-
Adds a component that will need to be repainted if the user changes the colour of a label.
- addRepaintNotify(Component) - 类中的方法 weka.gui.visualize.LegendPanel
-
Adds a component that will need to be repainted if the user changes the colour of a label.
- ADDRESS - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
Usually the address of the publisher or other type of institution.
- addResult(String, StringBuffer) - 类中的方法 weka.gui.ResultHistoryPanel
-
Adds a new result to the result list.
- addResultChangedListener(ResultChangedListener) - 类中的方法 weka.gui.sql.ResultPanel
-
adds the given listener to the list of listeners
- addResultChangedListener(ResultChangedListener) - 类中的方法 weka.gui.sql.SqlViewer
-
adds the given listener to the list of listeners.
- addStartupListener(StartUpListener) - 类中的静态方法 weka.gui.beans.KnowledgeFlowApp
-
Add a listener to be notified when startup is complete
- addStartupListener(StartUpListener) - 类中的静态方法 weka.gui.Main
-
Add a listener to be notified when startup is complete.
- addStringValue(String) - 类中的方法 weka.core.Attribute
-
Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
- addStringValue(Attribute, int) - 类中的方法 weka.core.Attribute
-
Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
- addTableModelListener(TableModelListener) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
adds a listener to the list that is notified each time a change to data model occurs
- addTableModelListener(TableModelListener) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
adds a listener to the list that is notified each time a change to data model occurs
- addTableModelListener(TableModelListener) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
adds a listener to the list that is notified each time a change to data model occurs.
- addTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Add a listener for test sets
- addTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Add a test set listener
- addTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.ClassAssigner
- addTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.Filter
-
Add a test set listener
- addTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.PredictionAppender
-
Add a test set listener
- addTestSetListener(TestSetListener) - 接口中的方法 weka.gui.beans.TestSetProducer
-
Add a listener for test set events
- addTextListener(TextListener) - 类中的方法 weka.gui.beans.Associator
-
Add a text listener
- addTextListener(TextListener) - 类中的方法 weka.gui.beans.Classifier
-
Add a text listener
- addTextListener(TextListener) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Add a text listener
- addTextListener(TextListener) - 类中的方法 weka.gui.beans.Clusterer
-
Add a text listener
- addTextListener(TextListener) - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Add a text listener
- addTextListener(TextListener) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Add a text listener
- addTextListener(TextListener) - 类中的方法 weka.gui.beans.TextViewer
-
Add a text listener
- addThresholdDataListener(ThresholdDataListener) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Add a threshold data listener
- addToList(Object[], double) - 类中的方法 weka.attributeSelection.BestFirst.LinkedList2
-
adds an element (Link) to the list.
- addToList(Object[], double) - 类中的方法 weka.attributeSelection.LFSMethods.LinkedList2
-
adds an element (Link) to the list.
- addTrainingInstance(Instance) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Adds a training instance to the visualization dataset.
- addTrainingInstanceFromMouseLocation(int, int, int, double) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Adds a training instance to our dataset, based on the coordinates of the mouse on the panel.
- addTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Add a training set listener
- addTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Add a training set listener
- addTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.ClassAssigner
- addTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.Filter
-
Add a training set listener
- addTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.PredictionAppender
-
Add a training set listener
- addTrainingSetListener(TrainingSetListener) - 接口中的方法 weka.gui.beans.TrainingSetProducer
-
Add a training set listener
- addUndoPoint() - 接口中的方法 weka.core.Undoable
-
adds an undo point to the undo history
- addUndoPoint() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
adds the current state of the instances to the undolist
- addUndoPoint() - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
adds an undo point to the undo history
- addUndoPoint() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
adds an undo point to the undo history, if the undo support is enabled
- addUndoPoint() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Backs up the current state of the dataset, so the changes can be undone.
- addURL(URL) - 类中的静态方法 weka.core.ClassloaderUtil
-
Add URL to CLASSPATH
- addValue(double, double) - 类中的方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Add a new data value to the current estimator.
- addValue(double, double) - 类中的方法 weka.estimators.DiscreteEstimator
-
Add a new data value to the current estimator.
- addValue(double, double) - 类中的方法 weka.estimators.Estimator
-
Add a new data value to the current estimator.
- addValue(double, double) - 接口中的方法 weka.estimators.IncrementalEstimator
-
Add one value to the current estimator.
- addValue(double, double) - 类中的方法 weka.estimators.KernelEstimator
-
Add a new data value to the current estimator.
- addValue(double, double) - 类中的方法 weka.estimators.MahalanobisEstimator
-
Add a new data value to the current estimator.
- addValue(double, double) - 类中的方法 weka.estimators.NormalEstimator
-
Add a new data value to the current estimator.
- addValue(double, double) - 类中的方法 weka.estimators.PoissonEstimator
-
Add a new data value to the current estimator.
- addValue(double, double, double) - 接口中的方法 weka.estimators.ConditionalEstimator
-
Add a new data value to the current estimator.
- addValue(double, double, double) - 类中的方法 weka.estimators.DDConditionalEstimator
-
Add a new data value to the current estimator.
- addValue(double, double, double) - 类中的方法 weka.estimators.DKConditionalEstimator
-
Add a new data value to the current estimator.
- addValue(double, double, double) - 类中的方法 weka.estimators.DNConditionalEstimator
-
Add a new data value to the current estimator.
- addValue(double, double, double) - 类中的方法 weka.estimators.KDConditionalEstimator
-
Add a new data value to the current estimator.
- addValue(double, double, double) - 类中的方法 weka.estimators.KKConditionalEstimator
-
Add a new data value to the current estimator.
- addValue(double, double, double) - 类中的方法 weka.estimators.NDConditionalEstimator
-
Add a new data value to the current estimator.
- addValue(double, double, double) - 类中的方法 weka.estimators.NNConditionalEstimator
-
Add a new data value to the current estimator.
- addValues(Instances, int) - 类中的方法 weka.estimators.Estimator
-
Initialize the estimator with a new dataset.
- addValues(Instances, int, double, double, double) - 类中的方法 weka.estimators.Estimator
-
Initialize the estimator with all values of one attribute of a dataset.
- addValues(Instances, int, int, int) - 类中的方法 weka.estimators.Estimator
-
Initialize the estimator using only the instance of one class.
- addValues(Instances, int, int, int, double, double) - 类中的方法 weka.estimators.Estimator
-
Initialize the estimator using only the instance of one class.
- AddValues - weka.filters.unsupervised.attribute中的类
-
Adds the labels from the given list to an attribute if they are missing.
- AddValues() - 类的构造器 weka.filters.unsupervised.attribute.AddValues
- addVariable(String, String) - 类中的方法 weka.core.Environment
-
Add a variable to the internal map.
- addVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Add a vetoable change listener to this bean
- addVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- addVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.DataVisualizer
-
Add a vetoable change listener to this bean
- addVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.GraphViewer
-
Add a vetoable change listener to this bean
- addVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Add a vetoable change listener to this bean
- addVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.TextViewer
-
Add a vetoable change listener to this bean
- addVisualizableErrorListener(VisualizableErrorListener) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Add a visualizable error listener
- addWeights(Instance, double[]) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Adds given instance to all bags weighting it according to given weights.
- adjustCenter(double) - 类中的方法 weka.gui.treevisualizer.Node
-
Will increase or decrease the postion of center.
- adjustSize(SERObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Adjusts the size of this panel in respect of the shown content
- adjustWeightsTipText() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns the tip text for this property
- ADNode - weka.classifiers.bayes.net中的类
-
The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in an Instances object.
- ADNode() - 类的构造器 weka.classifiers.bayes.net.ADNode
-
Creates new ADNode
- ADTree - weka.classifiers.trees中的类
-
Class for generating an alternating decision tree.
- ADTree() - 类的构造器 weka.classifiers.trees.ADTree
- advanceCounters() - 类中的方法 weka.experiment.Experiment
-
Increments iteration counters appropriately.
- advanceCounters() - 类中的方法 weka.experiment.RemoteExperiment
-
overides the one in Experiment
- AFFILIATION - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The authors affiliation.
- Agrawal - weka.datagenerators.classifiers.classification中的类
-
Generates a people database and is based on the paper by Agrawal et al.:
R. - Agrawal() - 类的构造器 weka.datagenerators.classifiers.classification.Agrawal
-
initializes the generator with default values
- AIC - 接口中的静态变量 weka.classifiers.bayes.net.search.local.Scoreable
- ALGORITHM_HAAR - 类中的静态变量 weka.filters.unsupervised.attribute.Wavelet
-
the type of algorithm: Haar wavelet
- ALGORITHM_PLS1 - 类中的静态变量 weka.filters.supervised.attribute.PLSFilter
-
the type of algorithm: PLS1
- ALGORITHM_SIMPLS - 类中的静态变量 weka.filters.supervised.attribute.PLSFilter
-
the type of algorithm: SIMPLS
- AlgorithmListPanel - weka.gui.experiment中的类
-
This panel controls setting a list of algorithms for an experiment to iterate over.
- AlgorithmListPanel() - 类的构造器 weka.gui.experiment.AlgorithmListPanel
-
Create the algorithm list panel initially disabled.
- AlgorithmListPanel(Experiment) - 类的构造器 weka.gui.experiment.AlgorithmListPanel
-
Creates the algorithm list panel with the given experiment.
- AlgorithmListPanel.ObjectCellRenderer - weka.gui.experiment中的类
-
Class required to show the Classifiers nicely in the list
- algorithmTipText() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns the tip text for this property
- algorithmTipText() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Returns the tip text for this property
- ALGORITHMTYPE_ARITHMETIC - 类中的静态变量 weka.classifiers.mi.MILR
-
collective MI assumption, arithmetic mean for posteriors
- ALGORITHMTYPE_DEFAULT - 类中的静态变量 weka.classifiers.mi.MILR
-
standard MI assumption
- ALGORITHMTYPE_GEOMETRIC - 类中的静态变量 weka.classifiers.mi.MILR
-
collective MI assumption, geometric mean for posteriors
- algorithmTypeTipText() - 类中的方法 weka.classifiers.mi.MILR
-
Returns the tip text for this property
- AlgVector - weka.core中的类
-
Class for performing operations on an algebraic vector of floating-point values.
- AlgVector(double[]) - 类的构造器 weka.core.AlgVector
-
Constructs a vector using a given array.
- AlgVector(int) - 类的构造器 weka.core.AlgVector
-
Constructs a vector and initializes it with default values.
- AlgVector(Instance) - 类的构造器 weka.core.AlgVector
-
Constructs a vector using an instance.
- AlgVector(Instances, Random) - 类的构造器 weka.core.AlgVector
-
Constructs a vector using a given data format.
- alignBottom(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
align set of nodes with the bottom most node in the list
- alignLeft(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
align set of nodes with the left most node in the list
- alignRight(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
align set of nodes with the right most node in the list
- alignTop(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
align set of nodes with the top most node in the list
- ALL - enum class 中的枚举常量 weka.core.logging.Logger.Level
-
logs all messages.
- ALL - 类中的静态变量 weka.core.Debug
-
the log level All
- AllFilter - weka.filters中的类
-
A simple instance filter that passes all instances directly through.
- AllFilter() - 类的构造器 weka.filters.AllFilter
- AllJavadoc - weka.core中的类
-
Applies all known Javadoc-derived classes to a source file.
- AllJavadoc() - 类的构造器 weka.core.AllJavadoc
- allowed() - 类中的方法 weka.core.xml.PropertyHandler
-
returns an enumeration of the classnames for which only certain properties (display names) are allowed
- allowUnclassifiedInstancesTipText() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns the tip text for this property
- AlphabeticTokenizer - weka.core.tokenizers中的类
-
Alphabetic string tokenizer, tokens are to be formed only from contiguous alphabetic sequences.
- AlphabeticTokenizer() - 类的构造器 weka.core.tokenizers.AlphabeticTokenizer
- alphaTipText() - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
- alphaTipText() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns the tip text for this property
- amplitudeTipText() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Returns the tip text for this property
- amplitudeTipText() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Returns the tip text for this property
- and(Capabilities) - 类中的方法 weka.core.Capabilities
-
performs an AND conjunction with the capabilities of the given Capabilities object and updates itself
- AND - 接口中的静态变量 weka.core.mathematicalexpression.sym
- AND - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- ANNOTE - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
An annotation.
- Antd(Attribute) - 类的构造器 weka.classifiers.rules.JRip.Antd
-
Constructor
- AODE - weka.classifiers.bayes中的类
-
AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes.
- AODE() - 类的构造器 weka.classifiers.bayes.AODE
- AODEsr - weka.classifiers.bayes中的类
-
AODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification time and deletes the generalization attribute value.
For more information, see:
Fei Zheng, Geoffrey I. - AODEsr() - 类的构造器 weka.classifiers.bayes.AODEsr
- append(Object) - 类中的方法 weka.gui.sql.InfoPanel
-
adds the given message to the end of the list
- append(String, String) - 类中的方法 weka.gui.sql.InfoPanel
-
adds the given message to the end of the list (with the associated icon at the beginning)
- appendElements(FastVector) - 类中的方法 weka.core.FastVector
-
Appends all elements of the supplied vector to this vector.
- appendPredictedProbabilitiesTipText() - 类中的方法 weka.gui.beans.PredictionAppender
-
Return a tip text suitable for displaying in a GUI
- applyClassifier(PMMLModel, Instances) - 类中的静态方法 weka.core.pmml.PMMLFactory
- applyCostMatrix(Instances, Random) - 类中的方法 weka.classifiers.CostMatrix
-
Applies the cost matrix to a set of instances.
- applyMinMaxRescaleCast(double) - 类中的方法 weka.core.pmml.TargetMetaInfo
-
Apply min and max, rescaleFactor, rescaleConstant and castInteger - in that order (where defined).
- applyMissingAndOutlierTreatments(double[]) - 类中的方法 weka.core.pmml.MiningSchema
-
Apply both missing and outlier treatments to an incoming instance.
- applyMissingValuesTreatment(double[]) - 类中的方法 weka.core.pmml.MiningSchema
-
Apply the missing value treatments (if any) to an incoming instance.
- applyMissingValueTreatment(double) - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Apply the missing value treatment method for this field.
- applyOutlierTreatment(double) - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Apply the outlier treatment method for this field.
- applyOutlierTreatment(double[]) - 类中的方法 weka.core.pmml.MiningSchema
-
Apply the outlier treatment methods (if any) to an incoming instance.
- APPROVE_OPTION - 类中的静态变量 weka.gui.experiment.OutputFormatDialog
-
Signifies an OK property selection.
- APPROVE_OPTION - 类中的静态变量 weka.gui.ListSelectorDialog
-
Signifies an OK property selection
- APPROVE_OPTION - 类中的静态变量 weka.gui.PropertySelectorDialog
-
Signifies an OK property selection
- APPROVE_OPTION - 类中的静态变量 weka.gui.ViewerDialog
-
Signifies an OK property selection
- Apriori - weka.associations中的类
-
Class implementing an Apriori-type algorithm.
- Apriori() - 类的构造器 weka.associations.Apriori
-
Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
- aprioriGen(FastVector) - 类中的静态方法 weka.associations.gsp.Sequence
-
Generates all possible candidate k-Sequences and prunes the ones that contain an infrequent (k-1)-Sequence.
- AprioriItemSet - weka.associations中的类
-
Class for storing a set of items.
- AprioriItemSet(int) - 类的构造器 weka.associations.AprioriItemSet
-
Constructor
- areaUnderROC(int) - 类中的方法 weka.classifiers.Evaluation
-
Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
- ARFF_ATTRIBUTE - 类中的静态变量 weka.core.Attribute
-
The keyword used to denote the start of an arff attribute declaration
- ARFF_ATTRIBUTE_DATE - 类中的静态变量 weka.core.Attribute
-
The keyword used to denote a date attribute
- ARFF_ATTRIBUTE_INTEGER - 类中的静态变量 weka.core.Attribute
-
A keyword used to denote a numeric attribute
- ARFF_ATTRIBUTE_NUMERIC - 类中的静态变量 weka.core.Attribute
-
A keyword used to denote a numeric attribute
- ARFF_ATTRIBUTE_REAL - 类中的静态变量 weka.core.Attribute
-
A keyword used to denote a numeric attribute
- ARFF_ATTRIBUTE_RELATIONAL - 类中的静态变量 weka.core.Attribute
-
The keyword used to denote a relation-valued attribute
- ARFF_ATTRIBUTE_STRING - 类中的静态变量 weka.core.Attribute
-
The keyword used to denote a string attribute
- ARFF_DATA - 类中的静态变量 weka.core.Instances
-
The keyword used to denote the start of the arff data section
- ARFF_END_SUBRELATION - 类中的静态变量 weka.core.Attribute
-
The keyword used to denote the end of the declaration of a subrelation
- ARFF_RELATION - 类中的静态变量 weka.core.Instances
-
The keyword used to denote the start of an arff header
- ArffLoader - weka.core.converters中的类
-
Reads a source that is in arff (attribute relation file format) format.
- ArffLoader() - 类的构造器 weka.core.converters.ArffLoader
- ArffLoader.ArffReader - weka.core.converters中的类
-
Reads data from an ARFF file, either in incremental or batch mode.
- ArffPanel - weka.gui.arffviewer中的类
-
A Panel representing an ARFF-Table and the associated filename.
- ArffPanel() - 类的构造器 weka.gui.arffviewer.ArffPanel
-
initializes the panel with no data
- ArffPanel(String) - 类的构造器 weka.gui.arffviewer.ArffPanel
-
initializes the panel and loads the specified file
- ArffPanel(Instances) - 类的构造器 weka.gui.arffviewer.ArffPanel
-
initializes the panel with the given data
- ArffReader(Reader) - 类的构造器 weka.core.converters.ArffLoader.ArffReader
-
Reads the data completely from the reader.
- ArffReader(Reader, int) - 类的构造器 weka.core.converters.ArffLoader.ArffReader
-
Reads only the header and reserves the specified space for instances.
- ArffReader(Reader, Instances, int) - 类的构造器 weka.core.converters.ArffLoader.ArffReader
-
Reads the data without header according to the specified template.
- ArffReader(Reader, Instances, int, int) - 类的构造器 weka.core.converters.ArffLoader.ArffReader
-
Initializes the reader without reading the header according to the specified template.
- ArffSaver - weka.core.converters中的类
-
Writes to a destination in arff text format.
- ArffSaver() - 类的构造器 weka.core.converters.ArffSaver
-
Constructor
- ArffSortedTableModel - weka.gui.arffviewer中的类
-
A sorter for the ARFF-Viewer - necessary because of the custom CellRenderer.
- ArffSortedTableModel(String) - 类的构造器 weka.gui.arffviewer.ArffSortedTableModel
-
initializes the sorter w/o a model, but loads the given file and creates from that a model
- ArffSortedTableModel(TableModel) - 类的构造器 weka.gui.arffviewer.ArffSortedTableModel
-
initializes the sorter with the given model
- ArffSortedTableModel(Instances) - 类的构造器 weka.gui.arffviewer.ArffSortedTableModel
-
initializes the sorter w/o a model, but uses the given data to create a model from that
- ArffTable - weka.gui.arffviewer中的类
-
A specialized JTable for the Arff-Viewer.
- ArffTable() - 类的构造器 weka.gui.arffviewer.ArffTable
-
initializes with no model
- ArffTable(TableModel) - 类的构造器 weka.gui.arffviewer.ArffTable
-
initializes with the given model
- ArffTableCellRenderer - weka.gui.arffviewer中的类
-
Handles the background colors for missing values differently than the DefaultTableCellRenderer.
- ArffTableCellRenderer() - 类的构造器 weka.gui.arffviewer.ArffTableCellRenderer
-
initializes the Renderer with a standard color
- ArffTableCellRenderer(Color, Color) - 类的构造器 weka.gui.arffviewer.ArffTableCellRenderer
-
initializes the Renderer with the given colors
- ArffTableCellRenderer(Color, Color, Color, Color) - 类的构造器 weka.gui.arffviewer.ArffTableCellRenderer
-
initializes the Renderer with the given colors
- ArffTableModel - weka.gui.arffviewer中的类
-
The model for the Arff-Viewer.
- ArffTableModel(String) - 类的构造器 weka.gui.arffviewer.ArffTableModel
-
initializes the object and loads the given file
- ArffTableModel(Instances) - 类的构造器 weka.gui.arffviewer.ArffTableModel
-
initializes the model with the given data
- ArffViewer - weka.gui.arffviewer中的类
-
A little tool for viewing ARFF files.
- ArffViewer() - 类的构造器 weka.gui.arffviewer.ArffViewer
-
initializes the object
- ArffViewerMainPanel - weka.gui.arffviewer中的类
-
The main panel of the ArffViewer.
- ArffViewerMainPanel(Container) - 类的构造器 weka.gui.arffviewer.ArffViewerMainPanel
-
initializes the object
- arrayLeftDivide(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Element-by-element left division, C = A.\B
- arrayLeftDivideEquals(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Element-by-element left division in place, A = A.\B
- arrayRightDivide(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Element-by-element right division, C = A./B
- arrayRightDivideEquals(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Element-by-element right division in place, A = A./B
- arrayTimes(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Element-by-element multiplication, C = A.*B
- arrayTimesEquals(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Element-by-element multiplication in place, A = A.*B
- arrayToString(Object) - 类中的静态方法 weka.core.Utils
-
Returns the given Array in a string representation.
- arrayToString(Object[]) - 类中的静态方法 weka.experiment.DatabaseUtils
-
Converts an array of objects to a string by inserting a space between each element.
- ARTICLE - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
An article from a journal or magazine.
- artificialSizeTipText() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns the tip text for this property
- ASEvaluation - weka.attributeSelection中的类
-
Abstract attribute selection evaluation class
- ASEvaluation() - 类的构造器 weka.attributeSelection.ASEvaluation
- ASSearch - weka.attributeSelection中的类
-
Abstract attribute selection search class.
- ASSearch() - 类的构造器 weka.attributeSelection.ASSearch
- assign(Capabilities) - 类中的方法 weka.core.Capabilities
-
retrieves the data from the given Capabilities object
- assign(TestInstances) - 类中的方法 weka.core.TestInstances
-
updates itself with all the settings from the given TestInstances object
- assign(ResultMatrix) - 类中的方法 weka.experiment.ResultMatrix
-
acquires the data from the given matrix
- assign(Tester) - 类中的方法 weka.experiment.PairedTTester
-
retrieves all the settings from the given Tester
- assign(Tester) - 接口中的方法 weka.experiment.Tester
-
retrieves all the settings from the given Tester
- assignIDs(int) - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Assigns unique IDs to all nodes in the tree
- assignIDs(int) - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Assigns a uniqe id to every node in the tree.
- assignIDs(int) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Assigns unique IDs to all nodes in the tree
- assignLeafModelNumbers(int) - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Assigns numbers to the logistic regression models at the leaves of the tree
- assignLeafModelNumbers(int) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Assigns numbers to the logistic regression models at the leaves of the tree
- assignSubToCenters(KDTreeNode, Instances, int[], int[]) - 类中的方法 weka.core.neighboursearch.KDTree
-
Assigns instances of this node to center.
- associatedConnections(Vector) - 类中的静态方法 weka.gui.beans.BeanConnection
-
Returns a vector of BeanConnections associated with the supplied vector of BeanInstances, i.e.
- AssociationRule(Collection<FPGrowth.BinaryItem>, Collection<FPGrowth.BinaryItem>, FPGrowth.AssociationRule.METRIC_TYPE, int, int, int, int) - 类的构造器 weka.associations.FPGrowth.AssociationRule
-
Construct a new association rule.
- AssociationsPanel - weka.gui.explorer中的类
-
This panel allows the user to select, configure, and run a scheme that learns associations.
- AssociationsPanel() - 类的构造器 weka.gui.explorer.AssociationsPanel
-
Creates the associator panel
- Associator - weka.gui.beans中的类
-
Bean that wraps around weka.associations
- Associator - weka.associations中的接口
- Associator() - 类的构造器 weka.gui.beans.Associator
-
Creates a new
Associator
instance. - AssociatorBeanInfo - weka.gui.beans中的类
-
BeanInfo class for the Associator wrapper bean
- AssociatorBeanInfo() - 类的构造器 weka.gui.beans.AssociatorBeanInfo
- AssociatorCustomizer - weka.gui.beans中的类
-
GUI customizer for the associator wrapper bean
- AssociatorCustomizer() - 类的构造器 weka.gui.beans.AssociatorCustomizer
- AssociatorEvaluation - weka.associations中的类
-
Class for evaluating Associaters.
- AssociatorEvaluation() - 类的构造器 weka.associations.AssociatorEvaluation
-
default constructor
- associatorTipText() - 类中的方法 weka.associations.SingleAssociatorEnhancer
-
Returns the tip text for this property
- aSubsumesB(RuleItem, RuleItem) - 类中的静态方法 weka.associations.CaRuleGeneration
-
Methods that decides whether or not rule a subsumes rule b.
- aSubsumesB(RuleItem, RuleItem) - 类中的静态方法 weka.associations.RuleGeneration
-
Methods that decides whether or not rule a subsumes rule b.
- ATT_ARRAY - 类中的静态变量 weka.core.xml.XMLSerialization
-
the tag whether array or not (yes/no)
- ATT_ARRAY_DEFAULT - 类中的静态变量 weka.core.xml.XMLSerialization
-
default value for attribute ATT_ARRAY
- ATT_CLASS - 类中的静态变量 weka.core.xml.XMLInstances
-
the class attribute
- ATT_CLASS - 类中的静态变量 weka.core.xml.XMLSerialization
-
the tag for the class
- ATT_FORMAT - 类中的静态变量 weka.core.xml.XMLInstances
-
the format attribute (for date attributes)
- ATT_INDEX - 类中的静态变量 weka.core.xml.XMLInstances
-
the index attribute
- ATT_MISSING - 类中的静态变量 weka.core.xml.XMLInstances
-
the missing attribute
- ATT_NAME - 类中的静态变量 weka.core.xml.XMLDocument
-
the "name" attribute.
- ATT_NAME - 类中的静态变量 weka.core.xml.XMLOptions
-
the name attribute.
- ATT_NAME - 类中的静态变量 weka.core.xml.XMLSerialization
-
the tag for the name
- ATT_NULL - 类中的静态变量 weka.core.xml.XMLSerialization
-
the tag whether null or not (yes/no)
- ATT_NULL_DEFAULT - 类中的静态变量 weka.core.xml.XMLSerialization
-
default value for attribute ATT_NULL
- ATT_PRIMITIVE - 类中的静态变量 weka.core.xml.XMLSerialization
-
the tag whether primitive or not (yes/no)
- ATT_PRIMITIVE_DEFAULT - 类中的静态变量 weka.core.xml.XMLSerialization
-
default value for attribute ATT_PRIMITIVE
- ATT_TYPE - 类中的静态变量 weka.core.xml.XMLInstances
-
the type attribute
- ATT_TYPE - 类中的静态变量 weka.core.xml.XMLOptions
-
the type attribute.
- ATT_VALUE - 类中的静态变量 weka.core.xml.XMLOptions
-
the value attribute.
- ATT_VERSION - 类中的静态变量 weka.core.xml.XMLDocument
-
the "version" attribute.
- ATT_VERSION - 类中的静态变量 weka.core.xml.XMLInstances
-
the version attribute
- ATT_VERSION - 类中的静态变量 weka.core.xml.XMLSerialization
-
the version attribute
- ATT_WEIGHT - 类中的静态变量 weka.core.xml.XMLInstances
-
the weight attribute
- attIndex() - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Returns index of attribute for which split was generated.
- attIndex() - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns index of attribute for which split was generated.
- attIndex() - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Returns index of attribute for which split was generated.
- attList_IrrTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the tip text for this property
- attribute() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- attribute(int) - 类中的方法 weka.core.Instance
-
Returns the attribute with the given index.
- attribute(int) - 类中的方法 weka.core.Instances
-
Returns an attribute.
- attribute(String) - 类中的方法 weka.core.Instances
-
Returns an attribute given its name.
- Attribute - weka.core中的类
-
Class for handling an attribute.
- Attribute(String) - 类的构造器 weka.core.Attribute
-
Constructor for a numeric attribute.
- Attribute(String, int) - 类的构造器 weka.core.Attribute
-
Constructor for a numeric attribute with a particular index.
- Attribute(String, String) - 类的构造器 weka.core.Attribute
-
Constructor for a date attribute.
- Attribute(String, String, int) - 类的构造器 weka.core.Attribute
-
Constructor for date attributes with a particular index.
- Attribute(String, String, ProtectedProperties) - 类的构造器 weka.core.Attribute
-
Constructor for a date attribute, where metadata is supplied.
- Attribute(String, FastVector) - 类的构造器 weka.core.Attribute
-
Constructor for nominal attributes and string attributes.
- Attribute(String, FastVector, int) - 类的构造器 weka.core.Attribute
-
Constructor for nominal attributes and string attributes with a particular index.
- Attribute(String, FastVector, ProtectedProperties) - 类的构造器 weka.core.Attribute
-
Constructor for nominal attributes and string attributes, where metadata is supplied.
- Attribute(String, Instances) - 类的构造器 weka.core.Attribute
-
Constructor for relation-valued attributes.
- Attribute(String, Instances, int) - 类的构造器 weka.core.Attribute
-
Constructor for a relation-valued attribute with a particular index.
- Attribute(String, Instances, ProtectedProperties) - 类的构造器 weka.core.Attribute
-
Constructor for relation-valued attributes.
- Attribute(String, ProtectedProperties) - 类的构造器 weka.core.Attribute
-
Constructor for a numeric attribute, where metadata is supplied.
- ATTRIBUTE - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- attributeAsClass() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
sets the current attribute as class attribute, i.e.
- attributeAsClass() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
sets the current selected Attribute as class attribute, i.e.
- attributeAsClassAt(int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
sets the attribute at the given col index as the new class attribute
- attributeAsClassAt(int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
sets the attribute at the given col index as the new class attribute, i.e.
- AttributeEvaluator - weka.attributeSelection中的接口
-
Interface for classes that evaluate attributes individually.
- attributeEvaluatorTipText() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Returns the tip text for this property
- attributeEvaluatorTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- attributeEvaluatorTipText() - 类中的方法 weka.attributeSelection.RankSearch
-
Returns the tip text for this property
- AttributeExpression - weka.core中的类
-
A general purpose class for parsing mathematical expressions involving attribute values.
- AttributeExpression() - 类的构造器 weka.core.AttributeExpression
- attributeIndexesTipText() - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Returns the tip text for this property
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns the tip text for this property.
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Returns the tip text for this property
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Returns the tip text for this property
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns the tip text for this property
- attributeIndexTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.core.NormalizableDistance
-
Returns the tip text for this property.
- attributeIndicesTipText() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Returns the tip text for this property
- attributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- attributeList(BitSet) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
converts a BitSet into a list of attribute indexes
- AttributeListPanel - weka.gui中的类
-
Creates a panel that displays the attributes contained in a set of instances, letting the user select a single attribute for inspection.
- AttributeListPanel() - 类的构造器 weka.gui.AttributeListPanel
-
Creates the attribute selection panel with no initial instances.
- AttributeLocator - weka.core中的类
-
This class locates and records the indices of a certain type of attributes, recursively in case of Relational attributes.
- AttributeLocator(Instances, int) - 类的构造器 weka.core.AttributeLocator
-
Initializes the AttributeLocator with the given data for the specified type of attribute.
- AttributeLocator(Instances, int, int[]) - 类的构造器 weka.core.AttributeLocator
-
initializes the AttributeLocator with the given data for the specified type of attribute.
- AttributeLocator(Instances, int, int, int) - 类的构造器 weka.core.AttributeLocator
-
Initializes the AttributeLocator with the given data for the specified type of attribute.
- attributeNamePrefixTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- attributeNames() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the attribute names.
- attributeNames() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the attribute names.
- attributeNameTipText() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns the tip text for this property.
- attributeNameTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Returns the tip text for this property
- AttributePanel - weka.gui.visualize中的类
-
This panel displays one dimensional views of the attributes in a dataset.
- AttributePanel() - 类的构造器 weka.gui.visualize.AttributePanel
- AttributePanel(Color) - 类的构造器 weka.gui.visualize.AttributePanel
-
This constructs an attributePanel.
- AttributePanelEvent - weka.gui.visualize中的类
-
Class encapsulating a change in the AttributePanel's selected x and y attributes.
- AttributePanelEvent(boolean, boolean, int) - 类的构造器 weka.gui.visualize.AttributePanelEvent
-
Constructor
- AttributePanelListener - weka.gui.visualize中的接口
-
Interface for classes that want to listen for Attribute selection changes in the attribute panel
- attributeRangeTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
- AttributeSelectedClassifier - weka.classifiers.meta中的类
-
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
- AttributeSelectedClassifier() - 类的构造器 weka.classifiers.meta.AttributeSelectedClassifier
-
Default constructor.
- AttributeSelection - weka.attributeSelection中的类
-
Attribute selection class.
- AttributeSelection - weka.filters.supervised.attribute中的类
-
A supervised attribute filter that can be used to select attributes.
- AttributeSelection() - 类的构造器 weka.attributeSelection.AttributeSelection
-
constructor.
- AttributeSelection() - 类的构造器 weka.filters.supervised.attribute.AttributeSelection
-
Constructor
- attributeSelectionChange(AttributePanelEvent) - 接口中的方法 weka.gui.visualize.AttributePanelListener
-
Called when the user clicks on an attribute bar
- attributeSelectionMethodTipText() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns the tip text for this property
- AttributeSelectionPanel - weka.gui中的类
-
Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).
- AttributeSelectionPanel - weka.gui.explorer中的类
-
This panel allows the user to select and configure an attribute evaluator and a search method, set the attribute of the current dataset to be used as the class, and perform attribute selection using one of two selection modes (select using all the training data or perform a n-fold cross validation---on each trial selecting features using n-1 folds of the data).
- AttributeSelectionPanel() - 类的构造器 weka.gui.AttributeSelectionPanel
-
Creates the attribute selection panel with no initial instances.
- AttributeSelectionPanel() - 类的构造器 weka.gui.explorer.AttributeSelectionPanel
-
Creates the classifier panel
- AttributeSelectionPanel(boolean, boolean, boolean, boolean) - 类的构造器 weka.gui.AttributeSelectionPanel
-
Creates the attribute selection panel with no initial instances.
- AttributeSetEvaluator - weka.attributeSelection中的类
-
Abstract attribute set evaluator.
- AttributeSetEvaluator() - 类的构造器 weka.attributeSelection.AttributeSetEvaluator
- attributeSparse(int) - 类中的方法 weka.core.Instance
-
Returns the attribute with the given index.
- attributeSparse(int) - 类中的方法 weka.core.SparseInstance
-
Returns the attribute associated with the internal index.
- attributeStats(int) - 类中的方法 weka.core.Instances
-
Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
- AttributeStats - weka.core中的类
-
A Utility class that contains summary information on an the values that appear in a dataset for a particular attribute.
- AttributeStats() - 类的构造器 weka.core.AttributeStats
- attributesToString() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Make a string from the attribues list.
- attributeString(Instances) - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Gets the string describing the attributes the split depends on.
- attributeString(Instances) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Gets the string describing the attributes the split depends on.
- attributeString(Instances) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Gets the string describing the attributes the split depends on.
- AttributeSummarizer - weka.gui.beans中的类
-
Bean that encapsulates displays bar graph summaries for attributes in a data set.
- AttributeSummarizer() - 类的构造器 weka.gui.beans.AttributeSummarizer
-
Creates a new
AttributeSummarizer
instance. - AttributeSummarizerBeanInfo - weka.gui.beans中的类
-
Bean info class for the attribute summarizer bean
- AttributeSummarizerBeanInfo() - 类的构造器 weka.gui.beans.AttributeSummarizerBeanInfo
- AttributeSummaryPanel - weka.gui中的类
-
This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.
- AttributeSummaryPanel() - 类的构造器 weka.gui.AttributeSummaryPanel
-
Creates the instances panel with no initial instances.
- attributeToDoubleArray(int) - 类中的方法 weka.core.Instances
-
Gets the value of all instances in this dataset for a particular attribute.
- AttributeTransformer - weka.attributeSelection中的接口
-
Abstract attribute transformer.
- attributeTypeTipText() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns the tip text for this property
- attributeTypeTipText() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Returns the tip text for this property
- attributeTypeToString(int) - 类中的静态方法 weka.core.CheckScheme
-
returns a string representation of the attribute type
- AttributeValueLiteral - weka.associations.tertius中的类
- AttributeValueLiteral(Predicate, String, int, int, int) - 类的构造器 weka.associations.tertius.AttributeValueLiteral
- AttributeVisualizationPanel - weka.gui中的类
-
Creates a panel that shows a visualization of an attribute in a dataset.
- AttributeVisualizationPanel() - 类的构造器 weka.gui.AttributeVisualizationPanel
-
Constructor - If used then the class will not show the class selection combo box.
- AttributeVisualizationPanel(boolean) - 类的构造器 weka.gui.AttributeVisualizationPanel
-
Constructor.
- attrIndexRangeTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns the tip text for this property
- attrSplit(int, Instances) - 类中的方法 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Finds the best splitting point for an attribute in the instances
- attrSplit(int, Instances) - 接口中的方法 weka.classifiers.trees.m5.SplitEvaluate
-
Finds the best splitting point for an attribute in the instances
- attrSplit(int, Instances) - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Finds the best splitting point for an attribute in the instances
- attsToEliminatePerIterationTipText() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns a tip text for this property suitable for display in the GUI
- AUTHOR - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The name(s) of the author(s), in the format described in the LaTeX book.
- autoBuildTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- autoKeyGenerationTipText() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the tip text for this property.
- AVERAGE_RULE - 类中的静态变量 weka.classifiers.meta.Vote
-
combination rule: Average of Probabilities
- AveragingResultProducer - weka.experiment中的类
-
Takes the results from a ResultProducer and submits the average to the result listener.
- AveragingResultProducer() - 类的构造器 weka.experiment.AveragingResultProducer
- avgCost() - 类中的方法 weka.classifiers.Evaluation
-
Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
- avgProb - 类中的变量 weka.classifiers.lazy.kstar.KStarWrapper
-
used/reused to hold the average transformation probability
B
- B_ENTROPY - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- B_SPHERE - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
-
Blend setting modes
- BackgroundDesktopPane(String) - 类的构造器 weka.gui.Main.BackgroundDesktopPane
-
intializes the desktop pane.
- backQuoteChars(String) - 类中的静态方法 weka.core.Utils
-
Converts carriage returns and new lines in a string into \r and \n.
- backward(PaceMatrix, IntVector, int, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Backward ordering of columns in terms of response explanation.
- Bagging - weka.classifiers.meta中的类
-
Class for bagging a classifier to reduce variance.
- Bagging() - 类的构造器 weka.classifiers.meta.Bagging
-
Constructor.
- bagSizePercentTipText() - 类中的方法 weka.classifiers.meta.Bagging
-
Returns the tip text for this property
- bagSizePercentTipText() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns the tip text for this property
- balanceClassTipText() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Returns the tip text for this property
- balancedTipText() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns the tip text for this property
- BallNode - weka.core.neighboursearch.balltrees中的类
-
Class representing a node of a BallTree.
- BallNode(int) - 类的构造器 weka.core.neighboursearch.balltrees.BallNode
-
Constructor.
- BallNode(int, int, int) - 类的构造器 weka.core.neighboursearch.balltrees.BallNode
-
Creates a new instance of BallNode.
- BallNode(int, int, int, Instance, double) - 类的构造器 weka.core.neighboursearch.balltrees.BallNode
-
Creates a new instance of BallNode.
- BallSplitter - weka.core.neighboursearch.balltrees中的类
-
Abstract class for splitting a ball tree's BallNode.
- BallSplitter() - 类的构造器 weka.core.neighboursearch.balltrees.BallSplitter
-
default constructor.
- BallSplitter(int[], Instances, EuclideanDistance) - 类的构造器 weka.core.neighboursearch.balltrees.BallSplitter
-
Creates a new instance of BallSplitter.
- ballSplitterTipText() - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Returns the tip text for this property.
- BallTree - weka.core.neighboursearch中的类
-
Class implementing the BallTree/Metric Tree algorithm for nearest neighbour search.
The connection to dataset is only a reference. - BallTree() - 类的构造器 weka.core.neighboursearch.BallTree
-
Creates a new instance of BallTree.
- BallTree(Instances) - 类的构造器 weka.core.neighboursearch.BallTree
-
Creates a new instance of BallTree.
- BallTreeConstructor - weka.core.neighboursearch.balltrees中的类
-
Abstract class for constructing a BallTree .
- BallTreeConstructor() - 类的构造器 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Creates a new instance of BallTreeConstructor.
- ballTreeConstructorTipText() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the tip text for this property.
- baseTipText() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the tip text for this property.
- BATCH - 接口中的静态变量 weka.core.converters.Loader
- BATCH - 接口中的静态变量 weka.core.converters.Saver
- BATCH_FINISHED - 类中的静态变量 weka.gui.beans.IncrementalClassifierEvent
- BATCH_FINISHED - 类中的静态变量 weka.gui.beans.InstanceEvent
- BATCH_FINISHED - 类中的静态变量 weka.gui.streams.InstanceEvent
-
Specifies that the batch of instances is finished
- BatchClassifierEvent - weka.gui.beans中的类
-
Class encapsulating a built classifier and a batch of instances to test on.
- BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int) - 类的构造器 weka.gui.beans.BatchClassifierEvent
-
Creates a new
BatchClassifierEvent
instance. - BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int, int, int) - 类的构造器 weka.gui.beans.BatchClassifierEvent
-
Creates a new
BatchClassifierEvent
instance. - BatchClassifierListener - weka.gui.beans中的接口
-
Interface to something that can process a BatchClassifierEvent
- BatchClustererEvent - weka.gui.beans中的类
-
Class encapsulating a built clusterer and a batch of instances to test on.
- BatchClustererEvent(Object, Clusterer, DataSetEvent, int, int, int) - 类的构造器 weka.gui.beans.BatchClustererEvent
-
Creates a new
BatchClustererEvent
instance. - BatchClustererListener - weka.gui.beans中的接口
-
Interface to something that can process a BatchClustererEvent
- BatchConverter - weka.core.converters中的接口
-
Marker interface for a loader/saver that can retrieve instances in batch mode
- batchFilterFile(Filter, String[]) - 类中的静态方法 weka.filters.Filter
-
Method for testing filters ability to process multiple batches.
- batchFinished() - 类中的方法 weka.filters.Filter
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.MultiFilter
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.SimpleBatchFilter
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.SimpleStreamFilter
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Signifies that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.supervised.instance.Resample
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Signifies that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.Center
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Signifies that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Signifies that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.ReplaceMissingValues
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.Standardize
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Signifies that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Signifies that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.gui.streams.InstanceJoiner
-
Signify that this batch of input to the filter is finished.
- batchFinished() - 类中的方法 weka.gui.streams.InstanceSavePanel
- batchFinished() - 类中的方法 weka.gui.streams.InstanceTable
- batchFinished() - 类中的方法 weka.gui.streams.InstanceViewer
- BAYES - 接口中的静态变量 weka.classifiers.bayes.net.search.local.Scoreable
-
score types
- BayesianLogisticRegression - weka.classifiers.bayes中的类
-
Implements Bayesian Logistic Regression for both Gaussian and Laplace Priors.
For more information, see
Alexander Genkin, David D. - BayesianLogisticRegression() - 类的构造器 weka.classifiers.bayes.BayesianLogisticRegression
- BayesNet - weka.classifiers.bayes中的类
-
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. - BayesNet - weka.datagenerators.classifiers.classification中的类
-
Generates random instances based on a Bayes network.
- BayesNet - 接口中的静态变量 weka.core.Drawable
- BayesNet() - 类的构造器 weka.classifiers.bayes.BayesNet
- BayesNet() - 类的构造器 weka.datagenerators.classifiers.classification.BayesNet
-
initializes the generator
- BayesNetEstimator - weka.classifiers.bayes.net.estimate中的类
-
BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure has been learned.
- BayesNetEstimator() - 类的构造器 weka.classifiers.bayes.net.estimate.BayesNetEstimator
- BayesNetGenerator - weka.classifiers.bayes.net中的类
-
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. - BayesNetGenerator() - 类的构造器 weka.classifiers.bayes.net.BayesNetGenerator
-
Constructor for BayesNetGenerator.
- BDeu - 接口中的静态变量 weka.classifiers.bayes.net.search.local.Scoreable
- BEAN_EXECUTING - 类中的静态变量 weka.gui.beans.BeanInstance
- BeanCommon - weka.gui.beans中的接口
-
Interface specifying routines that all weka beans should implement in order to allow the bean environment to exercise some control over the bean and also to allow the bean to exercise some control over connections.
- BeanConnection - weka.gui.beans中的类
-
Class for encapsulating a connection between two beans.
- BeanConnection(BeanInstance, BeanInstance, EventSetDescriptor) - 类的构造器 weka.gui.beans.BeanConnection
-
Creates a new
BeanConnection
instance. - BeanInstance - weka.gui.beans中的类
-
Class that manages a set of beans.
- BeanInstance(JComponent, Object, int, int) - 类的构造器 weka.gui.beans.BeanInstance
-
Creates a new
BeanInstance
instance. - BeanInstance(JComponent, String, int, int) - 类的构造器 weka.gui.beans.BeanInstance
-
Creates a new
BeanInstance
instance given the fully qualified name of the bean - BeanVisual - weka.gui.beans中的类
-
BeanVisual encapsulates icons and label for a given bean.
- BeanVisual(String, String, String) - 类的构造器 weka.gui.beans.BeanVisual
-
Constructor
- BestFirst - weka.attributeSelection中的类
-
BestFirst:
Searches the space of attribute subsets by greedy hillclimbing augmented with a backtracking facility. - BestFirst() - 类的构造器 weka.attributeSelection.BestFirst
-
Constructor
- BestFirst.Link2 - weka.attributeSelection中的类
-
Class for a node in a linked list.
- BestFirst.LinkedList2 - weka.attributeSelection中的类
-
Class for handling a linked list.
- betaTipText() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns the tip text for this property
- BetaVector - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Array for storing coefficients of Bayesian regression model.
- BFTree - weka.classifiers.trees中的类
-
Class for building a best-first decision tree classifier.
- BFTree() - 类的构造器 weka.classifiers.trees.BFTree
- bias() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the bias of each binary SMO.
- bias() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the bias of each binary SMO.
- biasTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- biasTipText() - 类中的方法 weka.classifiers.misc.VFI
-
Returns the tip text for this property
- biasToUniformClassTipText() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns the tip text for this property.
- BIBTEX_ENDTAG - 类中的静态变量 weka.core.TechnicalInformationHandlerJavadoc
-
the end comment tag for inserting the generated BibTex
- BIBTEX_STARTTAG - 类中的静态变量 weka.core.TechnicalInformationHandlerJavadoc
-
the start comment tag for inserting the generated BibTex
- BIFFileTipText() - 类中的方法 weka.classifiers.bayes.BayesNet
- BIFFormatException - weka.gui.graphvisualizer中的异常错误
-
This is the Exception thrown by BIFParser, if there was an error in parsing the XMLBIF string or input stream.
- BIFFormatException(String) - 异常错误的构造器 weka.gui.graphvisualizer.BIFFormatException
- BIFParser - weka.gui.graphvisualizer中的类
-
This class parses an inputstream or a string in XMLBIF ver.
- BIFParser(InputStream, FastVector, FastVector) - 类的构造器 weka.gui.graphvisualizer.BIFParser
-
Constructor (if our input is an InputStream)
- BIFParser(String, FastVector, FastVector) - 类的构造器 weka.gui.graphvisualizer.BIFParser
-
Constructor (if our input is a String)
- BIFReader - weka.classifiers.bayes.net中的类
-
Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format.
For more details on XML BIF see:
Fabio Cozman, Marek Druzdzel, Daniel Garcia (1998). - BIFReader() - 类的构造器 weka.classifiers.bayes.net.BIFReader
-
the default constructor
- bigF(double, double) - 类中的静态方法 weka.classifiers.bayes.BayesianLogisticRegression
-
This is a convient function that defines and upper bound (Delta>0) for values of r(i) reachable by updates in the trust region.
- binarizeNumericAttributesTipText() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Returns the tip text for this property
- binarizeNumericAttributesTipText() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Returns the tip text for this property
- BINARY - 类中的静态变量 weka.gui.beans.SerializedModelSaver
- BINARY_ATTRIBUTES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle binary attributes
- BINARY_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle binary classes
- binaryAttributesNominalTipText() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Returns the tip text for this property
- binaryAttributesNominalTipText() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Returns the tip text for this property
- BinaryItem(Attribute, int) - 类的构造器 weka.associations.FPGrowth.BinaryItem
- BinarySMO() - 类的构造器 weka.classifiers.functions.SMO.BinarySMO
- BinarySparseInstance - weka.core中的类
-
Class for storing a binary-data-only instance as a sparse vector.
- BinarySparseInstance(double, double[]) - 类的构造器 weka.core.BinarySparseInstance
-
Constructor that generates a sparse instance from the given parameters.
- BinarySparseInstance(double, int[], int) - 类的构造器 weka.core.BinarySparseInstance
-
Constructor that inititalizes instance variable with given values.
- BinarySparseInstance(int) - 类的构造器 weka.core.BinarySparseInstance
-
Constructor of an instance that sets weight to one, all values to 1, and the reference to the dataset to null.
- BinarySparseInstance(Instance) - 类的构造器 weka.core.BinarySparseInstance
-
Constructor that generates a sparse instance from the given instance.
- BinarySparseInstance(SparseInstance) - 类的构造器 weka.core.BinarySparseInstance
-
Constructor that copies the info from the given instance.
- binarySplitsTipText() - 类中的方法 weka.classifiers.rules.PART
-
Returns the tip text for this property
- binarySplitsTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- binarySplitsTipText() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the tip text for this property
- binaryToKOML(String, String) - 类中的静态方法 weka.core.xml.SerialUIDChanger
-
converts a binary file into a KOML XML file
- BinC45ModelSelection - weka.classifiers.trees.j48中的类
-
Class for selecting a C4.5-like binary (!) split for a given dataset.
- BinC45ModelSelection(int, Instances) - 类的构造器 weka.classifiers.trees.j48.BinC45ModelSelection
-
Initializes the split selection method with the given parameters.
- BinC45Split - weka.classifiers.trees.j48中的类
-
Class implementing a binary C4.5-like split on an attribute.
- BinC45Split(int, int, double) - 类的构造器 weka.classifiers.trees.j48.BinC45Split
-
Initializes the split model.
- binomialDistribution(double, double, double) - 类中的静态方法 weka.associations.RuleGeneration
-
calculates the probability using a binomial distribution.
- binomialStandardError(double, int) - 类中的静态方法 weka.core.Statistics
-
Computes standard error for observed values of a binomial random variable.
- binomP(double, double, double) - 类中的方法 weka.classifiers.lazy.LBR
-
Significance test binomp:
- binSplitTipText() - 类中的方法 weka.classifiers.trees.FT
-
Returns the tip text for this property
- binsTipText() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the tip text for this property
- binsTipText() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Returns the tip text for this property
- binValueTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- biprob(double, double, double) - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Significance test
- BIRCHCluster - weka.datagenerators.clusterers中的类
-
Cluster data generator designed for the BIRCH System
Dataset is generated with instances in K clusters.
Instances are 2-d data points.
Each cluster is characterized by the number of data points in itits radius and its center. - BIRCHCluster() - 类的构造器 weka.datagenerators.clusterers.BIRCHCluster
-
initializes the generator with default values
- blocker(boolean) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
A function used to stop the code that called buildclassifier from continuing on before the user has finished the decision tree.
- BMAEstimator - weka.classifiers.bayes.net.estimate中的类
-
BMAEstimator estimates conditional probability tables of a Bayes network using Bayes Model Averaging (BMA).
- BMAEstimator() - 类的构造器 weka.classifiers.bayes.net.estimate.BMAEstimator
- BMPWriter - weka.gui.visualize中的类
-
This class takes any JComponent and outputs it to a BMP-file.
- BMPWriter() - 类的构造器 weka.gui.visualize.BMPWriter
-
initializes the object
- BMPWriter(JComponent) - 类的构造器 weka.gui.visualize.BMPWriter
-
initializes the object with the given Component
- BMPWriter(JComponent, File) - 类的构造器 weka.gui.visualize.BMPWriter
-
initializes the object with the given Component and filename
- Body - weka.associations.tertius中的类
-
Class representing the body of a rule.
- Body() - 类的构造器 weka.associations.tertius.Body
-
Constructor without storing the counter-instances.
- Body(Instances) - 类的构造器 weka.associations.tertius.Body
-
Constructor storing the counter-instances.
- bodyContains(Literal) - 类中的方法 weka.associations.tertius.Rule
-
Test if the body of the rule contains a literal.
- BOOK - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
A book with an explicit publisher.
- BOOKLET - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
A work that is printed and bound, but without a named publisher or sponsoring institution.
- BOOKTITLE - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
Title of a book, part of which is being cited.
- BOOL - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for BOOL used for reading experiment results.
- BOOLEAN - 接口中的静态变量 weka.core.mathematicalexpression.sym
- BOOLEAN - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- booleanColsTipText() - 类中的方法 weka.datagenerators.ClusterGenerator
-
Returns the tip text for this property
- boost() - 类中的方法 weka.classifiers.trees.ADTree
-
Performs a single boosting iteration, using two-class optimized method.
- BottomUpConstructor - weka.core.neighboursearch.balltrees中的类
-
The class that constructs a ball tree bottom up.
- BottomUpConstructor() - 类的构造器 weka.core.neighboursearch.balltrees.BottomUpConstructor
-
Creates a new instance of BottomUpConstructor.
- BoundaryPanel - weka.gui.boundaryvisualizer中的类
-
BoundaryPanel.
- BoundaryPanel(int, int) - 类的构造器 weka.gui.boundaryvisualizer.BoundaryPanel
-
Creates a new
BoundaryPanel
instance. - BoundaryPanelDistributed - weka.gui.boundaryvisualizer中的类
-
This class extends BoundaryPanel with code for distributing the processing necessary to create a visualization among a list of remote machines.
- BoundaryPanelDistributed(int, int) - 类的构造器 weka.gui.boundaryvisualizer.BoundaryPanelDistributed
-
Creates a new
BoundaryPanelDistributed
instance. - BoundaryVisualizer - weka.gui.boundaryvisualizer中的类
-
BoundaryVisualizer.
- BoundaryVisualizer() - 类的构造器 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Creates a new
BoundaryVisualizer
instance. - branchInstanceGoesDown(Instance) - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Gets the index of the branch that an instance applies to.
- branchInstanceGoesDown(Instance) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Gets the index of the branch that an instance applies to.
- branchInstanceGoesDown(Instance) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Gets the index of the branch that an instance applies to.
- BrowserHelper - weka.gui中的类
-
A little helper class for browser related stuff.
- BrowserHelper() - 类的构造器 weka.gui.BrowserHelper
- bubbleSubsetSort(List<ScatterSearchV1.Subset>) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Sort a List of subsets according to their merits
- build(String, String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Build a tree from the given property with the given delimitor
- buildAssociations(Instances) - 类中的方法 weka.associations.Apriori
-
Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.
- buildAssociations(Instances) - 接口中的方法 weka.associations.Associator
-
Generates an associator.
- buildAssociations(Instances) - 类中的方法 weka.associations.FilteredAssociator
-
Build the associator on the filtered data.
- buildAssociations(Instances) - 类中的方法 weka.associations.FPGrowth
-
Method that generates all large item sets with a minimum support, and from these all association rules with a minimum metric (i.e.
- buildAssociations(Instances) - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Extracts all sequential patterns out of a given sequential data set and prints out the results.
- buildAssociations(Instances) - 类中的方法 weka.associations.PredictiveApriori
-
Method that generates all large itemsets with a minimum support, and from these all association rules.
- buildAssociations(Instances) - 类中的方法 weka.associations.Tertius
-
Method that launches the search to find the rules with the highest confirmation.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.AODE
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
(1) Set the data to the class attribute m_Instances. (2)Call the method initialize() to initialize the values.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.HNB
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.NaiveBayesSimple
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.bayes.WAODE
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.Classifier
-
Generates a classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Method for building the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.IsotonicRegression
-
Builds an isotonic regression model given the supplied training data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Build lms regression
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.LibSVM
-
builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.LinearRegression
-
Builds a regression model for the given data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.Logistic
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
Call this function to build and train a neural network for the training data provided.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.PaceRegression
-
Builds a pace regression model for the given data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.PLSClassifier
-
builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Builds a simple linear regression model given the supplied training data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Builds the logistic regression using LogitBoost.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.SMO
-
Method for building the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.SMOreg
-
Method for building the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.SPegasos
-
Method for building the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
learn SVM parameters from data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
learn SVM parameters from data using Smola's SMO algorithm.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
learn SVM parameters from data using Keerthi's SMO algorithm.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Builds the ensemble of perceptrons.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.functions.Winnow
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.IteratedSingleClassifierEnhancer
-
Stump method for building the classifiers.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.lazy.IB1
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.lazy.IBk
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.lazy.KStar
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.lazy.LBR
-
For lazy learning, building classifier is only to prepare their inputs until classification time.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.lazy.LWL
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Boosting method.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Build the classifier on the supplied data
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Build the classifier on the dimensionally reduced data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.Bagging
-
Bagging method.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.ClassificationViaRegression
-
Builds the classifiers.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Builds the model of the base learner.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.Dagging
-
Bagging method.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.Decorate
-
Build Decorate classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.END
-
Builds the committee of randomizable classifiers.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Build the classifier on the filtered data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.GridSearch
-
builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Builds the boosted classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.MetaCost
-
Builds the model of the base learner.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Method for building this classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Builds the classifiers.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.MultiScheme
-
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Builds tree recursively.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Builds tree recursively.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
-
Builds the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Builds the classifiers.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Builds the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.RandomCommittee
-
Builds the committee of randomizable classifiers.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
builds the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.RotationForest
-
builds the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.Stacking
-
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.meta.Vote
-
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MDD
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MIBoost
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MIDD
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MIEMDD
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MILR
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MINND
-
As normal Nearest Neighbour algorithm does, it's lazy and simply records the exemplar information (i.e.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MISMO
-
Method for building the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MISVM
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.MIWrapper
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.mi.SimpleMI
-
Builds the classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.misc.HyperPipes
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
loads only the serialized classifier
- buildClassifier(Instances) - 类中的方法 weka.classifiers.misc.VFI
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Throw an exception - PMML models are pre-built.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Builds a single rule learner with REP dealing with nominal classes or numeric classes.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.DTNB
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.JRip
-
Builds Ripper in the order of class frequencies.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.NNge
-
Generates a classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.OneR
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.PART
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.part.MakeDecList
-
Builds dec list.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.Prism
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.Ridor
-
Builds a ripple-down manner rule learner.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.rules.ZeroR
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.ADTree
-
Builds a classifier for a set of instances.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.BFTree
-
Method for building a BestFirst decision tree classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.DecisionStump
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.FT
-
Builds the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.ft.FTInnerNode
-
Method for building a Functional Inner tree (only called for the root node).
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.ft.FTLeavesNode
-
Method for building a Functional Leaves tree (only called for the root node).
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.ft.FTNode
-
Method for building a Functional tree (only called for the root node).
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Method for building a Functional Tree (only called for the root node).
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.Id3
-
Builds Id3 decision tree classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Creates a C4.5-type split on the given data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.J48
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTree
-
Method for building a pruneable classifier tree.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Method for building a pruneable classifier tree.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Creates a C4.5-type split on the given data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Builds the classifier split model for the given set of instances.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Method for building a classifier tree.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
builds m_graftdistro using the passed data
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeClassifierTree
-
Method for building a naive bayes classifier tree
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Build the no-split node
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Creates a NBTree-type split on the given data.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.NoSplit
-
Creates a "no-split"-split for a given set of instances.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.j48.PruneableClassifierTree
-
Method for building a pruneable classifier tree.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.J48graft
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.LADTree
-
Builds a classifier for a set of instances.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.LMT
-
Builds the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Method for building a logistic model tree (only called for the root node).
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Builds the logistic regression model usiing LogitBoost.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Method not in use
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.m5.PreConstructedLinearModel
-
Builds the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.m5.Rule
-
Generates a single rule or m5 model tree.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Build this node (find an attribute and split point)
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.NBTree
-
Generates the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.RandomForest
-
Builds a classifier for a set of instances.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.RandomTree
-
Builds classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.REPTree
-
Builds classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Build the classifier.
- buildClassifier(Instances) - 类中的方法 weka.classifiers.trees.UserClassifier
-
Call this function to build a decision tree for the training data provided.
- buildClassifier(Instances, double[][], double[][]) - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Builds the split.
- buildClassifierForNode(ND.NDTree, Instances) - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
-
Builds the classifier for one node.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.AbstractClusterer
-
Generates a clusterer.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.CLOPE
-
Generate Clustering via CLOPE
- buildClusterer(Instances) - 接口中的方法 weka.clusterers.Clusterer
-
Generates a clusterer.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.Cobweb
-
Builds the clusterer.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.DBSCAN
-
Generate Clustering via DBSCAN
- buildClusterer(Instances) - 类中的方法 weka.clusterers.EM
-
Generates a clusterer.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.FarthestFirst
-
Generates a clusterer.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.FilteredClusterer
-
Build the clusterer on the filtered data.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.HierarchicalClusterer
- buildClusterer(Instances) - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Builds a clusterer for a set of instances.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.OPTICS
-
Generate Clustering via OPTICS
- buildClusterer(Instances) - 类中的方法 weka.clusterers.sIB
-
Generates a clusterer.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.SimpleKMeans
-
Generates a clusterer.
- buildClusterer(Instances) - 类中的方法 weka.clusterers.XMeans
-
Generates the X-Means clusterer.
- buildCNN() - 类中的方法 weka.classifiers.mi.CitationKNN
-
generates all the variables associated to the citation classifier
- buildDecList(Instances, boolean) - 类中的方法 weka.classifiers.rules.part.C45PruneableDecList
-
Builds the partial tree without hold out set.
- buildDecList(Instances, boolean) - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Builds the partial tree without hold out set.
- buildDecList(Instances, Instances, boolean) - 类中的方法 weka.classifiers.rules.part.PruneableDecList
-
Builds the partial tree with hold out set
- buildDistribution(double, double) - 类中的方法 weka.associations.PriorEstimation
-
updates the distribution of the confidence values.
- buildEstimator(Estimator, String[], boolean) - 类中的静态方法 weka.estimators.Estimator
-
Build an estimator using the options.
- buildEstimator(Estimator, Instances, int, int, int, boolean) - 类中的静态方法 weka.estimators.Estimator
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.ASEvaluation
-
Generates a attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Generates a attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Initializes a chi-squared attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Generates a attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.ConsistencySubsetEval
-
Generates a attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Generates a attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Initializes a filtered attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Initializes a filtered attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Initializes a gain ratio attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Initializes an information gain attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Initializes the singular values/vectors and performs the analysis
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Initializes a OneRAttribute attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Initializes principal components and performs the analysis
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Initializes a ReliefF attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Initializes the evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Initializes a symmetrical uncertainty attribute evaluator.
- buildEvaluator(Instances) - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Generates a attribute evaluator.
- buildGenerator(Instances) - 接口中的方法 weka.gui.boundaryvisualizer.DataGenerator
-
Build the data generator
- buildGenerator(Instances) - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
-
Initialize the generator using the supplied instances
- buildKernel(Instances) - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
builds the kernel with the given data.
- buildKernel(Instances) - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
builds the kernel with the given data
- buildKernel(Instances) - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
builds the kernel with the given data.
- buildKernel(Instances) - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
builds the kernel with the given data.
- buildKernel(Instances) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
builds the kernel with the given data.
- buildKernel(Instances) - 类中的方法 weka.classifiers.mi.supportVector.MIRBFKernel
-
builds the kernel with the given data.
- buildLogisticModelsTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- buildLogisticModelsTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- buildRegressionTreeTipText() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns the tip text for this property
- buildRule(Instances) - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Method for building a pruned partial tree.
- buildRule(Instances, Instances) - 类中的方法 weka.classifiers.rules.part.PruneableDecList
-
Method for building a pruned partial tree.
- buildStructure() - 类中的方法 weka.classifiers.bayes.BayesNet
-
buildStructure determines the network structure/graph of the network.
- buildStructure(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.fixed.FromFile
- buildStructure(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.fixed.NaiveBayes
- buildStructure(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.global.TAN
-
buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
- buildStructure(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
- buildStructure(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.local.TAN
-
buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
- buildStructure(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.SearchAlgorithm
-
buildStructure determines the network structure/graph of the network.
- buildTree() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Builds the ball tree.
- buildTree() - 类中的方法 weka.core.neighboursearch.balltrees.BottomUpConstructor
-
Builds the ball tree bottom up.
- buildTree() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Builds a ball tree middle out.
- buildTree() - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Builds the ball tree top down.
- buildTree(Instances, boolean) - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Builds the tree structure.
- buildTree(Instances, SimpleLinearRegression[][], double, double) - 类中的方法 weka.classifiers.trees.ft.FTInnerNode
-
Method for building the tree structure.
- buildTree(Instances, SimpleLinearRegression[][], double, double) - 类中的方法 weka.classifiers.trees.ft.FTLeavesNode
-
Method for building the tree structure.
- buildTree(Instances, SimpleLinearRegression[][], double, double) - 类中的方法 weka.classifiers.trees.ft.FTNode
-
Method for building the tree structure.
- buildTree(Instances, SimpleLinearRegression[][], double, double) - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Abstract method for building the tree structure.
- buildTree(Instances, SimpleLinearRegression[][], double, double) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Method for building the tree structure.
- buildTree(Instances, Instances, boolean) - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Builds the tree structure with hold out set
- BuiltInArithmetic - weka.core.pmml中的类
-
Built-in function for +, -, *, /.
- BuiltInArithmetic(BuiltInArithmetic.Operator) - 类的构造器 weka.core.pmml.BuiltInArithmetic
-
Construct a new Arithmetic built-in pmml function.
- BuiltInMath - weka.core.pmml中的类
-
Built-in function for min, max, sum, avg, log10, ln, sqrt, abs, exp, pow, threshold, floor, ceil and round.
- BuiltInMath(BuiltInMath.MathFunc) - 类的构造器 weka.core.pmml.BuiltInMath
-
Construct a new built-in pmml Math function.
- BuiltInString - weka.core.pmml中的类
-
Built-in function for uppercase, substring and trimblanks.
- BVDecompose - weka.classifiers中的类
-
Class for performing a Bias-Variance decomposition on any classifier using the method specified in:
Ron Kohavi, David H. - BVDecompose() - 类的构造器 weka.classifiers.BVDecompose
- BVDecomposeSegCVSub - weka.classifiers中的类
-
This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in (1).
The Kohavi and Wolpert definition of bias and variance is specified in (2).
The Webb definition of bias and variance is specified in (3).
Geoffrey I. - BVDecomposeSegCVSub() - 类的构造器 weka.classifiers.BVDecomposeSegCVSub
- BYTE - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for BYTE used for reading experiment results.
C
- C45Loader - weka.core.converters中的类
-
Reads a file that is C45 format.
- C45Loader() - 类的构造器 weka.core.converters.C45Loader
- C45ModelSelection - weka.classifiers.trees.j48中的类
-
Class for selecting a C4.5-type split for a given dataset.
- C45ModelSelection(int, Instances) - 类的构造器 weka.classifiers.trees.j48.C45ModelSelection
-
Initializes the split selection method with the given parameters.
- C45PruneableClassifierTree - weka.classifiers.trees.j48中的类
-
Class for handling a tree structure that can be pruned using C4.5 procedures.
- C45PruneableClassifierTree(ModelSelection, boolean, float, boolean, boolean) - 类的构造器 weka.classifiers.trees.j48.C45PruneableClassifierTree
-
Constructor for pruneable tree structure.
- C45PruneableClassifierTreeG - weka.classifiers.trees.j48中的类
-
Class for handling a tree structure that can be pruned using C4.5 procedures and have nodes grafted on.
- C45PruneableClassifierTreeG(ModelSelection, boolean, float, boolean, boolean, boolean) - 类的构造器 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Constructor for pruneable tree structure.
- C45PruneableClassifierTreeG(ModelSelection, Instances, ClassifierSplitModel, boolean, float, boolean, boolean, boolean, boolean) - 类的构造器 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Constructor for pruneable tree structure.
- C45PruneableDecList - weka.classifiers.rules.part中的类
-
Class for handling a partial tree structure pruned using C4.5's pruning heuristic.
- C45PruneableDecList(ModelSelection, double, int) - 类的构造器 weka.classifiers.rules.part.C45PruneableDecList
-
Constructor for pruneable tree structure.
- C45Saver - weka.core.converters中的类
-
Writes to a destination that is in the format used by the C4.5 algorithm.
Therefore it outputs a names and a data file. - C45Saver() - 类的构造器 weka.core.converters.C45Saver
-
Constructor
- C45Split - weka.classifiers.trees.j48中的类
-
Class implementing a C4.5-type split on an attribute.
- C45Split(int, int, double) - 类的构造器 weka.classifiers.trees.j48.C45Split
-
Initializes the split model.
- CachedKernel - weka.classifiers.functions.supportVector中的类
-
Base class for RBFKernel and PolyKernel that implements a simple LRU.
- CachedKernel() - 类的构造器 weka.classifiers.functions.supportVector.CachedKernel
-
default constructor - does nothing.
- cacheKeyNameTipText() - 类中的方法 weka.experiment.DatabaseResultListener
-
Returns the tip text for this property
- cacheSizeTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- cacheSizeTipText() - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Returns the tip text for this property
- cacheSizeTipText() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the tip text for this property
- CacheTable() - 类的构造器 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Constructs a new hashtable with a default capacity and load factor.
- CacheTable(int, float) - 类的构造器 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Constructs a new hashtable with a default capacity and load factor.
- calcCentroidPivot(int[], Instances) - 类中的静态方法 weka.core.neighboursearch.balltrees.BallNode
-
Calculates the centroid pivot of a node.
- calcCentroidPivot(int, int, int[], Instances) - 类中的静态方法 weka.core.neighboursearch.balltrees.BallNode
-
Calculates the centroid pivot of a node.
- calcColumnWidth(int) - 类中的方法 weka.gui.JTableHelper
-
calcs the optimal column width of the given column
- calcColumnWidth(JTable, int) - 类中的静态方法 weka.gui.JTableHelper
-
Calculates the optimal width for the column of the given table.
- calcFullMargins(BayesNet) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
- calcGraph(int, int) - 类中的方法 weka.gui.AttributeVisualizationPanel
-
Recalculates the barplot or histogram to display, required usually when the attribute is changed or the component is resized.
- calcHeaderWidth(int) - 类中的方法 weka.gui.JTableHelper
-
calcs the optimal header width of the given column
- calcHeaderWidth(JTable, int) - 类中的静态方法 weka.gui.JTableHelper
-
Calculates the optimal width for the header of the given table.
- calcMargins(BayesNet) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
-
Calc marginal distributions of nodes in Bayesian network Note that a connected network is assumed.
- calcNodeScore(int) - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
Calc Node Score for given parent set
- calcOutOfBagTipText() - 类中的方法 weka.classifiers.meta.Bagging
-
Returns the tip text for this property
- calcPivot(BallNode, BallNode, Instances) - 类中的静态方法 weka.core.neighboursearch.balltrees.BallNode
-
Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
- calcPivot(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode, Instances) - 类中的方法 weka.core.neighboursearch.balltrees.BottomUpConstructor
-
Calculates the centroid pivot of a node based on its two child nodes.
- calcPivot(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instances) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Calculates the centroid pivot of a node based on the list of points that it contains (tbe two lists of its children are provided).
- calcPivot(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode, Instances) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
/** Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
- calcRadius(int[], Instances, Instance, DistanceFunction) - 类中的静态方法 weka.core.neighboursearch.balltrees.BallNode
-
Calculates the radius of node.
- calcRadius(int, int, int[], Instances, Instance, DistanceFunction) - 类中的静态方法 weka.core.neighboursearch.balltrees.BallNode
-
Calculates the radius of a node.
- calcRadius(BallNode, BallNode, Instance, DistanceFunction) - 类中的静态方法 weka.core.neighboursearch.balltrees.BallNode
-
Calculates the radius of a node based on its two child nodes (if merging two nodes).
- calcRadius(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode) - 类中的方法 weka.core.neighboursearch.balltrees.BottomUpConstructor
-
Calculates the radius of a node based on its two child nodes.
- calcRadius(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instance, Instances) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Calculates the radius of a node based on the list of points that it contains (the two lists of its children are provided).
- calcRadius(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Calculates the radius of a node based on its two child nodes (if merging two nodes).
- calcScore(BayesNet) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
performCV returns the accuracy calculated using cross validation.
- calcScoreWithExtraParent(int, int) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
Calc Node Score With Added Parent
- calcScoreWithExtraParent(int, int) - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
Calc Node Score With AddedParent
- calcScoreWithMissingParent(int, int) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
Calc Node Score With Parent Deleted
- calcScoreWithMissingParent(int, int) - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
Calc Node Score With Parent Deleted
- calcScoreWithReversedParent(int, int) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
Calc Node Score With Arrow reversed
- calculateAlphas() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Updates the alpha field for all nodes.
- calculateAlphas() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Updates the alpha field for all nodes.
- calculateConfirmation() - 类中的方法 weka.associations.tertius.Rule
-
Calculate the confirmation of this rule.
- calculateDerived() - 类中的方法 weka.experiment.PairedStats
-
Calculates the derived statistics (significance etc).
- calculateDerived() - 类中的方法 weka.experiment.PairedStatsCorrected
-
Calculates the derived statistics (significance etc).
- calculateDerived() - 类中的方法 weka.experiment.Stats
-
Tells the object to calculate any statistics that don't have their values automatically updated during add.
- calculateDistance(Instances) - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
calculate the distances from each instance in a positive bag to each bag.
- calculateOptimistic() - 类中的方法 weka.associations.tertius.Rule
-
Calculate the optimistic estimate of this rule.
- calculatePriorSum(boolean, double) - 类中的方法 weka.associations.PriorEstimation
-
calculates the numerator and the denominator of the prior equation
- calculateStatistics(Instance, int, int, int) - 类中的方法 weka.experiment.PairedCorrectedTTester
-
Computes a paired t-test comparison for a specified dataset between two resultsets.
- calculateStatistics(Instance, int, int, int) - 类中的方法 weka.experiment.PairedTTester
-
Computes a paired t-test comparison for a specified dataset between two resultsets.
- calculateStatistics(Instance, int, int, int) - 接口中的方法 weka.experiment.Tester
-
Computes a paired t-test comparison for a specified dataset between two resultsets.
- calculateStdDevsTipText() - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns the tip text for this property
- calculateTreshhold() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Calculate the treshold of a dataSet given an evaluator
- canAcceptConnection(Class) - 类中的方法 weka.gui.beans.MetaBean
-
Checks to see if any of the inputs to this group implements the supplied listener class
- cancel() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Cancels the incremental saving process.
- cancel() - 类中的方法 weka.core.converters.AbstractSaver
-
Cancels the incremental saving process if the write mode is CANCEL.
- cancel() - 类中的方法 weka.core.converters.DatabaseSaver
-
Cancels the incremental saving process and tries to drop the table if the write mode is CANCEL.
- CANCEL_OPTION - 类中的静态变量 weka.gui.experiment.OutputFormatDialog
-
Signifies a cancelled property selection.
- CANCEL_OPTION - 类中的静态变量 weka.gui.ListSelectorDialog
-
Signifies a cancelled property selection
- CANCEL_OPTION - 类中的静态变量 weka.gui.PropertySelectorDialog
-
Signifies a cancelled property selection
- CANCEL_OPTION - 类中的静态变量 weka.gui.ViewerDialog
-
Signifies a cancelled property selection
- canKeep(Instance, Literal) - 类中的方法 weka.associations.tertius.Body
-
Test if an instance can be kept as a counter-instance, if a new literal is added to this body.
- canKeep(Instance, Literal) - 类中的方法 weka.associations.tertius.Head
-
Test if an instance can be kept as a counter-instance, if a new literal is added to this head.
- canKeep(Instance, Literal) - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if an instance can be kept as a counter-instance, given a new literal.
- canMoveDown(JList) - 类中的静态方法 weka.gui.JListHelper
-
checks whether the selected items can be moved down
- canMoveUp(JList) - 类中的静态方法 weka.gui.JListHelper
-
checks whether the selected items can be moved up
- canRedo() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
return whether there is something on the undo stack that can be performed
- canUndo() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
return whether there is something on the undo stack that can be performed
- canUndo() - 接口中的方法 weka.core.Undoable
-
returns whether an undo is possible, i.e.
- canUndo() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns whether an undo is possible
- canUndo() - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns whether an undo is possible, i.e.
- canUndo() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns whether an undo is possible, i.e.
- capabilities() - 类中的方法 weka.core.Capabilities
-
Returns an Iterator over the stored capabilities
- Capabilities - weka.core中的类
-
A class that describes the capabilites (e.g., handling certain types of attributes, missing values, types of classes, etc.) of a specific classifier.
- Capabilities(CapabilitiesHandler) - 类的构造器 weka.core.Capabilities
-
initializes the capabilities for the given owner
- Capabilities.Capability - weka.core中的Enum Class
-
enumeration of all capabilities
- capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - 类中的方法 weka.gui.explorer.AssociationsPanel
-
method gets called in case of a change event
- capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - 类中的方法 weka.gui.explorer.AttributeSelectionPanel
-
method gets called in case of a change event
- capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - 类中的方法 weka.gui.explorer.ClassifierPanel
-
method gets called in case of a change event
- capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - 类中的方法 weka.gui.explorer.ClustererPanel
-
method gets called in case of a change event
- capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - 接口中的方法 weka.gui.explorer.Explorer.CapabilitiesFilterChangeListener
-
method gets called in case of a change event
- capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
method gets called in case of a change event
- CapabilitiesFilterChangeEvent(Object, Capabilities) - 类的构造器 weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent
-
Constructs a GOECapabilitiesFilterChangeEvent object.
- CapabilitiesFilterDialog() - 类的构造器 weka.gui.GenericObjectEditor.CapabilitiesFilterDialog
-
creates a dialog to choose Capabilities from.
- CapabilitiesHandler - weka.core中的接口
-
Classes implementing this interface return their capabilities in regards to datasets.
- capacity() - 类中的方法 weka.core.FastVector
-
Returns the capacity of the vector.
- capacity() - 类中的方法 weka.core.matrix.DoubleVector
-
Gets the capacity of the vector.
- capacity() - 类中的方法 weka.core.matrix.IntVector
-
Returns the capacity of the vector
- cardinalityTipText() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Returns the tip text for this property
- caretUpdate(CaretEvent) - 类中的方法 weka.gui.LogWindow
-
Called when the caret position is updated.
- caretUpdate(CaretEvent) - 类中的方法 weka.gui.sql.ConnectionPanel
-
Called when the caret position is updated.
- caretUpdate(CaretEvent) - 类中的方法 weka.gui.sql.QueryPanel
-
Called when the caret position is updated.
- carTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- carTipText() - 类中的方法 weka.associations.PredictiveApriori
-
Returns the tip text for this property
- CaRuleGeneration - weka.associations中的类
-
Class implementing the rule generation procedure of the predictive apriori algorithm for class association rules.
- CaRuleGeneration(ItemSet) - 类的构造器 weka.associations.CaRuleGeneration
-
Constructor
- CARuleMiner - weka.associations中的接口
-
Interface for learning class association rules.
- cat(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Combine two vectors together
- CATEGORICAL - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Optype
- cbind(PaceMatrix) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns a new matrix which binds two matrices with columns.
- CEIL - 接口中的静态变量 weka.core.mathematicalexpression.sym
- CEIL - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- Center - weka.filters.unsupervised.attribute中的类
-
Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set).
- Center() - 类的构造器 weka.filters.unsupervised.attribute.Center
- centerDataTipText() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns the tip text for this property
- centerDataTipText() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Returns the tip text for this property
- centerHorizontal(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
center set of nodes half way between left and right most node in the list
- centerInstances(Instances, int[], double) - 类中的方法 weka.core.neighboursearch.KDTree
-
Assigns instances to centers using KDTree.
- centerVertical(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
center set of nodes half way between top and bottom most node in the list
- CfsSubsetEval - weka.attributeSelection中的类
-
CfsSubsetEval :
Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.
Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.
For more information see:
M. - CfsSubsetEval() - 类的构造器 weka.attributeSelection.CfsSubsetEval
-
Constructor
- change() - 类中的方法 weka.associations.RuleGeneration
-
Gets if the list fo the best rules has been changed
- Change - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
This variable is used to keep track of change in the value of delta summation of r(i).
- ChangeDateFormat - weka.filters.unsupervised.attribute中的类
-
Changes the date format used by a date attribute.
- ChangeDateFormat() - 类的构造器 weka.filters.unsupervised.attribute.ChangeDateFormat
- changeLength(double) - 类中的方法 weka.core.AlgVector
-
Changes the length of a vector.
- changeUID(long, long, String, String) - 类中的静态方法 weka.core.xml.SerialUIDChanger
-
changes the oldUID into newUID from the given file (binary/KOML) into the other one (binary/KOML).
- CHAPTER - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
A chapter (or section or whatever) number.
- CharacterDelimitedTokenizer - weka.core.tokenizers中的类
-
Abstract superclass for tokenizers that take characters as delimiters.
- CharacterDelimitedTokenizer() - 类的构造器 weka.core.tokenizers.CharacterDelimitedTokenizer
- charSetTipText() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
the tip text for this property
- ChartEvent - weka.gui.beans中的类
-
Event encapsulating info for plotting a data point on the StripChart
- ChartEvent(Object) - 类的构造器 weka.gui.beans.ChartEvent
-
Creates a new
ChartEvent
instance. - ChartEvent(Object, Vector, double, double, double[], boolean) - 类的构造器 weka.gui.beans.ChartEvent
-
Creates a new
ChartEvent
instance. - ChartListener - weka.gui.beans中的接口
-
Interface to something that can process a ChartEvent
- ChebyshevDistance - weka.core中的类
-
Implements the Chebyshev distance.
- ChebyshevDistance() - 类的构造器 weka.core.ChebyshevDistance
-
Constructs an Chebyshev Distance object, Instances must be still set.
- ChebyshevDistance(Instances) - 类的构造器 weka.core.ChebyshevDistance
-
Constructs an Chebyshev Distance object and automatically initializes the ranges.
- check(double) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Checks if at least two bags contain a minimum number of instances.
- Check - weka.core中的类
-
Abstract general class for testing in Weka.
- Check() - 类的构造器 weka.core.Check
- CheckAssociator - weka.associations中的类
-
Class for examining the capabilities and finding problems with associators.
- CheckAssociator() - 类的构造器 weka.associations.CheckAssociator
- CheckAttributeSelection - weka.attributeSelection中的类
-
Class for examining the capabilities and finding problems with attribute selection schemes.
- CheckAttributeSelection() - 类的构造器 weka.attributeSelection.CheckAttributeSelection
- CheckBoxList - weka.gui中的类
-
An extended JList that contains CheckBoxes.
- CheckBoxList() - 类的构造器 weka.gui.CheckBoxList
-
initializes the list with an empty CheckBoxListModel
- CheckBoxList(CheckBoxList.CheckBoxListModel) - 类的构造器 weka.gui.CheckBoxList
-
initializes the list with the given CheckBoxListModel
- CheckBoxList.CheckBoxListModel - weka.gui中的类
-
A specialized model.
- CheckBoxList.CheckBoxListRenderer - weka.gui中的类
-
A specialized CellRenderer for the CheckBoxList
- CheckBoxListModel() - 类的构造器 weka.gui.CheckBoxList.CheckBoxListModel
-
initializes the model with no data.
- CheckBoxListModel(Object[]) - 类的构造器 weka.gui.CheckBoxList.CheckBoxListModel
-
Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.
- CheckBoxListModel(Vector) - 类的构造器 weka.gui.CheckBoxList.CheckBoxListModel
-
Constructs a CheckBoxListModel from a Vector and then applies setModel to it.
- CheckBoxListRenderer() - 类的构造器 weka.gui.CheckBoxList.CheckBoxListRenderer
- checkCanonicalUserOptions() - 类中的方法 weka.core.CheckOptionHandler
-
checks whether the user-supplied options stay the same after settting, getting and re-setting again
- CheckClassifier - weka.classifiers中的类
-
Class for examining the capabilities and finding problems with classifiers.
- CheckClassifier() - 类的构造器 weka.classifiers.CheckClassifier
- CheckClusterer - weka.clusterers中的类
-
Class for examining the capabilities and finding problems with clusterers.
- CheckClusterer() - 类的构造器 weka.clusterers.CheckClusterer
-
default constructor
- checkDefaultOptions() - 类中的方法 weka.core.CheckOptionHandler
-
checks whether the default options can be processed completely or some invalid options are returned by the getOptions() method.
- checkErrorRateTipText() - 类中的方法 weka.classifiers.rules.JRip
-
Returns the tip text for this property
- CheckEstimator - weka.estimators中的类
-
Class for examining the capabilities and finding problems with estimators.
- CheckEstimator() - 类的构造器 weka.estimators.CheckEstimator
- CheckEstimator.AttrTypes - weka.estimators中的类
-
class that contains info about the attribute types the estimator can estimate estimator work on one attribute only
- CheckEstimator.EstTypes - weka.estimators中的类
-
public class that contains info about the chosen attribute type estimator work on one attribute only
- CheckEstimator.PostProcessor - weka.estimators中的类
-
a class for postprocessing the test-data
- checkForAttributeType(int) - 类中的方法 weka.core.Instances
-
Checks for attributes of the given type in the dataset
- checkForMissing(Instance, Instances) - 类中的方法 weka.classifiers.functions.PaceRegression
-
Checks if an instance has a missing value.
- checkForNominalAttributes(Instances) - 类中的方法 weka.clusterers.XMeans
-
Checks for nominal attributes in the dataset.
- checkForRemainingOptions(String[]) - 类中的静态方法 weka.core.Utils
-
Checks if the given array contains any non-empty options.
- checkForStringAttributes() - 类中的方法 weka.core.Instances
-
Checks for string attributes in the dataset
- checkGlobalInfo() - 类中的方法 weka.core.CheckGOE
-
checks whether the object declares a globalInfo method.
- CheckGOE - weka.core中的类
-
Simple command line checking of classes that are editable in the GOE.
- CheckGOE() - 类的构造器 weka.core.CheckGOE
-
default constructor
- checkIndicesList(MiddleOutConstructor.MyIdxList, int, int) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Checks whether if the points in an index list are in some specified of the master index array.
- checkInstance(Instance) - 类中的方法 weka.core.Instances
-
Checks if the given instance is compatible with this dataset.
- CheckKernel - weka.classifiers.functions.supportVector中的类
-
Class for examining the capabilities and finding problems with kernels.
- CheckKernel() - 类的构造器 weka.classifiers.functions.supportVector.CheckKernel
- checkListOptions() - 类中的方法 weka.core.CheckOptionHandler
-
checks whether the listOptions method works
- checkModel() - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Checks if generated model is valid.
- checkModel(int) - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Checks if there are at least 2 subsets that contain >= minNumInstances.
- CheckOptionHandler - weka.core中的类
-
Simple command line checking of classes that implement OptionHandler.
- CheckOptionHandler() - 类的构造器 weka.core.CheckOptionHandler
- checkRemainingOptions() - 类中的方法 weka.core.CheckOptionHandler
-
checks whether the user-supplied options can be processed completely or some "left-over" options remain
- checkResettingOptions() - 类中的方法 weka.core.CheckOptionHandler
-
checks whether the optionhandler can be re-setted again to default options after the user-supplied options have been set.
- CheckScheme - weka.core中的类
-
Abstract general class for testing schemes in Weka.
- CheckScheme() - 类的构造器 weka.core.CheckScheme
- CheckScheme.PostProcessor - weka.core中的类
-
a class for postprocessing the test-data
- checkSetOptions() - 类中的方法 weka.core.CheckOptionHandler
-
checks whether the user-supplied options can be processed at all
- CheckSource - weka.classifiers中的类
-
A simple class for checking the source generated from Classifiers implementing the
weka.classifiers.Sourcable
interface. - CheckSource - weka.filters中的类
-
A simple class for checking the source generated from Filters implementing the
weka.filters.Sourcable
interface. - CheckSource() - 类的构造器 weka.classifiers.CheckSource
- CheckSource() - 类的构造器 weka.filters.CheckSource
- checkStatus(Object) - 接口中的方法 weka.experiment.Compute
-
Check on the status of a
Task
- checkStatus(Object) - 类中的方法 weka.experiment.RemoteEngine
-
Returns status information on a particular task
- checksTurnedOffTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- checksTurnedOffTipText() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns the tip text for this property
- checksTurnedOffTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- checksTurnedOffTipText() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns the tip text for this property
- checkToolTips() - 类中的方法 weka.core.CheckGOE
-
checks whether the object declares tip text method for all its properties.
- ChildFrameMDI(Main, String) - 类的构造器 weka.gui.Main.ChildFrameMDI
-
constructs a new internal frame that knows about its parent.
- ChildFrameSDI(GUIChooser, String) - 类的构造器 weka.gui.GUIChooser.ChildFrameSDI
-
constructs a new internal frame that knows about its parent.
- ChildFrameSDI(Main, String) - 类的构造器 weka.gui.Main.ChildFrameSDI
-
constructs a new internal frame that knows about its parent.
- children() - 类中的方法 weka.classifiers.trees.adtree.PredictionNode
-
Enumerates the children of this node.
- childrenValues() - 类中的方法 weka.gui.HierarchyPropertyParser
-
The value in the children nodes.
- chisqDistribution - 类中的静态变量 weka.core.matrix.Maths
-
Distribution type: chi-squared
- ChisqMixture - weka.classifiers.functions.pace中的类
-
Class for manipulating chi-square mixture distributions.
- ChisqMixture() - 类的构造器 weka.classifiers.functions.pace.ChisqMixture
-
Contructs an empty ChisqMixture
- chiSquared(double[][], boolean) - 类中的静态方法 weka.core.ContingencyTables
-
Returns chi-squared probability for a given matrix.
- ChiSquaredAttributeEval - weka.attributeSelection中的类
-
ChiSquaredAttributeEval :
Evaluates the worth of an attribute by computing the value of the chi-squared statistic with respect to the class. - ChiSquaredAttributeEval() - 类的构造器 weka.attributeSelection.ChiSquaredAttributeEval
-
Constructor
- chiSquaredProbability(double, double) - 类中的静态方法 weka.core.Statistics
-
Returns chi-squared probability for given value and degrees of freedom.
- chiVal(double[][], boolean) - 类中的静态方法 weka.core.ContingencyTables
-
Computes chi-squared statistic for a contingency table.
- chol() - 类中的方法 weka.core.matrix.Matrix
-
Cholesky Decomposition
- CholeskyDecomposition - weka.core.matrix中的类
-
Cholesky Decomposition.
- CholeskyDecomposition(Matrix) - 类的构造器 weka.core.matrix.CholeskyDecomposition
-
Cholesky algorithm for symmetric and positive definite matrix.
- chooseIndex() - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Method for choosing a subset to expand.
- chooseLastIndex() - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Choose last index (ie.
- CISearchAlgorithm - weka.classifiers.bayes.net.search.ci中的类
-
The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).
- CISearchAlgorithm() - 类的构造器 weka.classifiers.bayes.net.search.ci.CISearchAlgorithm
- CitationKNN - weka.classifiers.mi中的类
-
Modified version of the Citation kNN multi instance classifier.
For more information see:
Jun Wang, Zucker, Jean-Daniel: Solving Multiple-Instance Problem: A Lazy Learning Approach. - CitationKNN() - 类的构造器 weka.classifiers.mi.CitationKNN
- CLASS_IS_LAST - 类中的静态变量 weka.core.TestInstances
-
can be used for settting the class attribute index to last
- CLASS_PYTHONINERPRETER - 类中的静态变量 weka.core.Jython
-
the classname of the Python interpreter
- CLASS_PYTHONOBJECTINPUTSTREAM - 类中的静态变量 weka.core.Jython
-
the classname of the Python ObjectInputStream
- ClassAssigner - weka.filters.unsupervised.attribute中的类
-
Filter that can set and unset the class index.
- ClassAssigner - weka.gui.beans中的类
-
Bean that assigns a class attribute to a data set.
- ClassAssigner() - 类的构造器 weka.filters.unsupervised.attribute.ClassAssigner
- ClassAssigner() - 类的构造器 weka.gui.beans.ClassAssigner
- ClassAssignerBeanInfo - weka.gui.beans中的类
-
BeanInfo class for the class assigner bean
- ClassAssignerBeanInfo() - 类的构造器 weka.gui.beans.ClassAssignerBeanInfo
- ClassAssignerCustomizer - weka.gui.beans中的类
-
GUI customizer for the class assigner bean
- ClassAssignerCustomizer() - 类的构造器 weka.gui.beans.ClassAssignerCustomizer
- classAttribute() - 类中的方法 weka.core.Instance
-
Returns class attribute.
- classAttribute() - 类中的方法 weka.core.Instances
-
Returns the class attribute.
- classAttributeNames() - 类中的方法 weka.classifiers.functions.SMO
- classAttributeNames() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the names of the class attributes.
- ClassBalancedND - weka.classifiers.meta.nestedDichotomies中的类
-
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random class-balanced tree structure.
For more info, check
Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. - ClassBalancedND() - 类的构造器 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Constructor.
- classColumnTipText() - 类中的方法 weka.gui.beans.ClassAssigner
-
Tool tip text for this property
- ClassDiscovery - weka.core中的类
-
This class is used for discovering classes that implement a certain interface or a derived from a certain class.
- ClassDiscovery() - 类的构造器 weka.core.ClassDiscovery
- ClassDiscovery.StringCompare - weka.core中的类
-
compares two strings.
- classFirst(boolean) - 类中的方法 weka.experiment.Experiment
-
Sets whether the first attribute is treated as the class for all datasets involved in the experiment.
- classFlagTipText() - 类中的方法 weka.datagenerators.ClusterGenerator
-
Returns the tip text for this property
- ClassificationGenerator - weka.datagenerators中的类
-
Abstract class for data generators for classifiers.
- ClassificationGenerator() - 类的构造器 weka.datagenerators.ClassificationGenerator
-
initializes with default values
- classificationTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- ClassificationViaClustering - weka.classifiers.meta中的类
-
A simple meta-classifier that uses a clusterer for classification.
- ClassificationViaClustering() - 类的构造器 weka.classifiers.meta.ClassificationViaClustering
-
default constructor
- ClassificationViaRegression - weka.classifiers.meta中的类
-
Class for doing classification using regression methods.
- ClassificationViaRegression() - 类的构造器 weka.classifiers.meta.ClassificationViaRegression
-
Default constructor.
- Classifier - weka.classifiers中的类
-
Abstract classifier.
- Classifier - weka.gui.beans中的类
-
Bean that wraps around weka.classifiers
- Classifier() - 类的构造器 weka.classifiers.Classifier
- Classifier() - 类的构造器 weka.gui.beans.Classifier
-
Creates a new
Classifier
instance. - ClassifierBeanInfo - weka.gui.beans中的类
-
BeanInfo class for the Classifier wrapper bean
- ClassifierBeanInfo() - 类的构造器 weka.gui.beans.ClassifierBeanInfo
- ClassifierCustomizer - weka.gui.beans中的类
-
GUI customizer for the classifier wrapper bean
- ClassifierCustomizer() - 类的构造器 weka.gui.beans.ClassifierCustomizer
- ClassifierDecList - weka.classifiers.rules.part中的类
-
Class for handling a rule (partial tree) for a decision list.
- ClassifierDecList(ModelSelection, int) - 类的构造器 weka.classifiers.rules.part.ClassifierDecList
-
Constructor - just calls constructor of class DecList.
- ClassifierPanel - weka.gui.explorer中的类
-
0* This panel allows the user to select and configure a classifier, set the attribute of the current dataset to be used as the class, and evaluate the classifier using a number of testing modes (test on the training data, train/test on a percentage split, n-fold cross-validation, test on a separate split).
- ClassifierPanel() - 类的构造器 weka.gui.explorer.ClassifierPanel
-
Creates the classifier panel
- ClassifierPerformanceEvaluator - weka.gui.beans中的类
-
A bean that evaluates the performance of batch trained classifiers
- ClassifierPerformanceEvaluator() - 类的构造器 weka.gui.beans.ClassifierPerformanceEvaluator
- ClassifierPerformanceEvaluatorBeanInfo - weka.gui.beans中的类
-
Bean info class for the classifier performance evaluator
- ClassifierPerformanceEvaluatorBeanInfo() - 类的构造器 weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
- classifiers() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the array of classifiers that have been built.
- ClassifierSplitEvaluator - weka.experiment中的类
-
A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.
- ClassifierSplitEvaluator() - 类的构造器 weka.experiment.ClassifierSplitEvaluator
-
No args constructor.
- ClassifierSplitModel - weka.classifiers.trees.j48中的类
-
Abstract class for classification models that can be used recursively to split the data.
- ClassifierSplitModel() - 类的构造器 weka.classifiers.trees.j48.ClassifierSplitModel
- classifiersTipText() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Returns the tip text for this property
- classifiersTipText() - 类中的方法 weka.classifiers.MultipleClassifiersCombiner
-
Returns the tip text for this property
- ClassifierSubsetEval - weka.attributeSelection中的类
-
Classifier subset evaluator:
Evaluates attribute subsets on training data or a seperate hold out testing set. - ClassifierSubsetEval() - 类的构造器 weka.attributeSelection.ClassifierSubsetEval
- classifierTipText() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Returns the tip text for this property
- classifierTipText() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns the tip text for this property
- classifierTipText() - 类中的方法 weka.classifiers.SingleClassifierEnhancer
-
Returns the tip text for this property
- classifierTipText() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Returns the tip text for this property
- classifierTipText() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Returns the tip text for this property
- classifierTipText() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns the tip text for this property.
- classifierTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns the tip text for this property
- ClassifierTree - weka.classifiers.trees.j48中的类
-
Class for handling a tree structure used for classification.
- ClassifierTree(ModelSelection) - 类的构造器 weka.classifiers.trees.j48.ClassifierTree
-
Constructor.
- CLASSIFY_CHILD - 类中的静态变量 weka.gui.treevisualizer.TreeDisplayEvent
-
Asks for another learning scheme to classify this node.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Classifies the given instance using the Bayesian Logistic Regression function.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Classifies a given instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.Classifier
-
Classifies the given test instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Classifies a given instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.IsotonicRegression
-
Generate a prediction for the supplied instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Classify a given instance using the best generated LinearRegression Classifier.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.LinearRegression
-
Classifies the given instance using the linear regression function.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.PaceRegression
-
Classifies the given instance using the linear regression function.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Classifies the given test instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Generate a prediction for the supplied instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.SMOreg
-
Classifies the given instance using the linear regression function.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.functions.Winnow
-
Outputs the prediction for the given instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.lazy.IB1
-
Classifies the given test instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Classify an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Classifies the given test instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns a predicted class for the test instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.meta.Vote
-
Classifies the given test instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.mi.MINND
-
Use Kullback Leibler distance to find the nearest neighbours of the given exemplar.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.rules.NNge
-
Classifies a given instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.rules.OneR
-
Classifies a given instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Classifies an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.rules.PART
-
Classifies an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.rules.part.MakeDecList
-
Classifies an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.rules.Prism
-
Classifies a given instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.rules.Ridor
-
Classify the test instance with the rule learner
- classifyInstance(Instance) - 类中的方法 weka.classifiers.rules.ZeroR
-
Classifies a given instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.FT
-
Classifies an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.Id3
-
Classifies a given test instance using the decision tree.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Classifies a given instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Classifies an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.J48
-
Classifies an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.J48graft
-
Classifies an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.LMT
-
Classifies an instance.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Calculates a prediction for an instance using a set of rules or an M5 model tree
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.m5.PreConstructedLinearModel
-
Predicts the class of the supplied instance using the linear model.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.m5.Rule
-
Calculates a prediction for an instance using this rule or M5 model tree
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Classify an instance using this node.
- classifyInstance(Instance) - 类中的方法 weka.classifiers.trees.NBTree
-
Classifies an instance.
- classIndex() - 类中的方法 weka.core.Instance
-
Returns the class attribute's index.
- classIndex() - 类中的方法 weka.core.Instances
-
Returns the class attribute's index.
- ClassIndex - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
The class index from the training data
- classIndexTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- classIndexTipText() - 类中的方法 weka.associations.FilteredAssociator
-
Returns the tip text for this property
- classIndexTipText() - 类中的方法 weka.associations.PredictiveApriori
-
Returns the tip text for this property
- classIndexTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- classIndexTipText() - 类中的方法 weka.core.converters.LibSVMSaver
-
Returns the tip text for this property
- classIndexTipText() - 类中的方法 weka.core.converters.SVMLightSaver
-
Returns the tip text for this property.
- classIndexTipText() - 类中的方法 weka.core.converters.XRFFSaver
-
Returns the tip text for this property
- classIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
Returns the tip text for this property.
- classIndexTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns the tip text for this property
- classIsMissing() - 类中的方法 weka.core.Instance
-
Tests if an instance's class is missing.
- ClassloaderUtil - weka.core中的类
-
Utility class that can add jar files to the classpath dynamically.
- ClassloaderUtil() - 类的构造器 weka.core.ClassloaderUtil
- className(int) - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Gets the name of one of the classes.
- classNameTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Returns the tip text for this property
- ClassOrder - weka.filters.supervised.attribute中的类
-
Changes the order of the classes so that the class values are no longer of in the order specified in the header.
- ClassOrder() - 类的构造器 weka.filters.supervised.attribute.ClassOrder
- classOrderTipText() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Returns the tip text for this property
- ClassPanel - weka.gui.visualize中的类
-
This panel displays coloured labels for nominal attributes and a spectrum for numeric attributes.
- ClassPanel() - 类的构造器 weka.gui.visualize.ClassPanel
- ClassPanel(Color) - 类的构造器 weka.gui.visualize.ClassPanel
- classProb(int, Instance, int) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Gets class probability for instance.
- classProb(int, Instance, int) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Gets class probability for instance.
- classProb(int, Instance, int) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Gets class probability for instance.
- classProb(int, Instance, int) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
returns the probability for instance for the specified class
- classProb(int, Instance, int) - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Return the probability for a class value
- classProb(int, Instance, int) - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Return the probability for a class value
- classProbLaplace(int, Instance, int) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Gets class probability for instance.
- classSgn(double) - 类中的静态方法 weka.classifiers.bayes.BayesianLogisticRegression
-
This class is used to mask the internal class labels.
- classValue() - 类中的方法 weka.core.Instance
-
Returns an instance's class value in internal format.
- ClassValuePicker - weka.gui.beans中的类
- ClassValuePicker() - 类的构造器 weka.gui.beans.ClassValuePicker
- ClassValuePickerBeanInfo - weka.gui.beans中的类
-
BeanInfo class for the class value picker bean
- ClassValuePickerBeanInfo() - 类的构造器 weka.gui.beans.ClassValuePickerBeanInfo
- ClassValuePickerCustomizer - weka.gui.beans中的类
- ClassValuePickerCustomizer() - 类的构造器 weka.gui.beans.ClassValuePickerCustomizer
- classValueTipText() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns the tip text for this property.
- clean() - 类中的方法 weka.attributeSelection.ASEvaluation
-
Tells the evaluator that the attribute selection process is complete.
- clean() - 类中的方法 weka.attributeSelection.CfsSubsetEval
- clean() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval
- clean() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
- clean() - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Frees the cache used by the kernel.
- clean() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Frees the memory used by the kernel.
- clean() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Frees the cache used by the kernel.
- clean() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Frees the memory used by the kernel.
- clean() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Frees the memory used by the kernel.
- clean() - 类中的方法 weka.classifiers.mi.supportVector.MIPolyKernel
-
Frees the cache used by the kernel.
- clean() - 接口中的方法 weka.core.DistanceFunction
-
Free any references to training instances
- clean() - 类中的方法 weka.core.NormalizableDistance
-
Free any references to training instances
- cleanse(Instance) - 类中的方法 weka.classifiers.mi.MINND
-
Cleanse the given exemplar according to the valid and noise data statistics
- cleanup() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Cleanup in order to save memory.
- cleanup() - 类中的方法 weka.classifiers.trees.j48.BinC45ModelSelection
-
Sets reference to training data to null.
- cleanup() - 类中的方法 weka.classifiers.trees.j48.C45ModelSelection
-
Sets reference to training data to null.
- cleanup() - 类中的方法 weka.classifiers.trees.j48.NBTreeModelSelection
-
Sets reference to training data to null.
- cleanup() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Cleanup in order to save memory.
- cleanup() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Cleanup in order to save memory.
- cleanup() - 类中的方法 weka.classifiers.trees.lmt.ResidualModelSelection
-
Method not in use
- cleanup(Instances) - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Cleanup in order to save memory.
- cleanup(Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Cleanup in order to save memory.
- cleanUp() - 类中的方法 weka.classifiers.rules.RuleStats
-
Frees up memory after classifier has been built.
- clear() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- clear() - 类中的方法 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Clears this hashtable so that it contains no keys.
- clear() - 类中的方法 weka.classifiers.xml.XMLClassifier
-
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
- clear() - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Removes all the elements from the stack.
- clear() - 类中的方法 weka.core.ProtectedProperties
-
Overrides a method to prevent the properties from being modified.
- clear() - 类中的方法 weka.core.Stopwords
-
removes all stopwords
- clear() - 类中的方法 weka.core.Tee
-
removes all streams and places the default printstream, if any, again in the list.
- clear() - 类中的方法 weka.core.Trie
-
Removes all of the elements from this collection
- clear() - 类中的方法 weka.core.xml.MethodHandler
-
removes all mappings
- clear() - 类中的方法 weka.core.xml.XMLBasicSerialization
-
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
- clear() - 类中的方法 weka.core.xml.XMLDocument
-
sets up an empty DOM document, with the current DOCTYPE and root node.
- clear() - 类中的方法 weka.core.xml.XMLSerialization
-
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
- clear() - 类中的方法 weka.core.xml.XMLSerializationMethodHandler
-
removes all current methods and adds the methods according to the
- clear() - 类中的方法 weka.experiment.ResultMatrix
-
removes the stored data and the ordering, but retains the dimensions of the matrix
- clear() - 类中的方法 weka.experiment.ResultMatrixCSV
-
removes the stored data but retains the dimensions of the matrix
- clear() - 类中的方法 weka.experiment.ResultMatrixGnuPlot
-
removes the stored data but retains the dimensions of the matrix
- clear() - 类中的方法 weka.experiment.ResultMatrixHTML
-
removes the stored data but retains the dimensions of the matrix
- clear() - 类中的方法 weka.experiment.ResultMatrixLatex
-
removes the stored data but retains the dimensions of the matrix
- clear() - 类中的方法 weka.experiment.ResultMatrixPlainText
-
removes the stored data but retains the dimensions of the matrix
- clear() - 类中的方法 weka.experiment.ResultMatrixSignificance
-
removes the stored data but retains the dimensions of the matrix
- clear() - 类中的方法 weka.experiment.xml.XMLExperiment
-
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
- clear() - 类中的方法 weka.gui.beans.xml.XMLBeans
-
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
- clear() - 类中的方法 weka.gui.LogWindow
-
clears the output
- clear() - 类中的方法 weka.gui.sql.ConnectionPanel
-
sets the parameters back to standard.
- clear() - 类中的方法 weka.gui.sql.InfoPanel
-
clears the content of the panel
- clear() - 类中的方法 weka.gui.sql.QueryPanel
-
clears the textarea.
- clear() - 类中的方法 weka.gui.sql.ResultPanel
-
sets the parameters back to standard
- clear() - 类中的方法 weka.gui.sql.SqlViewer
-
calls the clear method of all sub-panels to set back to default values and free up memory.
- clearCache() - 类中的静态方法 weka.core.ClassDiscovery
-
clears the cache for class/classnames relation.
- clearHeader() - 类中的方法 weka.experiment.ResultMatrix
-
removes all the header information
- clearLayout() - 类中的方法 weka.gui.beans.KnowledgeFlowApp
- clearRanking() - 类中的方法 weka.experiment.ResultMatrix
-
clears the currently stored ranking data
- clearRect(int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw a filled rectangle with the background color.
- clearResults() - 类中的方法 weka.gui.ResultHistoryPanel
-
Removes all of the result buffers from the history.
- clearSearch() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
clears the search, i.e.
- clearSearch() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
clears the search, i.e.
- clearStatus() - 类中的方法 weka.gui.beans.LogPanel
-
Clear the status area.
- clearSummary() - 类中的方法 weka.experiment.ResultMatrix
-
clears the current summary data
- clearUndo() - 接口中的方法 weka.core.Undoable
-
removes the undo history
- clearUndo() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
removes the undo history
- clearUndo() - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
removes the undo history
- clearUndo() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
removes the undo history
- clearUndoStack() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
remove all actions from the undo stack
- clip(Shape) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- clipRect(int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- Clock() - 类的构造器 weka.core.Debug.Clock
-
automatically starts the clock with FORMAT_SECONDS format and CPU time if available
- Clock(boolean) - 类的构造器 weka.core.Debug.Clock
-
starts the clock depending on
start
immediately with the FORMAT_SECONDS output format and CPU time if available - Clock(boolean, int) - 类的构造器 weka.core.Debug.Clock
-
starts the clock depending on
start
immediately, using CPU time if available - Clock(int) - 类的构造器 weka.core.Debug.Clock
-
automatically starts the clock with the given output format and CPU time if available
- clone() - 类中的方法 weka.associations.gsp.Element
-
Returns a deep clone of an Element.
- clone() - 类中的方法 weka.associations.gsp.Sequence
-
Returns a deep clone of a Sequence.
- clone() - 类中的方法 weka.associations.tertius.LiteralSet
-
Returns a shallow copy of this set.
- clone() - 类中的方法 weka.associations.tertius.Rule
-
Returns a shallow copy of this rule.
- clone() - 类中的方法 weka.attributeSelection.ScatterSearchV1.Subset
- clone() - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Creates and returns a clone of this object.
- clone() - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Clones the discrete function
- clone() - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Clone the PaceMatrix object.
- clone() - 接口中的方法 weka.classifiers.IterativeClassifier
-
Performs a deep copy of the classifier, and a reference copy of the training instances (or a deep copy if required).
- clone() - 类中的方法 weka.classifiers.trees.ADTree
-
Creates a clone that is identical to the current tree, but is independent.
- clone() - 类中的方法 weka.classifiers.trees.adtree.PredictionNode
-
Clones this node.
- clone() - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Clones this node.
- clone() - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Clones this node.
- clone() - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Clones this node.
- clone() - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Allows to clone a model (shallow copy).
- clone() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Clones distribution (Deep copy of distribution).
- clone() - 类中的方法 weka.core.AlgVector
-
Creates and returns a clone of this object.
- clone() - 类中的方法 weka.core.Capabilities
-
Creates and returns a copy of this object.
- clone() - 类中的方法 weka.core.Matrix
-
已过时。Creates and returns a clone of this object.
- clone() - 类中的方法 weka.core.matrix.DoubleVector
-
Clones the DoubleVector object.
- clone() - 类中的方法 weka.core.matrix.IntVector
-
Clones the IntVector object.
- clone() - 类中的方法 weka.core.matrix.Matrix
-
Clone the Matrix object.
- clone() - 类中的方法 weka.core.PropertyPath.PathElement
-
returns a clone of the current object
- clone() - 类中的方法 weka.core.TestInstances
-
creates a clone of the current object
- clone() - 类中的方法 weka.core.Trie
-
returns a deep copy of itself
- clone() - 类中的方法 weka.core.Trie.TrieNode
-
creates a deep copy of itself
- clone(Estimator) - 类中的静态方法 weka.estimators.Estimator
-
Creates a deep copy of the given estimator using serialization.
- CLOPE - weka.clusterers中的类
-
Yiling Yang, Xudong Guan, Jinyuan You: CLOPE: a fast and effective clustering algorithm for transactional data.
- CLOPE() - 类的构造器 weka.clusterers.CLOPE
-
the default constructor
- close() - 类中的方法 weka.experiment.DatabaseUtils
-
closes the m_PreparedStatement to avoid memory leaks.
- close() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
closes the window, i.e., if the parent is not null and implements the WindowListener interface it calls the windowClosing method
- close() - 类中的方法 weka.gui.LogWindow
-
closes the frame
- close(ResultSet) - 类中的方法 weka.experiment.DatabaseUtils
-
closes the ResultSet and the statement that generated the ResultSet to avoid memory leaks in JDBC drivers - in contrast to the JDBC specs, a lot of JDBC drives don't clean up correctly.
- closeAllFiles() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
closes all open files
- CLOSEDCLOSED - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Interval.Closure
- CLOSEDOPEN - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Interval.Closure
- closeFile() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
closes the current tab
- closeFile(boolean) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
closes the current tab
- closeFrame() - 类中的方法 weka.gui.SetInstancesPanel
-
closes the frame, i.e., the visibility is set to false
- closestPoint(Instance, Instances, int[]) - 类中的方法 weka.core.EuclideanDistance
-
Returns the index of the closest point to the current instance.
- closeToDefaultTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- closeToTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- closeToToleranceTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- ClusterDefinition - weka.datagenerators中的类
-
Ancestor to all ClusterDefinitions, i.e., subclasses that handle their own parameters that the cluster generator only passes on.
- ClusterDefinition() - 类的构造器 weka.datagenerators.ClusterDefinition
-
initializes the cluster, without a parent cluster (necessary for GOE)
- ClusterDefinition(ClusterGenerator) - 类的构造器 weka.datagenerators.ClusterDefinition
-
initializes the cluster
- clusterDefinitionsTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Returns the tip text for this property
- Clusterer - weka.gui.beans中的类
-
Bean that wraps around weka.clusterers
- Clusterer - weka.clusterers中的接口
-
Interface for clusterers.
- Clusterer() - 类的构造器 weka.gui.beans.Clusterer
-
Creates a new
Clusterer
instance. - ClustererBeanInfo - weka.gui.beans中的类
-
BeanInfo class for the Clusterer wrapper bean
- ClustererBeanInfo() - 类的构造器 weka.gui.beans.ClustererBeanInfo
- ClustererCustomizer - weka.gui.beans中的类
-
GUI customizer for the Clusterer wrapper bean
- ClustererCustomizer() - 类的构造器 weka.gui.beans.ClustererCustomizer
- ClustererPanel - weka.gui.explorer中的类
-
This panel allows the user to select and configure a clusterer, and evaluate the clusterer using a number of testing modes (test on the training data, train/test on a percentage split, test on a separate split).
- ClustererPanel() - 类的构造器 weka.gui.explorer.ClustererPanel
-
Creates the clusterer panel
- ClustererPerformanceEvaluator - weka.gui.beans中的类
-
A bean that evaluates the performance of batch trained clusterers
- ClustererPerformanceEvaluator() - 类的构造器 weka.gui.beans.ClustererPerformanceEvaluator
- ClustererPerformanceEvaluatorBeanInfo - weka.gui.beans中的类
-
Bean info class for the clusterer performance evaluator
- ClustererPerformanceEvaluatorBeanInfo() - 类的构造器 weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
- clustererTipText() - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Returns the tip text for this property
- clustererTipText() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns the tip text for this property
- clustererTipText() - 类中的方法 weka.clusterers.SingleClustererEnhancer
-
Returns the tip text for this property
- clustererTipText() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Returns the tip text for this property
- clustererTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Returns the tip text for this property
- ClusterEvaluation - weka.clusterers中的类
-
Class for evaluating clustering models.
- ClusterEvaluation() - 类的构造器 weka.clusterers.ClusterEvaluation
-
Constructor.
- ClusterGenerator - weka.datagenerators中的类
-
Abstract class for cluster data generators.
- ClusterGenerator() - 类的构造器 weka.datagenerators.ClusterGenerator
-
initializes the generator
- clusteringSeedTipText() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns the tip text for this property
- clusterInstance(Instance) - 类中的方法 weka.clusterers.AbstractClusterer
-
Classifies a given instance.
- clusterInstance(Instance) - 类中的方法 weka.clusterers.CLOPE
-
Classifies a given instance.
- clusterInstance(Instance) - 接口中的方法 weka.clusterers.Clusterer
-
Classifies a given instance.
- clusterInstance(Instance) - 类中的方法 weka.clusterers.Cobweb
-
Classifies a given instance.
- clusterInstance(Instance) - 类中的方法 weka.clusterers.DBSCAN
-
Classifies a given instance.
- clusterInstance(Instance) - 类中的方法 weka.clusterers.FarthestFirst
-
Classifies a given instance.
- clusterInstance(Instance) - 类中的方法 weka.clusterers.HierarchicalClusterer
- clusterInstance(Instance) - 类中的方法 weka.clusterers.OPTICS
-
Classifies a given instance.
- clusterInstance(Instance) - 类中的方法 weka.clusterers.sIB
-
Cluster a given instance, this is the method defined in Clusterer interface do nothing but just return the cluster assigned to it
- clusterInstance(Instance) - 类中的方法 weka.clusterers.SimpleKMeans
-
Classifies a given instance.
- clusterInstance(Instance) - 类中的方法 weka.clusterers.XMeans
-
Classifies a given instance.
- ClusterMembership - weka.filters.unsupervised.attribute中的类
-
A filter that uses a density-based clusterer to generate cluster membership values; filtered instances are composed of these values plus the class attribute (if set in the input data).
- ClusterMembership() - 类的构造器 weka.filters.unsupervised.attribute.ClusterMembership
- clusterPriors() - 类中的方法 weka.clusterers.AbstractDensityBasedClusterer
-
Returns the prior probability of each cluster.
- clusterPriors() - 接口中的方法 weka.clusterers.DensityBasedClusterer
-
Returns the prior probability of each cluster.
- clusterPriors() - 类中的方法 weka.clusterers.EM
-
Returns the cluster priors.
- clusterPriors() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns the cluster priors.
- clusterResultsToString() - 类中的方法 weka.clusterers.ClusterEvaluation
-
return the results of clustering.
- clusters - 类中的变量 weka.clusterers.CLOPE
-
Array of clusters
- clusterSubTypeTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns the tip text for this property
- clusterTypeTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns the tip text for this property
- Cobweb - weka.clusterers中的类
-
Class implementing the Cobweb and Classit clustering algorithms.
Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers. - Cobweb() - 类的构造器 weka.clusterers.Cobweb
-
default constructor
- cochransCriterion(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Tests if Cochran's criterion is fullfilled for the given contingency table.
- codingCost() - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns coding cost for split (used in rule learner).
- codingCost() - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Returns coding costs of model.
- coef0TipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- coefficients() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns the coefficients for this linear model.
- coefficients() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns the coefficients for this logistic model.
- coefficients() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns the coefficients for this linear model.
- coefficients() - 类中的方法 weka.classifiers.trees.m5.PreConstructedLinearModel
-
Return the array of coefficients
- collapse() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTree
-
Collapses a tree to a node if training error doesn't increase.
- collapse() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Collapses a tree to a node if training error doesn't increase.
- COLOR_STDERR - 类中的静态变量 weka.gui.LogWindow
-
the Color of the style for stderr
- COLOR_STDOUT - 类中的静态变量 weka.gui.LogWindow
-
the color of the style for stdout
- Colors - weka.gui.treevisualizer中的类
-
This class maintains a list that contains all the colornames from the dotty standard and what color (in RGB) they represent
- Colors() - 类的构造器 weka.gui.treevisualizer.Colors
- columnResponseExplanation(PaceMatrix, IntVector, int, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns the squared ks-th response value if the j-th column becomes the ks-th after orthogonal transformation.
- combinationRuleTipText() - 类中的方法 weka.classifiers.meta.Vote
-
Returns the tip text for this property
- combinations(int, int) - 类中的静态方法 weka.classifiers.functions.LeastMedSq
-
Produces the combination nCr
- combinationTipText() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns the tip text for this property
- combinedDL(double, double) - 类中的方法 weka.classifiers.rules.RuleStats
-
Compute the combined DL of the ruleset in this class, i.e.
- CombineParents() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Combine all the posible pair solutions existing in the Population
- combSort11(double[], int[]) - 类中的静态方法 weka.core.neighboursearch.NearestNeighbourSearch
-
sorts the two given arrays.
- COMMA - 接口中的静态变量 weka.core.mathematicalexpression.sym
- COMMA - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- CommandlineCompletion() - 类的构造器 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
default constructor.
- compactify() - 类中的方法 weka.core.Instances
-
Compactifies the set of instances.
- compare(Object, Object) - 类中的方法 weka.core.ClassDiscovery.StringCompare
-
Compares its two arguments for order.
- compare(Object, Object) - 类中的方法 weka.core.InstanceComparator
-
compares the two instances, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
- compareTo(Object) - 类中的方法 weka.associations.RuleItem
-
compares two RuleItems and allows an ordering concerning expected predictive accuracy and time of generation Note: this class has a natural ordering that is inconsistent with equals
- compareTo(Object) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
method needed for sorting a collection of GraftSplits by laplace value
- compareTo(Object) - 类中的方法 weka.core.Version
-
checks the version of this class against the given version-string
- compareTo(FPGrowth.AssociationRule) - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Compare this rule to the supplied rule.
- compareTo(FPGrowth.BinaryItem) - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
Ensures that items will be sorted in descending order of frequency.
- compareTo(AttributeLocator) - 类中的方法 weka.core.AttributeLocator
-
Compares this object with the specified object for order.
- compareTo(SortedTableModel.SortContainer) - 类中的方法 weka.gui.SortedTableModel.SortContainer
-
Compares this object with the specified object for order.
- comparisonString(int, Instances) - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Gets the string describing the comparision the split depends on for a particular branch.
- comparisonString(int, Instances) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Gets the string describing the comparision the split depends on for a particular branch.
- comparisonString(int, Instances) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Gets the string describing the comparision the split depends on for a particular branch.
- ComplementNaiveBayes - weka.classifiers.bayes中的类
-
Class for building and using a Complement class Naive Bayes classifier.
For more information see,
Jason D. - ComplementNaiveBayes() - 类的构造器 weka.classifiers.bayes.ComplementNaiveBayes
- complexityParameterTipText() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns a tip text for this property suitable for display in the GUI
- ComponentHelper - weka.gui中的类
-
A helper class for some common tasks with Dialogs, Icons, etc.
- ComponentHelper() - 类的构造器 weka.gui.ComponentHelper
- componentHidden(ComponentEvent) - 类中的方法 weka.gui.hierarchyvisualizer.HierarchyVisualizer
- componentMoved(ComponentEvent) - 类中的方法 weka.gui.hierarchyvisualizer.HierarchyVisualizer
- componentResized(ComponentEvent) - 类中的方法 weka.gui.hierarchyvisualizer.HierarchyVisualizer
- componentShown(ComponentEvent) - 类中的方法 weka.gui.hierarchyvisualizer.HierarchyVisualizer
- compressOutputTipText() - 类中的方法 weka.core.converters.ArffSaver
-
Returns the tip text for this property
- compressOutputTipText() - 类中的方法 weka.core.converters.XRFFSaver
-
Returns the tip text for this property
- Compute - weka.experiment中的接口
-
Interface to something that can accept remote connections and execute a task.
- computelogLikelihood(double[], Instances) - 类中的方法 weka.classifiers.bayes.blr.Prior
-
Function computes the log-likelihood value: -sum{1 to n}{ln(1+exp(-Beta*x(i)*y(i))}
- computeLoglikelihood(double[], Instances) - 类中的方法 weka.classifiers.bayes.blr.GaussianPriorImpl
-
This method calls the log-likelihood implemented in the Prior abstract class.
- computeLogLikelihood(double[], Instances) - 类中的方法 weka.classifiers.bayes.blr.LaplacePriorImpl
-
Computes the log-likelihood values using the implementation in the Prior class.
- computeMinMaxAtts() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set up the bounds of our graphic based by finding the smallest reasonable area in the instance space to surround our data points.
- computePenalty(double[], double[]) - 类中的方法 weka.classifiers.bayes.blr.GaussianPriorImpl
-
This function computes the penalty term specific to Gaussian distribution.
- computePenalty(double[], double[]) - 类中的方法 weka.classifiers.bayes.blr.LaplacePriorImpl
-
This function computes the penalty term specific to Laplacian distribution.
- computePenalty(double[], double[]) - 类中的方法 weka.classifiers.bayes.blr.Prior
-
Skeleton function to compute penalty terms.
- cond() - 类中的方法 weka.core.matrix.Matrix
-
Matrix condition (2 norm)
- cond() - 类中的方法 weka.core.matrix.SingularValueDecomposition
-
Two norm condition number
- ConditionalEstimator - weka.estimators中的接口
-
Interface for conditional probability estimators.
- CONFERENCE - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
The same as inproceedings.
- CONFIDENCE - enum class 中的枚举常量 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
- confidenceFactorTipText() - 类中的方法 weka.classifiers.rules.PART
-
Returns the tip text for this property
- confidenceFactorTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- confidenceFactorTipText() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the tip text for this property
- confidenceForRule(AprioriItemSet, AprioriItemSet) - 类中的静态方法 weka.associations.AprioriItemSet
-
Outputs the confidence for a rule.
- CONFIG - 类中的静态变量 weka.core.Debug
-
the log level Vonfig
- confirmationComparator - 类中的静态变量 weka.associations.tertius.Rule
-
Comparator used to compare two rules according to their confirmation value.
- confirmationThenObservedComparator - 类中的静态变量 weka.associations.tertius.Rule
-
Comparator used to compare two rules according to their confirmation and then their observed number of counter-instances.
- confirmationThresholdTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- confirmationValuesTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- confusionMatrix() - 类中的方法 weka.classifiers.Evaluation
-
Returns a copy of the confusion matrix.
- ConfusionMatrix - weka.classifiers.evaluation中的类
-
Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.
- ConfusionMatrix(String[]) - 类的构造器 weka.classifiers.evaluation.ConfusionMatrix
-
Creates the confusion matrix with the given class names.
- ConjunctiveRule - weka.classifiers.rules中的类
-
This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels.
A rule consists of antecedents "AND"ed together and the consequent (class value) for the classification/regression. - ConjunctiveRule() - 类的构造器 weka.classifiers.rules.ConjunctiveRule
- connect(NeuralConnection, NeuralConnection) - 类中的静态方法 weka.classifiers.functions.neural.NeuralConnection
-
Connects two units together.
- CONNECT - 类中的静态变量 weka.gui.sql.event.ConnectionEvent
-
it was a connect try
- CONNECTED - 类中的静态变量 weka.classifiers.functions.neural.NeuralConnection
-
This flag is set once the unit has a connection.
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.Associator
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 接口中的方法 weka.gui.beans.BeanCommon
-
Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.ClassAssigner
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.Classifier
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.ClassValuePicker
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.Clusterer
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.Filter
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.Loader
-
Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor.
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.MetaBean
-
Returns true if, at this time, the object will accept a connection with respect to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.PredictionAppender
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor.
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.StripChart
-
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
- connectionAllowed(EventSetDescriptor) - 类中的方法 weka.gui.beans.TextViewer
-
Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
- connectionAllowed(String) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Returns true if, at this time, the object will accept a connection according to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Returns true if, at this time, the object will accept a connection according to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Returns true if, at this time, the object will accept a connection according to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Returns true if, at this time, the object will accept a connection according to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Returns true if, at this time, the object will accept a connection according to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.Associator
-
Returns true if, at this time, the object will accept a connection with respect to the named event
- connectionAllowed(String) - 接口中的方法 weka.gui.beans.BeanCommon
-
Returns true if, at this time, the object will accept a connection via the named event
- connectionAllowed(String) - 类中的方法 weka.gui.beans.ClassAssigner
-
Returns true if, at this time, the object will accept a connection according to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.Classifier
-
Returns true if, at this time, the object will accept a connection with respect to the named event
- connectionAllowed(String) - 类中的方法 weka.gui.beans.ClassValuePicker
-
Returns true if, at this time, the object will accept a connection according to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.Clusterer
-
Returns true if, at this time, the object will accept a connection with respect to the named event
- connectionAllowed(String) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Returns true if, at this time, the object will accept a connection via the named event
- connectionAllowed(String) - 类中的方法 weka.gui.beans.Filter
-
Returns true if, at this time, the object will accept a connection with respect to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Returns true if, at this time, the object will accept a connection with respect to the named event
- connectionAllowed(String) - 类中的方法 weka.gui.beans.Loader
-
Returns true if, at this time, the object will accept a connection via the named event
- connectionAllowed(String) - 类中的方法 weka.gui.beans.MetaBean
- connectionAllowed(String) - 类中的方法 weka.gui.beans.PredictionAppender
-
Returns true if, at this time, the object will accept a connection according to the supplied event name
- connectionAllowed(String) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Returns true if, at this time, the object will accept a connection according to the supplied event name.
- connectionAllowed(String) - 类中的方法 weka.gui.beans.StripChart
-
Returns true if, at this time, the object will accept a connection via the named event
- connectionAllowed(String) - 类中的方法 weka.gui.beans.TextViewer
-
Returns true if, at this time, the object will accept a connection via the named event
- connectionChange(ConnectionEvent) - 接口中的方法 weka.gui.sql.event.ConnectionListener
-
This method gets called when the connection is either established or disconnected.
- connectionChange(ConnectionEvent) - 类中的方法 weka.gui.sql.QueryPanel
-
This method gets called when the connection is either established or disconnected.
- connectionChange(ConnectionEvent) - 类中的方法 weka.gui.sql.SqlViewer
-
This method gets called when the connection is either established or disconnected.
- ConnectionEvent - weka.gui.sql.event中的类
-
An event that is generated when a connection is established or dropped.
- ConnectionEvent(Object, int, DbUtils) - 类的构造器 weka.gui.sql.event.ConnectionEvent
-
constructs the event
- ConnectionEvent(Object, int, DbUtils, Exception) - 类的构造器 weka.gui.sql.event.ConnectionEvent
-
constructs the event
- ConnectionListener - weka.gui.sql.event中的接口
-
A listener for connect/disconnect events.
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.Associator
-
Notify this object that it has been registered as a listener with a source with respect to the named event
- connectionNotification(String, Object) - 接口中的方法 weka.gui.beans.BeanCommon
-
Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.ClassAssigner
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.Classifier
-
Notify this object that it has been registered as a listener with a source with respect to the named event
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.ClassValuePicker
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.Clusterer
-
Notify this object that it has been registered as a listener with a source with respect to the named event
- connectionNotification(String, Object) - 接口中的方法 weka.gui.beans.ConnectionNotificationConsumer
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.Filter
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Notify this object that it has been registered as a listener with a source with respect to the named event
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.Loader
-
Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.MetaBean
-
Notify this object that it has been registered as a listener with a source with respect to the named event.
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.PredictionAppender
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.StripChart
-
Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
- connectionNotification(String, Object) - 类中的方法 weka.gui.beans.TextViewer
-
Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
- ConnectionNotificationConsumer - weka.gui.beans中的接口
-
Interface for Beans that can receive (dis-)connection events generated when (dis-)connecting data processing nodes in the Weka KnowledgeFlow.
- ConnectionPanel - weka.gui.sql中的类
-
Enables the user to insert a database URL, plus user/password to connect to this database.
- ConnectionPanel(JFrame) - 类的构造器 weka.gui.sql.ConnectionPanel
-
initializes the panel.
- CONNECTIONS - 类中的静态变量 weka.gui.beans.BeanConnection
-
The list of connections
- connectToDatabase() - 类中的方法 weka.core.converters.DatabaseLoader
-
Opens a connection to the database
- connectToDatabase() - 类中的方法 weka.core.converters.DatabaseSaver
-
Opens a connection to the database.
- connectToDatabase() - 类中的方法 weka.experiment.DatabaseUtils
-
Opens a connection to the database.
- consequence() - 类中的方法 weka.associations.RuleItem
-
Gets the consequence of a rule
- conservativeForwardSelectionTipText() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns the tip text for this property
- ConsistencySubsetEval - weka.attributeSelection中的类
-
ConsistencySubsetEval :
Evaluates the worth of a subset of attributes by the level of consistency in the class values when the training instances are projected onto the subset of attributes. - ConsistencySubsetEval() - 类的构造器 weka.attributeSelection.ConsistencySubsetEval
-
Constructor.
- ConsistencySubsetEval.hashKey - weka.attributeSelection中的类
-
Class providing keys to the hash table.
- ConsoleLogger - weka.core.logging中的类
-
A simple logger that outputs the logging information in the console.
- ConsoleLogger() - 类的构造器 weka.core.logging.ConsoleLogger
- CONST_AUTOMATIC_SHAPE - 类中的静态变量 weka.gui.visualize.Plot2D
- Constant - weka.core.pmml中的类
-
Class encapsulating a Constant Expression.
- Constant(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - 类的构造器 weka.core.pmml.Constant
-
Construct an new Constant Expression.
- constructWithCopy(double[][]) - 类中的静态方法 weka.core.matrix.Matrix
-
Construct a matrix from a copy of a 2-D array.
- containChildBallsTipText() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the tip text for this property.
- containedBy(Instance) - 类中的方法 weka.associations.ItemSet
-
Checks if an instance contains an item set.
- contains(int) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
test if node is contained in parent set
- contains(int) - 类中的方法 weka.classifiers.functions.supportVector.SMOset
-
Checks whether an element is in the set.
- contains(PrintStream) - 类中的方法 weka.core.Tee
-
checks whether the given PrintStream is already in the list.
- contains(Class) - 类中的方法 weka.core.xml.MethodHandler
-
checks whether a method is stored for the given class
- contains(Object) - 类中的方法 weka.core.FastVector
-
added by akibriya
- contains(Object) - 类中的方法 weka.core.Trie
-
Returns true if this collection contains the specified element.
- contains(Object) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Tests whether the specified object is a component in this list.
- contains(String) - 类中的方法 weka.core.Trie.TrieNode
-
checks whether a suffix can be found in its children
- contains(String) - 类中的方法 weka.core.xml.MethodHandler
-
checks whether a method is stored for the given property
- contains(String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Whether the HierarchyPropertyParser contains the given string
- contains(Literal) - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if this LiteralSet contains a given Literal.
- contains(DataObject) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Tests if the database contains the dataObject_Query
- contains(DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Tests if the database contains the dataObject_Query
- containsAll(Collection<?>) - 类中的方法 weka.core.Trie
-
Returns true if this collection contains all of the elements in the specified collection.
- containsEnvVariables(String) - 类中的静态方法 weka.core.Environment
-
Tests for the presence of environment variables.
- containsItems(ArrayList<Attribute>, boolean) - 类中的方法 weka.associations.FPGrowth.AssociationRule
- containsKey(double) - 类中的方法 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Tests if the specified double is a key in this hashtable.
- containsKey(double) - 类中的方法 weka.classifiers.lazy.kstar.KStarCache
-
Checks if the specified key maps with an entry in the cache table
- containsOverOneEvent() - 类中的方法 weka.associations.gsp.Element
-
Checks if an Element contains over one event.
- containsPrefix(String) - 类中的方法 weka.core.Trie
-
checks whether the given prefix is stored in the trie
- containsValue(double) - 类中的方法 weka.core.pmml.FieldMetaInfo.Interval
-
Returns true if this interval contains the supplied value.
- containsWindow(Class) - 类中的方法 weka.gui.Main
-
checks, whether an instance of the given window class is already in the Window list.
- containsWindow(String) - 类中的方法 weka.gui.Main
-
checks, whether a window with the given title is already in the Window list.
- CONTENTS - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
A Table of Contents.
- context() - 类中的方法 weka.gui.HierarchyPropertyParser
-
The context of the current node, i.e.
- ContingencyTables - weka.core中的类
-
Class implementing some statistical routines for contingency tables.
- ContingencyTables() - 类的构造器 weka.core.ContingencyTables
- CONTINUOUS - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Optype
- CONTINUOUS - 类中的静态变量 weka.datagenerators.clusterers.SubspaceCluster
-
cluster subtype: continuous
- ConverterFileChooser - weka.gui中的类
-
A specialized JFileChooser that lists all available file Loaders and Savers.
- ConverterFileChooser() - 类的构造器 weka.gui.ConverterFileChooser
-
onstructs a FileChooser pointing to the user's default directory.
- ConverterFileChooser(File) - 类的构造器 weka.gui.ConverterFileChooser
-
Constructs a FileChooser using the given File as the path.
- ConverterFileChooser(String) - 类的构造器 weka.gui.ConverterFileChooser
-
Constructs a FileChooser using the given path.
- ConverterUtils - weka.core.converters中的类
-
Utility routines for the converter package.
- ConverterUtils() - 类的构造器 weka.core.converters.ConverterUtils
- ConverterUtils.DataSink - weka.core.converters中的类
-
Helper class for saving data to files.
- ConverterUtils.DataSource - weka.core.converters中的类
-
Helper class for loading data from files and URLs.
- convertInfixToPostfix(String) - 类中的方法 weka.core.AttributeExpression
-
Converts a string containing a mathematical expression in infix form to postfix form.
- convertInstance(Instance) - 接口中的方法 weka.attributeSelection.AttributeTransformer
-
Transforms an instance in the format of the original data to the transformed space
- convertInstance(Instance) - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Transform an instance in original (unnormalized) format
- convertInstance(Instance) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Transform an instance in original (unormalized) format.
- convertNewLines(String) - 类中的静态方法 weka.core.Utils
-
Converts carriage returns and new lines in a string into \r and \n.
- convertNominalTipText() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the tip text for this property
- convertNominalToBinaryTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- convertNumericAttToNominal(int, ArrayList<String>) - 类中的方法 weka.core.pmml.MiningSchema
-
Convert a numeric attribute in the mining schema to nominal.
- convertStringAttsToNominal() - 类中的方法 weka.core.pmml.MiningSchema
-
Method to convert any string attributes in the mining schema Instances to nominal attributes.
- convertToAttribX(double) - 类中的方法 weka.gui.visualize.Plot2D
-
convert a Panel x coordinate to a raw x value.
- convertToAttribY(double) - 类中的方法 weka.gui.visualize.Plot2D
-
convert a Panel y coordinate to a raw y value.
- convertToPanelX(double) - 类中的方法 weka.gui.visualize.Plot2D
-
Convert an raw x value to Panel x coordinate.
- convertToPanelY(double) - 类中的方法 weka.gui.visualize.Plot2D
-
Convert an raw y value to Panel y coordinate.
- convertToRelativePath(File) - 类中的静态方法 weka.core.Utils
-
Converts a File's absolute path to a path relative to the user (ie start) directory.
- CONVICTION - enum class 中的枚举常量 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
- convictionForRule(AprioriItemSet, AprioriItemSet, int, int) - 类中的方法 weka.associations.AprioriItemSet
-
Outputs the conviction for a rule.
- copy() - 类中的方法 weka.associations.tertius.IndividualInstance
- copy() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Return a shallow copy of this kernel
- copy() - 类中的方法 weka.classifiers.rules.JRip.Antd
-
Implements Copyable
- copy() - 类中的方法 weka.classifiers.rules.JRip.NominalAntd
-
Implements Copyable
- copy() - 类中的方法 weka.classifiers.rules.JRip.NumericAntd
-
Implements Copyable
- copy() - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Get a shallow copy of this rule
- copy() - 类中的方法 weka.classifiers.rules.Rule
-
Get a shallow copy of this rule
- copy() - 类中的方法 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Makes a copy of this CorrelationSplitInfo object
- copy() - 接口中的方法 weka.classifiers.trees.m5.SplitEvaluate
-
makes a copy of the SplitEvaluate object
- copy() - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Makes a copy of this SplitInfo object
- copy() - 类中的方法 weka.core.Attribute
-
Produces a shallow copy of this attribute.
- copy() - 类中的方法 weka.core.BinarySparseInstance
-
Produces a shallow copy of this instance.
- copy() - 接口中的方法 weka.core.Copyable
-
This method produces a shallow copy of an object.
- copy() - 类中的方法 weka.core.FastVector
-
Produces a shallow copy of this vector.
- copy() - 类中的方法 weka.core.Instance
-
Produces a shallow copy of this instance.
- copy() - 类中的方法 weka.core.matrix.DoubleVector
-
Makes a deep copy of the vector
- copy() - 类中的方法 weka.core.matrix.IntVector
-
Makes a deep copy of the vector
- copy() - 类中的方法 weka.core.matrix.Matrix
-
Make a deep copy of a matrix
- copy() - 类中的方法 weka.core.SparseInstance
-
Produces a shallow copy of this instance.
- copy(String) - 类中的方法 weka.core.Attribute
-
Produces a shallow copy of this attribute with a new name.
- copy(ParentSet) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
Copy makes current parents set equal to other parent set
- Copy - weka.filters.unsupervised.attribute中的类
-
An instance filter that copies a range of attributes in the dataset.
- Copy() - 类的构造器 weka.filters.unsupervised.attribute.Copy
- Copyable - weka.core中的接口
-
Interface implemented by classes that can produce "shallow" copies of their objects.
- copyArea(int, int, int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- copyContent() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
copies the content of the selection to the clipboard
- copyContent() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
copies the content of the selection to the clipboard
- copyElements() - 类中的方法 weka.core.FastVector
-
Clones the vector and shallow copies all its elements.
- copyInto(Object[]) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Copies the components of this list into the specified array.
- copyRelationalValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - 类中的静态方法 weka.core.RelationalLocator
-
Takes relational values referenced by an Instance and copies them from a source dataset to a destination dataset.
- copyRelationalValues(Instance, Instances, AttributeLocator) - 类中的静态方法 weka.core.RelationalLocator
-
Copies relational values contained in the instance copied to a new dataset.
- Copyright - weka.core中的类
-
A class for providing centralized Copyright information.
- Copyright() - 类的构造器 weka.core.Copyright
- COPYRIGHT - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
Copyright information.
- copyStringValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - 类中的静态方法 weka.core.StringLocator
-
Takes string values referenced by an Instance and copies them from a source dataset to a destination dataset.
- copyStringValues(Instance, Instances, AttributeLocator) - 类中的静态方法 weka.core.StringLocator
-
Copies string values contained in the instance copied to a new dataset.
- copyToClipboard() - 类中的方法 weka.gui.sql.InfoPanel
-
copies the currently selected error message to the clipboard
- CORE_FILE_LOADERS - 类中的静态变量 weka.core.converters.ConverterUtils
-
the core loaders - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
- CORE_FILE_SAVERS - 类中的静态变量 weka.core.converters.ConverterUtils
-
the core savers - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
- coreDistance(int, double, DataObject) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Calculates the coreDistance for the specified DataObject.
- coreDistance(int, double, DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Calculates the coreDistance for the specified DataObject.
- correct() - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Gets the number of correct classifications (that is, for which a correct prediction was made).
- correct() - 类中的方法 weka.classifiers.Evaluation
-
Gets the number of instances correctly classified (that is, for which a correct prediction was made).
- correlation - 类中的变量 weka.experiment.PairedStats
-
The correlation coefficient
- correlation(double[], double[], int) - 类中的静态方法 weka.core.Utils
-
Returns the correlation coefficient of two double vectors.
- correlationCoefficient() - 类中的方法 weka.classifiers.Evaluation
-
Returns the correlation coefficient if the class is numeric.
- CorrelationSplitInfo - weka.classifiers.trees.m5中的类
-
Finds split points using correlation.
- CorrelationSplitInfo(int, int, int) - 类的构造器 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Constructs an object which contains the split information
- COS - 接口中的静态变量 weka.core.mathematicalexpression.sym
- COS - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- CostBenefitAnalysis - weka.gui.beans中的类
-
Bean that aids in analyzing cost/benefit tradeoffs.
- CostBenefitAnalysis() - 类的构造器 weka.gui.beans.CostBenefitAnalysis
-
Constructor.
- CostBenefitAnalysisBeanInfo - weka.gui.beans中的类
-
Bean info class for the cost/benefit analysis
- CostBenefitAnalysisBeanInfo() - 类的构造器 weka.gui.beans.CostBenefitAnalysisBeanInfo
- CostCurve - weka.classifiers.evaluation中的类
-
Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes.
- CostCurve() - 类的构造器 weka.classifiers.evaluation.CostCurve
- CostMatrix - weka.classifiers中的类
-
Class for storing and manipulating a misclassification cost matrix.
- CostMatrix(int) - 类的构造器 weka.classifiers.CostMatrix
-
Creates a default cost matrix of a particular size.
- CostMatrix(Reader) - 类的构造器 weka.classifiers.CostMatrix
-
Reads a matrix from a reader.
- CostMatrix(CostMatrix) - 类的构造器 weka.classifiers.CostMatrix
-
Creates a cost matrix that is a copy of another.
- CostMatrixEditor - weka.gui中的类
-
Class for editing CostMatrix objects.
- CostMatrixEditor() - 类的构造器 weka.gui.CostMatrixEditor
-
Constructs a new CostMatrixEditor.
- costMatrixSourceTipText() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
- costMatrixSourceTipText() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
- costMatrixSourceTipText() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns the tip text for this property
- costMatrixTipText() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
- costMatrixTipText() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
- costMatrixTipText() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns the tip text for this property
- CostSensitiveASEvaluation - weka.attributeSelection中的类
-
Abstract base class for cost-sensitive subset and attribute evaluators.
- CostSensitiveASEvaluation() - 类的构造器 weka.attributeSelection.CostSensitiveASEvaluation
- CostSensitiveAttributeEval - weka.attributeSelection中的类
-
A meta subset evaluator that makes its base subset evaluator cost-sensitive.
- CostSensitiveAttributeEval() - 类的构造器 weka.attributeSelection.CostSensitiveAttributeEval
-
Default constructor.
- CostSensitiveClassifier - weka.classifiers.meta中的类
-
A metaclassifier that makes its base classifier cost-sensitive.
- CostSensitiveClassifier() - 类的构造器 weka.classifiers.meta.CostSensitiveClassifier
-
Default constructor.
- CostSensitiveClassifierSplitEvaluator - weka.experiment中的类
-
SplitEvaluator that produces results for a classification scheme on a nominal class attribute, including weighted misclassification costs.
- CostSensitiveClassifierSplitEvaluator() - 类的构造器 weka.experiment.CostSensitiveClassifierSplitEvaluator
- CostSensitiveSubsetEval - weka.attributeSelection中的类
-
A meta subset evaluator that makes its base subset evaluator cost-sensitive.
- CostSensitiveSubsetEval() - 类的构造器 weka.attributeSelection.CostSensitiveSubsetEval
-
Default constructor.
- costTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- costTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- count - 类中的变量 weka.experiment.PairedStats
-
The number of data points seen
- count - 类中的变量 weka.experiment.Stats
-
The number of values seen
- count() - 类中的方法 weka.associations.RuleGeneration
-
Gets the actual maximum value of the generation time
- countBagCiters(Instance) - 类中的方法 weka.classifiers.mi.CitationKNN
-
calculates the citers associated to a bag
- countBagReferences(Instance) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Calculates the references of the exemplar bag
- countData() - 类中的方法 weka.classifiers.rules.RuleStats
-
Filter the data according to the ruleset and compute the basic stats: coverage/uncoverage, true/false positive/negatives of each rule
- countData(int, Instances, double[][]) - 类中的方法 weka.classifiers.rules.RuleStats
-
Count data from the position index in the ruleset assuming that given data are not covered by the rules in position 0...(index-1), and the statistics of these rules are provided.
This procedure is typically useful when a temporary object of RuleStats is constructed in order to efficiently calculate the relative DL of rule in position index, thus all other stuff is not needed. - counter() - 类中的方法 weka.associations.ItemSet
-
Gets the counter
- counterInstance(Instance) - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if an instance is a counter-instance of this LiteralSet.
- counterInstance(Instance) - 类中的方法 weka.associations.tertius.Rule
-
Test if an instance is a counter-instance of this rule.
- counterInstance(Instance, Instance) - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if an individual instance, given a part instance of this individual, is a counter-instance of this LiteralSet.
- countsForInstance(Instance) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Calculates the counts for Dirichlet distribution for the class membership probabilities for the given test instance.
- covers(Instance) - 类中的方法 weka.classifiers.rules.JRip.Antd
- covers(Instance) - 类中的方法 weka.classifiers.rules.JRip.NominalAntd
-
Whether the instance is covered by this antecedent
- covers(Instance) - 类中的方法 weka.classifiers.rules.JRip.NumericAntd
-
Whether the instance is covered by this antecedent
- covers(Instance) - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Whether the instance covered by this rule
- covers(Instance) - 类中的方法 weka.classifiers.rules.Rule
-
Whether the instance covered by this rule
- CoverTree - weka.core.neighboursearch中的类
-
Class implementing the CoverTree datastructure.
The class is very much a translation of the c source code made available by the authors.
For more information and original source code see:
Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor. - CoverTree() - 类的构造器 weka.core.neighboursearch.CoverTree
-
default constructor.
- CoverTree.CoverTreeNode - weka.core.neighboursearch中的类
-
class representing a node of the cover tree.
- CoverTreeNode() - 类的构造器 weka.core.neighboursearch.CoverTree.CoverTreeNode
-
Constructor for the class.
- CoverTreeNode(Integer, double, double, Stack<CoverTree.CoverTreeNode>, int, int) - 类的构造器 weka.core.neighboursearch.CoverTree.CoverTreeNode
-
Constructor.
- CramersV(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Computes Cramer's V for a contingency table.
- create() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Clone a PostscriptGraphics object
- create(Reader) - 类中的方法 weka.gui.treevisualizer.TreeBuild
-
This will build A node structure from the dotty format passed.
- createExperimentIndex() - 类中的方法 weka.experiment.DatabaseUtils
-
Attempts to create the experiment index table.
- createExperimentIndexEntry(ResultProducer) - 类中的方法 weka.experiment.DatabaseUtils
-
Attempts to insert a results entry for the table into the experiment index.
- createNewVisualizerWindow(Classifier, Instances) - 类中的静态方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Creates a new GUI window with all of the BoundaryVisualizer trappings,
- CreatePopulation(int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Create the initial Population
- createResultsTable(ResultProducer, String) - 类中的方法 weka.experiment.DatabaseUtils
-
Creates a results table for the supplied result producer.
- createSingleton() - 类中的静态方法 weka.gui.GUIChooser
-
Create a singleton instance of the GUIChooser
- createSingleton(String[]) - 类中的静态方法 weka.gui.beans.KnowledgeFlowApp
-
Create the singleton instance of the KnowledgeFlow
- createSingleton(String[]) - 类中的静态方法 weka.gui.Main
-
Create the singleton instance of the Main GUI.
- createSubsampleWithoutReplacement(Random, int, int) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
creates the subsample without replacement
- createSubsampleWithoutReplacement(Random, int, int, int, int[]) - 类中的方法 weka.filters.supervised.instance.Resample
-
creates the subsample without replacement.
- createSubsampleWithReplacement(Random, int, int) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
creates the subsample with replacement
- createSubsampleWithReplacement(Random, int, int, int, int[]) - 类中的方法 weka.filters.supervised.instance.Resample
-
creates the subsample with replacement.
- criticalValueTipText() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns the tip text for this property
- crossoverProbTipText() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns the tip text for this property
- CROSSREF - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The database key of the entry being cross referenced.
- crossValidate(NaiveBayesUpdateable, Instances, Random) - 类中的静态方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Utility method for fast 5-fold cross validation of a naive bayes model
- CrossValidateAttributes() - 类中的方法 weka.attributeSelection.AttributeSelection
-
Perform a cross validation for attribute selection.
- crossValidateModel(String, Instances, int, String[], Random) - 类中的方法 weka.classifiers.Evaluation
-
Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
- crossValidateModel(String, Instances, int, String[], Random) - 类中的静态方法 weka.clusterers.ClusterEvaluation
-
Performs a cross-validation for a DensityBasedClusterer clusterer on a set of instances.
- crossValidateModel(Classifier, Instances, int, Random, Object...) - 类中的方法 weka.classifiers.Evaluation
-
Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
- crossValidateModel(DensityBasedClusterer, Instances, int, Random) - 类中的静态方法 weka.clusterers.ClusterEvaluation
-
Perform a cross-validation for DensityBasedClusterer on a set of instances.
- crossValidateTipText() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the tip text for this property.
- CrossValidationFoldMaker - weka.gui.beans中的类
-
Bean for splitting instances into training ant test sets according to a cross validation
- CrossValidationFoldMaker() - 类的构造器 weka.gui.beans.CrossValidationFoldMaker
- CrossValidationFoldMakerBeanInfo - weka.gui.beans中的类
-
BeanInfo class for the cross validation fold maker bean
- CrossValidationFoldMakerBeanInfo() - 类的构造器 weka.gui.beans.CrossValidationFoldMakerBeanInfo
- CrossValidationFoldMakerCustomizer - weka.gui.beans中的类
-
GUI Customizer for the cross validation fold maker bean
- CrossValidationFoldMakerCustomizer() - 类的构造器 weka.gui.beans.CrossValidationFoldMakerCustomizer
- CrossValidationResultProducer - weka.experiment中的类
-
Generates for each run, carries out an n-fold cross-validation, using the set SplitEvaluator to generate some results.
- CrossValidationResultProducer() - 类的构造器 weka.experiment.CrossValidationResultProducer
- crossValTipText() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns the tip text for this property
- CSVLoader - weka.core.converters中的类
-
Reads a source that is in comma separated or tab separated format.
- CSVLoader() - 类的构造器 weka.core.converters.CSVLoader
-
default constructor.
- CSVResultListener - weka.experiment中的类
-
Takes results from a result producer and assembles them into comma separated value form.
- CSVResultListener() - 类的构造器 weka.experiment.CSVResultListener
-
Sets temporary file.
- CSVSaver - weka.core.converters中的类
-
Writes to a destination that is in csv format
- CSVSaver() - 类的构造器 weka.core.converters.CSVSaver
-
Constructor
- cTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- cTipText() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns the tip text for this property
- cTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- cTipText() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns the tip text for this property
- cumulate() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns a vector that stores the cumulated values of the original vector
- cumulateInPlace() - 类中的方法 weka.core.matrix.DoubleVector
-
Cumulates the original vector in place
- cumulativeCV(BayesNet) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
CumulativeCV returns the accuracy calculated using cumulative cross validation.
- CustomizerCloseRequester - weka.gui.beans中的接口
-
Customizers who want to be able to close the customizer window themselves can implement this window.
- customizerClosing() - 类中的方法 weka.gui.beans.ClassAssignerCustomizer
- customizerClosing() - 类中的方法 weka.gui.beans.ClassifierCustomizer
- customizerClosing() - 类中的方法 weka.gui.beans.ClassValuePickerCustomizer
- customizerClosing() - 接口中的方法 weka.gui.beans.CustomizerClosingListener
-
Customizer classes that want to know when they are being disposed of can implement this method.
- CustomizerClosingListener - weka.gui.beans中的接口
- CustomPanelSupplier - weka.gui中的接口
-
An interface for objects that are capable of supplying their own custom GUI components.
- cutOffFactorTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- cutoffTipText() - 类中的方法 weka.clusterers.Cobweb
-
Returns the tip text for this property
- cutpointsToString(double[], boolean[]) - 类中的静态方法 weka.estimators.EstimatorUtils
-
Returns a string representing the cutpoints
- CV_BASED - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
- CVBasedHyperparameter() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Method computes the best hyperparameter value by doing cross -validation on the training data and compute the likelihood.
- CVParameterSelection - weka.classifiers.meta中的类
-
Class for performing parameter selection by cross-validation for any classifier.
For more information, see:
R. - CVParameterSelection() - 类的构造器 weka.classifiers.meta.CVParameterSelection
- CVParametersTipText() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns the tip text for this property
- CVResultsString() - 类中的方法 weka.attributeSelection.AttributeSelection
-
returns a string summarizing the results of repeated attribute selection runs on splits of a dataset.
- CVS - enum class 中的枚举常量 weka.core.RevisionUtils.Type
-
CVS.
- CVTypeTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
D
- D_CONVCHCLOSER - 类中的静态变量 weka.clusterers.XMeans
-
have a closer look at converge children.
- D_CURR - 类中的静态变量 weka.clusterers.XMeans
-
for current debug.
- D_FOLLOWSPLIT - 类中的静态变量 weka.clusterers.XMeans
-
follows the splitting of the centers.
- D_GENERAL - 类中的静态变量 weka.clusterers.XMeans
-
general debugging.
- D_ITERCOUNT - 类中的静态变量 weka.clusterers.XMeans
-
follow iterations.
- D_KDTREE - 类中的静态变量 weka.clusterers.XMeans
-
check on kdtree.
- D_METH_MISUSE - 类中的静态变量 weka.clusterers.XMeans
-
functions were maybe misused.
- D_PRINTCENTERS - 类中的静态变量 weka.clusterers.XMeans
-
print the centers.
- D_RANDOMVECTOR - 类中的静态变量 weka.clusterers.XMeans
-
check on random vectors.
- Dagging - weka.classifiers.meta中的类
-
This meta classifier creates a number of disjoint, stratified folds out of the data and feeds each chunk of data to a copy of the supplied base classifier.
- Dagging() - 类的构造器 weka.classifiers.meta.Dagging
-
Constructor.
- Database - weka.clusterers.forOPTICSAndDBScan.Databases中的接口
-
Database.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 20, 2004
Time: 1:03:43 PM
$ Revision 1.4 $ - database_distanceTypeTipText() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the tip text for this property
- database_distanceTypeTipText() - 类中的方法 weka.clusterers.OPTICS
-
Returns the tip text for this property
- database_TypeTipText() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the tip text for this property
- database_TypeTipText() - 类中的方法 weka.clusterers.OPTICS
-
Returns the tip text for this property
- DatabaseConnection - weka.core.converters中的类
-
Connects to a database.
- DatabaseConnection() - 类的构造器 weka.core.converters.DatabaseConnection
-
Sets up the database drivers
- DatabaseConnectionDialog - weka.gui中的类
-
A dialog to enter URL, username and password for a database connection.
- DatabaseConnectionDialog(Frame) - 类的构造器 weka.gui.DatabaseConnectionDialog
-
Create database connection dialog.
- DatabaseConnectionDialog(Frame, String, String) - 类的构造器 weka.gui.DatabaseConnectionDialog
-
Create database connection dialog.
- DatabaseConnectionDialog(Frame, String, String, boolean) - 类的构造器 weka.gui.DatabaseConnectionDialog
-
Create database connection dialog.
- DatabaseConverter - weka.core.converters中的接口
-
Marker interface for a loader/saver that uses a database
- databaseForName(String, Instances) - 类中的方法 weka.clusterers.DBSCAN
-
Returns a new Class-Instance of the specified database
- databaseForName(String, Instances) - 类中的方法 weka.clusterers.OPTICS
-
Returns a new Class-Instance of the specified database
- DatabaseLoader - weka.core.converters中的类
-
Reads Instances from a Database.
- DatabaseLoader() - 类的构造器 weka.core.converters.DatabaseLoader
-
Constructor
- databaseOutputTipText() - 类中的方法 weka.clusterers.OPTICS
-
Returns the tip text for this property.
- DatabaseResultListener - weka.experiment中的类
-
Takes results from a result producer and sends them to a database.
- DatabaseResultListener() - 类的构造器 weka.experiment.DatabaseResultListener
-
Sets up the database drivers
- DatabaseResultProducer - weka.experiment中的类
-
Examines a database and extracts out the results produced by the specified ResultProducer and submits them to the specified ResultListener.
- DatabaseResultProducer() - 类的构造器 weka.experiment.DatabaseResultProducer
-
Creates the DatabaseResultProducer, letting the parent constructor do it's thing.
- DatabaseSaver - weka.core.converters中的类
-
Writes to a database (tested with MySQL, InstantDB, HSQLDB).
- DatabaseSaver() - 类的构造器 weka.core.converters.DatabaseSaver
-
Constructor.
- databaseURLTipText() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns the tip text for this property.
- DatabaseUtils - weka.experiment中的类
-
DatabaseUtils provides utility functions for accessing the experiment database.
- DatabaseUtils() - 类的构造器 weka.experiment.DatabaseUtils
-
Reads properties and sets up the database drivers.
- dataDL(double, double, double, double, double) - 类中的静态方法 weka.classifiers.rules.RuleStats
-
The description length of data given the parameters of the data based on the ruleset.
- DataFormatListener - weka.gui.beans中的接口
-
Listener interface that customizer classes that are interested in data format changes can implement.
- DataGenerator - weka.datagenerators中的类
-
Abstract superclass for data generators that generate data for classifiers and clusterers.
- DataGenerator - weka.gui.boundaryvisualizer中的接口
-
Interface to something that can generate new instances based on a set of input instances
- DataGenerator() - 类的构造器 weka.datagenerators.DataGenerator
-
initializes with default settings.
- DataGeneratorPanel - weka.gui.explorer中的类
-
A panel for generating artificial data via DataGenerators.
- DataGeneratorPanel() - 类的构造器 weka.gui.explorer.DataGeneratorPanel
-
creates the panel
- DataNearBalancedND - weka.classifiers.meta.nestedDichotomies中的类
-
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random data-balanced tree structure.
For more info, check
Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. - DataNearBalancedND() - 类的构造器 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Constructor.
- DataObject - weka.clusterers.forOPTICSAndDBScan.DataObjects中的接口
-
DataObject.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 19, 2004
Time: 5:48:59 PM
$ Revision 1.4 $ - dataObjectForName(String, Instance, String, Database) - 类中的方法 weka.clusterers.DBSCAN
-
Returns a new Class-Instance of the specified database
- dataObjectForName(String, Instance, String, Database) - 类中的方法 weka.clusterers.OPTICS
-
Returns a new Class-Instance of the specified database
- dataObjectIterator() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Returns an iterator over all the dataObjects in the database
- dataObjectIterator() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Returns an iterator over all the dataObjects in the database
- dataSeqIDTipText() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the dataSeqID option tip text for the Weka GUI.
- dataset() - 类中的方法 weka.core.Instance
-
Returns the dataset this instance has access to.
- DATASET_FIELD_NAME - 类中的静态变量 weka.experiment.CrossValidationResultProducer
-
The name of the key field containing the dataset name
- DATASET_FIELD_NAME - 类中的静态变量 weka.experiment.RandomSplitResultProducer
-
The name of the key field containing the dataset name
- DataSetEvent - weka.gui.beans中的类
-
Event encapsulating a data set
- DataSetEvent(Object, Instances) - 类的构造器 weka.gui.beans.DataSetEvent
- DatasetListPanel - weka.gui.experiment中的类
-
This panel controls setting a list of datasets for an experiment to iterate over.
- DatasetListPanel() - 类的构造器 weka.gui.experiment.DatasetListPanel
-
Create the dataset list panel initially disabled.
- DatasetListPanel(Experiment) - 类的构造器 weka.gui.experiment.DatasetListPanel
-
Creates the dataset list panel with the given experiment.
- DataSink - weka.gui.beans中的接口
-
Indicator interface to something that can store instances to some destination
- DataSink(OutputStream) - 类的构造器 weka.core.converters.ConverterUtils.DataSink
-
initializes the sink to save the data in the stream (always in ARFF format).
- DataSink(String) - 类的构造器 weka.core.converters.ConverterUtils.DataSink
-
initializes the sink to save the data to the given file.
- DataSink(Saver) - 类的构造器 weka.core.converters.ConverterUtils.DataSink
-
initializes the sink to save the data to the given Saver (expected to be fully configured).
- DataSource - weka.gui.beans中的接口
-
Interface to something that is capable of being a source for data - either batch or incremental data
- DataSource(InputStream) - 类的构造器 weka.core.converters.ConverterUtils.DataSource
-
Initializes the datasource with the given input stream.
- DataSource(String) - 类的构造器 weka.core.converters.ConverterUtils.DataSource
-
Tries to load the data from the file.
- DataSource(Loader) - 类的构造器 weka.core.converters.ConverterUtils.DataSource
-
Initializes the datasource with the given Loader.
- DataSource(Instances) - 类的构造器 weka.core.converters.ConverterUtils.DataSource
-
Initializes the datasource with the given dataset.
- DataSourceListener - weka.gui.beans中的接口
-
Interface to something that can accept DataSetEvents
- DATATYPE_LAYOUT - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the data that is about to be read/written contains a complete layout
- DATATYPE_USERCOMPONENTS - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the data that is about to be read/written contains user-components, i.e., Metabeans
- DataVisualizer - weka.gui.beans中的类
-
Bean that encapsulates weka.gui.visualize.VisualizePanel
- DataVisualizer() - 类的构造器 weka.gui.beans.DataVisualizer
- DataVisualizerBeanInfo - weka.gui.beans中的类
-
Bean info class for the data visualizer
- DataVisualizerBeanInfo() - 类的构造器 weka.gui.beans.DataVisualizerBeanInfo
- DATE - 类中的静态变量 weka.core.Attribute
-
Constant set for attributes with date values.
- DATE - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for DATE used for reading experiment results.
- DATE_ATTRIBUTES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle date attributes
- DATE_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle date classes
- dateAttributesTipText() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the tip text for this property.
- dateFormatTipText() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the tip text for this property.
- dateFormatTipText() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns the tip text for this property.
- dateFormatTipText() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
- DbConnectionDialog(String, String) - 类中的方法 weka.gui.DatabaseConnectionDialog
-
Display the database connection dialog
- DbConnectionDialog(String, String, boolean) - 类中的方法 weka.gui.DatabaseConnectionDialog
-
Display the database connection dialog
- DBO() - 类的构造器 weka.core.Debug.DBO
- DBSCAN - weka.clusterers中的类
-
Basic implementation of DBSCAN clustering algorithm that should *not* be used as a reference for runtime benchmarks: more sophisticated implementations exist! Clustering of new instances is not supported.
- DBSCAN() - 类的构造器 weka.clusterers.DBSCAN
- DbUtils - weka.gui.sql中的类
-
A little bit extended DatabaseUtils class.
- DbUtils() - 类的构造器 weka.gui.sql.DbUtils
-
initializes the object.
- dchisq(double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the density of the Chi-squared distribution.
- dchisq(double, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the density of the noncentral Chi-squared distribution.
- dchisq(double, DoubleVector) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the density of the noncentral Chi-squared distribution.
- dchisqLog(double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the log-density of the noncentral Chi-square distribution.
- dchisqLog(double, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the log-density value of a noncentral Chi-square distribution.
- dchisqLog(double, DoubleVector) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the log-density of a set of noncentral Chi-squared distributions.
- DDConditionalEstimator - weka.estimators中的类
-
Conditional probability estimator for a discrete domain conditional upon a discrete domain.
- DDConditionalEstimator(int, int, boolean) - 类的构造器 weka.estimators.DDConditionalEstimator
-
Constructor
- Debug - weka.core中的类
-
A helper class for debug output, logging, clocking, etc.
- Debug() - 类的构造器 weka.core.Debug
-
default constructor, prints only to stdout
- Debug(String) - 类的构造器 weka.core.Debug
-
logs the output to the specified file (and stdout).
- Debug(String, int, int) - 类的构造器 weka.core.Debug
-
logs the output
- DEBUG - 类中的静态变量 weka.gui.LogWindow
-
whether we're debugging - enables output on stdout
- Debug.Clock - weka.core中的类
-
A little helper class for clocking and outputting times.
- Debug.DBO - weka.core中的类
-
contains debug methods
- Debug.Log - weka.core中的类
-
A helper class for logging stuff.
- Debug.Random - weka.core中的类
-
This extended Random class enables one to print the generated random numbers etc., before they are returned.
- Debug.SimpleLog - weka.core中的类
-
A little, simple helper class for logging stuff.
- Debug.Timestamp - weka.core中的类
-
A class that can be used for timestamps in files, The toString() method simply returns the associated Date object in a timestamp format.
- debugLevelTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- debugTipText() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.classifiers.Classifier
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.classifiers.rules.JRip
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.clusterers.EM
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.clusterers.HierarchicalClusterer
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.clusterers.sIB
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
the tip text for this property
- debugTipText() - 类中的方法 weka.datagenerators.DataGenerator
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.estimators.Estimator
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns the tip text for this property.
- debugTipText() - 类中的方法 weka.filters.SimpleFilter
-
Returns the tip text for this property
- debugTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Returns the tip text for this property
- debugVectorsFileTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- decayTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- decimalsTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- DecisionStump - weka.classifiers.trees中的类
-
Class for building and using a decision stump.
- DecisionStump() - 类的构造器 weka.classifiers.trees.DecisionStump
- DecisionTable - weka.classifiers.rules中的类
-
Class for building and using a simple decision table majority classifier.
For more information see:
Ron Kohavi: The Power of Decision Tables. - DecisionTable() - 类的构造器 weka.classifiers.rules.DecisionTable
-
Constructor for a DecisionTable
- DecisionTableHashKey - weka.classifiers.rules中的类
-
Class providing hash table keys for DecisionTable
- DecisionTableHashKey(double[]) - 类的构造器 weka.classifiers.rules.DecisionTableHashKey
-
Constructor for a hashKey
- DecisionTableHashKey(Instance, int, boolean) - 类的构造器 weka.classifiers.rules.DecisionTableHashKey
-
Constructor for a hashKey
- decompose() - 类中的方法 weka.classifiers.BVDecompose
-
Carry out the bias-variance decomposition
- decompose() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Carry out the bias-variance decomposition using the sub-sampled cross-validation method.
- Decorate - weka.classifiers.meta中的类
-
DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examples.
- Decorate() - 类的构造器 weka.classifiers.meta.Decorate
-
Constructor.
- decreaseFrequency() - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
Decrement the frequency of this item.
- decreaseFrequency(int) - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
Decrease the frequency of this item.
- DEFAULT_COLORS - 类中的静态变量 weka.gui.boundaryvisualizer.BoundaryPanel
-
default colours for classes
- DEFAULT_FORMAT - 类中的静态变量 weka.core.Debug.Timestamp
-
the default format
- DEFAULT_FORMAT - 类中的静态变量 weka.gui.SimpleDateFormatEditor
-
the default format
- DEFAULT_HEIGHT - 类中的静态变量 weka.gui.arffviewer.ArffViewerMainPanel
-
the default for height
- DEFAULT_LEFT - 类中的静态变量 weka.gui.arffviewer.ArffViewerMainPanel
-
the default for left
- DEFAULT_SEPARATORS - 类中的静态变量 weka.core.TestInstances
-
the default word separators used in strings
- DEFAULT_SHAPE_SIZE - 类中的静态变量 weka.gui.visualize.Plot2D
- DEFAULT_TOP - 类中的静态变量 weka.gui.arffviewer.ArffViewerMainPanel
-
the default for top
- DEFAULT_WIDTH - 类中的静态变量 weka.gui.arffviewer.ArffViewerMainPanel
-
the default for width
- DEFAULT_WORDS - 类中的静态变量 weka.core.TestInstances
-
the default list of words used in strings
- defaultEvaluatorString() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Return the name of the default evaluator.
- defaultEvaluatorString() - 类中的方法 weka.attributeSelection.CostSensitiveAttributeEval
-
Return the name of the default evaluator.
- defaultOutput() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the writer, which is used for outputting to stdout.
- defaultWeightTipText() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns the tip text for this property
- defineDataFormat() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Initializes the format for the dataset produced.
- defineDataFormat() - 类中的方法 weka.datagenerators.DataGenerator
-
Initializes the format for the dataset produced.
- DefineFunction - weka.core.pmml中的类
-
Class encapsulating DefineFunction (used in TransformationDictionary).
- DefineFunction(Element, TransformationDictionary) - 类的构造器 weka.core.pmml.DefineFunction
- degreeTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- del(int, Instance) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Deletes given instance from given bag.
- delete() - 类中的方法 weka.core.Instances
-
Removes all instances from the set.
- delete(int) - 类中的方法 weka.classifiers.functions.supportVector.SMOset
-
Deletes an element from the set.
- delete(int) - 类中的方法 weka.core.Instances
-
Removes an instance at the given position from the set.
- deleteArc(int, int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Delete arc between two nodes.
- deleteArc(String, String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Delete arc between two nodes.
- deleteAttribute() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
deletes the currently selected attribute
- deleteAttribute(boolean) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
deletes the current selected Attribute or several chosen ones
- deleteAttributeAt(int) - 类中的方法 weka.core.Instance
-
Deletes an attribute at the given position (0 to numAttributes() - 1).
- deleteAttributeAt(int) - 类中的方法 weka.core.Instances
-
Deletes an attribute at the given position (0 to numAttributes() - 1).
- deleteAttributeAt(int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
deletes the attribute at the given col index
- deleteAttributeAt(int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
deletes the attribute at the given col index.
- deleteAttributeAt(int, boolean) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
deletes the attribute at the given col index
- deleteAttributes() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
deletes the chosen attributes
- deleteAttributes(int[]) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
deletes the attributes at the given indices
- deleteAttributes(int[]) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
deletes the attributes at the given indices
- deleteAttributeType(int) - 类中的方法 weka.core.Instances
-
Deletes all attributes of the given type in the dataset.
- deleteEmptyBinsTipText() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns the tip text for this property
- deleteEvent(String) - 类中的方法 weka.associations.gsp.Element
-
Deletes the first or last event of an Element.
- deleteGraftedCases(Instances) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
deletes the cases in data that belong to leaf pointed to by the test (i.e.
- deleteInfrequentSequences(FastVector, long) - 类中的静态方法 weka.associations.gsp.Sequence
-
Deletes Sequences of a given set which don't meet the minimum support count threshold.
- deleteInstance() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
deletes the currently selected instance
- deleteInstance(boolean) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
deletes the current selected Instance or several chosen ones
- deleteInstanceAt(int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
deletes the instance at the given index
- deleteInstanceAt(int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
deletes the instance at the given index
- deleteInstanceAt(int, boolean) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
deletes the instance at the given index
- deleteInstances() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
deletes all the currently selected instances
- deleteInstances(int[]) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
deletes the instances at the given positions
- deleteInstances(int[]) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
deletes the instances at the given positions
- deleteItemSets(FastVector, int, int) - 类中的静态方法 weka.associations.ItemSet
-
Deletes all item sets that don't have minimum support.
- deleteItemSets(FastVector, int, int) - 类中的静态方法 weka.associations.LabeledItemSet
-
Deletes all item sets that don't have minimum support and have more than maximum support
- deleteLastParent(Instances) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
Delete last added parent from parent set and update internals (specifically the cardinality of the parent set)
- deleteNode(int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
- deleteNode(String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
- deleteParent(int, Instances) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
delete node from parent set
- deleteSelection(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Delete nodes with indexes in selection from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
- deleteStringAttributes() - 类中的方法 weka.core.Instances
-
Deletes all string attributes in the dataset.
- deleteWithMissing(int) - 类中的方法 weka.core.Instances
-
Removes all instances with missing values for a particular attribute from the dataset.
- deleteWithMissing(Attribute) - 类中的方法 weka.core.Instances
-
Removes all instances with missing values for a particular attribute from the dataset.
- deleteWithMissingClass() - 类中的方法 weka.core.Instances
-
Removes all instances with a missing class value from the dataset.
- delimitersTipText() - 类中的方法 weka.core.tokenizers.CharacterDelimitedTokenizer
-
Returns the tip text for this property
- delNodeValue(int, String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Delete node value from a node.
- delRange(int, Instances, int, int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Deletes all instances in given range from given bag.
- Delta - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Trust Region Radius
- DeltaBeta - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Array to store Regression Coefficient updates.
- DeltaR - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
This vector is used to store the increments on the R(i).
- deltaTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- deltaTipText() - 类中的方法 weka.associations.FPGrowth
-
Returns the tip text for this property
- deltaTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- deltaTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- DeltaUpdate - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Trust Region Radius Update
- DensityBasedClusterer - weka.clusterers中的接口
-
Interface for clusterers that can estimate the density for a given instance.
- DensityBasedClustererSplitEvaluator - weka.experiment中的类
-
A SplitEvaluator that produces results for a density based clusterer.
- DensityBasedClustererSplitEvaluator() - 类的构造器 weka.experiment.DensityBasedClustererSplitEvaluator
- densityBasedClustererTipText() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Returns a description of this option suitable for display as a tip text in the gui.
- dependencies() - 类中的方法 weka.core.Capabilities
-
Returns an Iterator over the stored dependencies
- depth() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Get the depth of the tree, i.e.
- DerivedFieldMetaInfo - weka.core.pmml中的类
- DerivedFieldMetaInfo(Element, ArrayList<Attribute>, TransformationDictionary) - 类的构造器 weka.core.pmml.DerivedFieldMetaInfo
- descendantPopulationSizeTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- descendantPopulationSizeTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- description() - 类中的方法 weka.associations.tertius.Predicate
- description() - 类中的方法 weka.core.Option
-
Returns the option's description.
- deserialize(InputStream) - 类中的静态方法 weka.core.Jython
-
deserializes the Python Object from the stream
- deSerialize(String) - 类中的静态方法 weka.core.xml.XStream
-
Deserializes an object from the supplied XML string
- designatedClassTipText() - 类中的方法 weka.classifiers.meta.ThresholdSelector
- desiredSizeTipText() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns the tip text for this property
- desiredWeightOfInstancesPerIntervalTipText() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the tip text for this property
- det() - 类中的方法 weka.core.matrix.LUDecomposition
-
Determinant
- det() - 类中的方法 weka.core.matrix.Matrix
-
Matrix determinant
- detectionPerAttributeTipText() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns the tip text for this property
- determineBounds() - 类中的方法 weka.gui.visualize.Plot2D
-
Determine the min and max values for axis and colouring attributes
- determineColumnConstraints(ResultProducer) - 类中的方法 weka.experiment.AveragingResultProducer
-
Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
- determineColumnConstraints(ResultProducer) - 类中的方法 weka.experiment.CSVResultListener
-
Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
- determineColumnConstraints(ResultProducer) - 类中的方法 weka.experiment.DatabaseResultListener
-
Determines if there are any constraints (imposed by the destination) on any additional measures produced by resultProducers.
- determineColumnConstraints(ResultProducer) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
- determineColumnConstraints(ResultProducer) - 接口中的方法 weka.experiment.ResultListener
-
Determines if there are any constraints (imposed by the destination) on additional result columns to be produced by resultProducers.
- determineValues(Instances) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
determines the values to retain, it is always at least 1 and up to the maximum number of distinct values
- DIAMOND_SHAPE - 类中的静态变量 weka.gui.visualize.Plot2D
- differencesProbability - 类中的变量 weka.experiment.PairedStats
-
The probability of obtaining the observed differences
- differencesSignificance - 类中的变量 weka.experiment.PairedStats
-
A significance indicator: 0 if the differences are not significant > 0 if x significantly greater than y < 0 if x significantly less than y
- differencesStats - 类中的变量 weka.experiment.PairedStats
-
The stats associated with the paired differences
- DIRECTED - 接口中的静态变量 weka.gui.graphvisualizer.GraphConstants
-
Types of Edges
- directionTipText() - 类中的方法 weka.attributeSelection.BestFirst
-
Returns the tip text for this property
- disable(Capabilities.Capability) - 类中的方法 weka.core.Capabilities
-
disables the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
- disable(Capabilities.Capability) - 类中的方法 weka.core.FindWithCapabilities
-
disables the given capability.
- disableAll() - 类中的方法 weka.core.Capabilities
-
disables all attribute and class types (including dependencies)
- disableAllAttributeDependencies() - 类中的方法 weka.core.Capabilities
-
disables all attribute type dependencies
- disableAllAttributes() - 类中的方法 weka.core.Capabilities
-
disables all attribute types
- disableAllClassDependencies() - 类中的方法 weka.core.Capabilities
-
disables all class type dependencies
- disableAllClasses() - 类中的方法 weka.core.Capabilities
-
disables all class types
- disabled_getEquivalent() - 类中的方法 weka.associations.Tertius
-
Get the value of equivalent.
- disabled_getPartFile() - 类中的方法 weka.associations.Tertius
-
Get the value of partFile.
- disabled_getSameClause() - 类中的方法 weka.associations.Tertius
-
Get the value of sameClause.
- disabled_getSubsumption() - 类中的方法 weka.associations.Tertius
-
Get the value of subsumption.
- disabled_setEquivalent(boolean) - 类中的方法 weka.associations.Tertius
-
Set the value of equivalent.
- disabled_setPartFile(File) - 类中的方法 weka.associations.Tertius
-
Set the value of partFile.
- disabled_setSameClause(boolean) - 类中的方法 weka.associations.Tertius
-
Set the value of sameClause.
- disabled_setSubsumption(boolean) - 类中的方法 weka.associations.Tertius
-
Set the value of subsumption.
- disableDependency(Capabilities.Capability) - 类中的方法 weka.core.Capabilities
-
disables the dependency of the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
- disableNot(Capabilities.Capability) - 类中的方法 weka.core.FindWithCapabilities
-
disables the given "not to have" capability.
- disconnect(NeuralConnection, NeuralConnection) - 类中的静态方法 weka.classifiers.functions.neural.NeuralConnection
-
Disconnects two units.
- DISCONNECT - 类中的静态变量 weka.gui.sql.event.ConnectionEvent
-
it was a disconnect
- disconnectFromDatabase() - 类中的方法 weka.experiment.DatabaseUtils
-
Closes the connection to the database.
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event named
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.Associator
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 接口中的方法 weka.gui.beans.BeanCommon
-
Notify this object that it has been deregistered as a listener with a source for named event.
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.ClassAssigner
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.Classifier
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.ClassValuePicker
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.Clusterer
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 接口中的方法 weka.gui.beans.ConnectionNotificationConsumer
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name This method should be implemented
synchronized . - disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Notify this object that it has been deregistered as a listener with a source for named event.
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.Filter
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.Loader
-
Notify this object that it has been deregistered as a listener with a source for named event.
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.MetaBean
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.PredictionAppender
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.StripChart
-
Notify this object that it has been deregistered as a listener with a source for named event.
- disconnectionNotification(String, Object) - 类中的方法 weka.gui.beans.TextViewer
-
Notify this object that it has been deregistered as a listener with a source for named event.
- DiscreteEstimator - weka.estimators中的类
-
Simple symbolic probability estimator based on symbol counts.
- DiscreteEstimator(int, boolean) - 类的构造器 weka.estimators.DiscreteEstimator
-
Constructor
- DiscreteEstimator(int, double) - 类的构造器 weka.estimators.DiscreteEstimator
-
Constructor
- DiscreteEstimatorBayes - weka.classifiers.bayes.net.estimate中的类
-
Symbolic probability estimator based on symbol counts and a prior.
- DiscreteEstimatorBayes(int, double) - 类的构造器 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Constructor
- DiscreteEstimatorFullBayes - weka.classifiers.bayes.net.estimate中的类
-
Symbolic probability estimator based on symbol counts and a prior.
- DiscreteEstimatorFullBayes(int, double, double, DiscreteEstimatorBayes, DiscreteEstimatorBayes, double) - 类的构造器 weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes
-
Constructor
- DiscreteFunction - weka.classifiers.functions.pace中的类
-
Class for handling discrete functions.
- DiscreteFunction() - 类的构造器 weka.classifiers.functions.pace.DiscreteFunction
-
Constructs an empty discrete function
- DiscreteFunction(DoubleVector) - 类的构造器 weka.classifiers.functions.pace.DiscreteFunction
-
Constructs a discrete function with the point values provides and the function values are all 1/n.
- DiscreteFunction(DoubleVector, DoubleVector) - 类的构造器 weka.classifiers.functions.pace.DiscreteFunction
-
Constructs a discrete function with both the point values and function values provided.
- Discretize - weka.core.pmml中的类
-
Class encapsulating a Discretize Expression.
- Discretize - weka.filters.supervised.attribute中的类
-
An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
- Discretize - weka.filters.unsupervised.attribute中的类
-
An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
- Discretize() - 类的构造器 weka.filters.supervised.attribute.Discretize
-
Constructor - initialises the filter
- Discretize() - 类的构造器 weka.filters.unsupervised.attribute.Discretize
-
Constructor - initialises the filter
- Discretize(String) - 类的构造器 weka.filters.unsupervised.attribute.Discretize
-
Another constructor, sets the attribute indices immediately
- Discretize(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - 类的构造器 weka.core.pmml.Discretize
-
Constructs a Discretize Expression
- discretizeBinTipText() - 类中的方法 weka.classifiers.mi.MIBoost
-
Returns the tip text for this property
- displayModelInOldFormatTipText() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns the tip text for this property
- displayModelInOldFormatTipText() - 类中的方法 weka.clusterers.EM
-
Returns the tip text for this property
- displayResultset(int) - 类中的方法 weka.experiment.PairedTTester
-
Checks whether the resultset with the given index shall be displayed.
- displayResultset(int) - 接口中的方法 weka.experiment.Tester
-
Checks whether the resultset with the given index shall be displayed.
- displayRulesTipText() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns the tip text for this property
- displayStdDevsTipText() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns the tip text for this property
- dispose() - 类中的方法 weka.gui.GUIChooser.ChildFrameSDI
-
de-registers the child frame with the parent first.
- dispose() - 类中的方法 weka.gui.Main.ChildFrameMDI
-
de-registers the child frame with the parent first.
- dispose() - 类中的方法 weka.gui.Main.ChildFrameSDI
-
de-registers the child frame with the parent first.
- dispose() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- disposeSplash() - 类中的静态方法 weka.gui.SplashWindow
-
Closes the splash window.
- distance(DataObject) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Calculates the distance between dataObject and this.dataObject
- distance(DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Calculates the euclidian-distance between dataObject and this.dataObject
- distance(DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Calculates the manhattan-distance between dataObject and this.dataObject
- distance(Instance, Instance) - 类中的方法 weka.classifiers.mi.CitationKNN
-
distance between two instances
- distance(Instance, Instance) - 接口中的方法 weka.core.DistanceFunction
-
Calculates the distance between two instances.
- distance(Instance, Instance) - 类中的方法 weka.core.EuclideanDistance
-
Calculates the distance between two instances.
- distance(Instance, Instance) - 类中的方法 weka.core.NormalizableDistance
-
Calculates the distance between two instances.
- distance(Instance, Instance, double) - 接口中的方法 weka.core.DistanceFunction
-
Calculates the distance between two instances.
- distance(Instance, Instance, double) - 类中的方法 weka.core.NormalizableDistance
-
Calculates the distance between two instances.
- distance(Instance, Instance, double, PerformanceStats) - 类中的方法 weka.core.AbstractStringDistanceFunction
-
Calculates the distance between two instances.
- distance(Instance, Instance, double, PerformanceStats) - 接口中的方法 weka.core.DistanceFunction
-
Calculates the distance between two instances.
- distance(Instance, Instance, double, PerformanceStats) - 类中的方法 weka.core.NormalizableDistance
-
Calculates the distance between two instances.
- distance(Instance, Instance, PerformanceStats) - 接口中的方法 weka.core.DistanceFunction
-
Calculates the distance between two instances.
- distance(Instance, Instance, PerformanceStats) - 类中的方法 weka.core.EuclideanDistance
-
Calculates the distance (or similarity) between two instances.
- distance(Instance, Instance, PerformanceStats) - 类中的方法 weka.core.NormalizableDistance
-
Calculates the distance between two instances.
- distanceFTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- DistanceFunction - weka.core中的接口
-
Interface for any class that can compute and return distances between two instances.
- distanceFunctionTipText() - 类中的方法 weka.clusterers.HierarchicalClusterer
- distanceFunctionTipText() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns the tip text for this property.
- distanceFunctionTipText() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns the tip text for this property.
- distanceIsBranchLengthTipText() - 类中的方法 weka.clusterers.HierarchicalClusterer
- distanceSet(Instance, Instance) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Calculates the distance between two instances
- distanceWeightingTipText() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the tip text for this property.
- distinctCount - 类中的变量 weka.core.AttributeStats
-
The number of distinct values
- distMultTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- distributedExperimentSelected() - 类中的方法 weka.gui.experiment.DistributeExperimentPanel
-
Returns true if the distribute experiment checkbox is selected
- DistributeExperimentPanel - weka.gui.experiment中的类
-
This panel enables an experiment to be distributed to multiple hosts; it also allows remote host names to be specified.
- DistributeExperimentPanel() - 类的构造器 weka.gui.experiment.DistributeExperimentPanel
-
Constructor
- DistributeExperimentPanel(Experiment) - 类的构造器 weka.gui.experiment.DistributeExperimentPanel
-
Creates the panel with the supplied initial experiment.
- distribution() - 类中的方法 weka.classifiers.evaluation.NominalPrediction
-
Gets the predicted probabilities
- distribution() - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Returns the distribution of class values induced by the model.
- Distribution - weka.classifiers.trees.j48中的类
-
Class for handling a distribution of class values.
- Distribution(double[][]) - 类的构造器 weka.classifiers.trees.j48.Distribution
-
Creates and initializes a new distribution using the given array.
- Distribution(int, int) - 类的构造器 weka.classifiers.trees.j48.Distribution
-
Creates and initializes a new distribution.
- Distribution(Distribution) - 类的构造器 weka.classifiers.trees.j48.Distribution
-
Creates distribution with only one bag by merging all bags of given distribution.
- Distribution(Distribution, int) - 类的构造器 weka.classifiers.trees.j48.Distribution
-
Creates distribution with two bags by merging all bags apart of the indicated one.
- Distribution(Instances) - 类的构造器 weka.classifiers.trees.j48.Distribution
-
Creates a distribution with only one bag according to instances in source.
- Distribution(Instances, ClassifierSplitModel) - 类的构造器 weka.classifiers.trees.j48.Distribution
-
Creates a distribution according to given instances and split model.
- distributionForInstance(BayesNet, Instance) - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(BayesNet, Instance) - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(BayesNet, Instance) - 类中的方法 weka.classifiers.bayes.net.estimate.SimpleEstimator
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.AODE
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.DMNBtext.DNBBinary
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.HNB
-
Calculates the class membership probabilities for the given test instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.NaiveBayesSimple
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.bayes.WAODE
-
Calculates the class membership probabilities for the given test instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.Classifier
-
Predicts the class memberships for a given instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Computes the distribution for a given instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.LibSVM
-
Computes the distribution for a given instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.Logistic
-
Computes the distribution for a given instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
Call this function to predict the class of an instance once a classification model has been built with the buildClassifier call.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Computes the distribution for a given instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns class probabilities for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.SMO
-
Estimates class probabilities for given instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.SPegasos
-
Computes the distribution for a given instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Outputs the distribution for the given output.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.lazy.IBk
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.lazy.KStar
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.lazy.LBR
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.lazy.LWL
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Classifies a given instance after attribute selection
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.Bagging
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.ClassificationViaRegression
-
Returns the distribution for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Returns class probabilities.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Predicts the class distribution for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.Dagging
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.Decorate
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.END
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Classifies a given instance after filtering.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.Grading
-
Returns class probabilities for a given instance using the stacked classifier.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.GridSearch
-
Computes the distribution for a given instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.MetaCost
-
Classifies a given instance after filtering.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Returns the distribution for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.MultiScheme
-
Returns class probabilities.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Predicts the class distribution for a given instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Predicts the class distribution for a given instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
-
Predicts the class distribution for a given instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Returns the distribution for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Computes class distribution of an instance using the best committee.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.RandomCommittee
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.RotationForest
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.Stacking
-
Returns class probabilities.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.StackingC
-
Classifies a given instance using the stacked classifier.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.meta.Vote
-
Classifies a given instance using the selected combination rule.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MDD
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MIBoost
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MIDD
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MIEMDD
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MILR
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Computes the distribution for a given multiple instance
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MISMO
-
Estimates class probabilities for given instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MISVM
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.MIWrapper
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.mi.SimpleMI
-
Computes the distribution for a given exemplar
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.misc.HyperPipes
-
Classifies the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.misc.VFI
-
Classifies the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.pmml.consumer.GeneralRegression
-
Classifies the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.pmml.consumer.NeuralNetwork
-
Classifies the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.pmml.consumer.Regression
-
Classifies the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Computes class distribution for the given instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.rules.DTNB
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.rules.JRip
-
Classify the test instance with the rule learner and provide the class distributions
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Returns class probabilities for a weighted instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.rules.PART
-
Returns class probabilities for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.rules.part.MakeDecList
-
Returns the class distribution for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.rules.ZeroR
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.ADTree
-
Returns the class probability distribution for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.BFTree
-
Computes class probabilities for instance using the decision tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.DecisionStump
-
Calculates the class membership probabilities for the given test instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.FT
-
Returns class probabilities for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.ft.FTInnerNode
-
Returns the class probabilities for an instance given by the Functional tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.ft.FTLeavesNode
-
Returns the class probabilities for an instance given by the Functional Leaves tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.ft.FTNode
-
Returns the class probabilities for an instance given by the Functional Tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns the class probabilities for an instance given by the Functional tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.Id3
-
Computes class distribution for instance using decision tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.J48
-
Returns class probabilities for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.J48graft
-
Returns class probabilities for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.LADTree
-
Returns the class probability distribution for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.LMT
-
Returns class probabilities for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns the class probabilities for an instance given by the logistic model tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Returns class probabilities for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.NBTree
-
Returns class probabilities for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns the class probability distribution for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.RandomTree
-
Computes class distribution of an instance using the tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.REPTree
-
Computes class distribution of an instance using the tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Computes class probabilities for instance using the decision tree.
- distributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.UserClassifier
-
Call this function to get a double array filled with the probability of how likely each class type is the class of the instance.
- distributionForInstance(Instance) - 类中的方法 weka.clusterers.AbstractClusterer
-
Predicts the cluster memberships for a given instance.
- distributionForInstance(Instance) - 类中的方法 weka.clusterers.AbstractDensityBasedClusterer
-
Returns the cluster probability distribution for an instance.
- distributionForInstance(Instance) - 接口中的方法 weka.clusterers.Clusterer
-
Predicts the cluster memberships for a given instance.
- distributionForInstance(Instance) - 接口中的方法 weka.clusterers.DensityBasedClusterer
-
Returns the cluster probability distribution for an instance.
- distributionForInstance(Instance) - 类中的方法 weka.clusterers.FilteredClusterer
-
Classifies a given instance after filtering.
- distributionForInstance(Instance) - 类中的方法 weka.clusterers.HierarchicalClusterer
- distributionForInstance(Instance, boolean) - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns class probabilities for a weighted instance.
- distributionsByOriginalIndex(double[]) - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Convert the given class distribution back to the distributions with the original internal class index
- distributionSpreadTipText() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns the tip text for this property
- distributionTipText() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns the tip text for this property
- divergence(BayesNet) - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
calculates the divergence between the probability distribution represented by this network and that of another, that is, \sum_{x\in X} P(x)log P(x)/Q(x) where X is the set of values the nodes in the network can take, P(x) the probability of this network for configuration x Q(x) the probability of the other network for configuration x
- divide(Instances, boolean) - 类中的静态方法 weka.associations.LabeledItemSet
-
Splits the class attribute away.
- dividedBy(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Divided by another DoubleVector element by element
- dividedByEquals(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Divided by another DoubleVector element by element in place
- DIVISION - 接口中的静态变量 weka.core.mathematicalexpression.sym
- DIVISION - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- DKConditionalEstimator - weka.estimators中的类
-
Conditional probability estimator for a discrete domain conditional upon a numeric domain.
- DKConditionalEstimator(int, double) - 类的构造器 weka.estimators.DKConditionalEstimator
-
Constructor
- dl(int) - 类中的方法 weka.core.Debug.DBO
-
Return true if the debug level is set same method as outpuTypeSet but better name
- DMNBtext - weka.classifiers.bayes中的类
-
Class for building and using a Discriminative Multinomial Naive Bayes classifier.
- DMNBtext() - 类的构造器 weka.classifiers.bayes.DMNBtext
- DMNBtext.DNBBinary - weka.classifiers.bayes中的类
- DNBBinary() - 类的构造器 weka.classifiers.bayes.DMNBtext.DNBBinary
- DNConditionalEstimator - weka.estimators中的类
-
Conditional probability estimator for a discrete domain conditional upon a numeric domain.
- DNConditionalEstimator(int, double) - 类的构造器 weka.estimators.DNConditionalEstimator
-
Constructor
- dnorm(double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the density of the standard normal.
- dnorm(double, double, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the density value of a standard normal.
- dnorm(double, DoubleVector, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the density values of a set of normal distributions with different means.
- dnormLog(double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the log-density of the standard normal.
- dnormLog(double, double, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the log-density value of a standard normal.
- dnormLog(double, DoubleVector, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the log-density values of a set of normal distributions with different means.
- do_action(int, lr_parser, Stack, int) - 类中的方法 weka.core.mathematicalexpression.Parser
-
Invoke a user supplied parse action.
- do_action(int, lr_parser, Stack, int) - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Invoke a user supplied parse action.
- doCommandlineCompletion(KeyEvent) - 类中的方法 weka.gui.SimpleCLIPanel
-
performs commandline completion on packages and classnames.
- DOCTYPE - 类中的静态变量 weka.core.xml.XMLInstances
-
the DTD
- DOCTYPE - 类中的静态变量 weka.core.xml.XMLOptions
-
the DTD for the XML file.
- DOCTYPE - 类中的静态变量 weka.core.xml.XMLSerialization
-
the DOCTYPE for the serialization
- doGrafting(Instances) - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Initializes variables for grafting.
- doHistory(KeyEvent) - 类中的方法 weka.gui.SimpleCLIPanel
-
Changes the currently displayed command line when certain keys are pressed.
- doMetaConnection(BeanInstance, BeanInstance, EventSetDescriptor, JComponent) - 类中的静态方法 weka.gui.beans.BeanConnection
- done() - 接口中的方法 weka.classifiers.IterativeClassifier
-
Signal end of iterating, useful for any house-keeping/cleanup
- done() - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Signal that a scoring run has been completed.
- done() - 类中的方法 weka.classifiers.trees.ADTree
-
Frees memory that is no longer needed for a final model - will no longer be able to increment the classifier after calling this.
- done() - 类中的方法 weka.classifiers.trees.LADTree
- doNotOperateOnPerClassBasisTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- doNotReplaceMissingValuesTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- doNotReplaceMissingValuesTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- doNotWeightBagsTipText() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Returns the tip text for this property
- dontFilterAfterFirstBatchTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the tip text for this property.
- dontNormalizeTipText() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns the tip text for this property
- dontNormalizeTipText() - 类中的方法 weka.core.NormalizableDistance
-
Returns the tip text for this property.
- dontReplaceMissingTipText() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns the tip text for this property
- dontReplaceMissingValuesTipText() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns the tip text for this property
- doRun(int) - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets the results for a specified run number.
- doRun(int) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets the results for a specified run number.
- doRun(int) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets the results for a specified run number.
- doRun(int) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets the results for a specified run number.
- doRun(int) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets the results for a specified run number.
- doRun(int) - 接口中的方法 weka.experiment.ResultProducer
-
Gets the results for a specified run number.
- doRunKeys(int) - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets the keys for a specified run number.
- doRunKeys(int) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets the keys for a specified run number.
- doRunKeys(int) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets the keys for a specified run number.
- doRunKeys(int) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets the keys for a specified run number.
- doRunKeys(int) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets the keys for a specified run number.
- doRunKeys(int) - 接口中的方法 weka.experiment.ResultProducer
-
Gets the keys for a specified run number.
- doTests() - 类中的方法 weka.associations.CheckAssociator
-
Begin the tests, reporting results to System.out
- doTests() - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Begin the tests, reporting results to System.out
- doTests() - 类中的方法 weka.classifiers.CheckClassifier
-
Begin the tests, reporting results to System.out
- doTests() - 类中的方法 weka.classifiers.functions.supportVector.CheckKernel
-
Begin the tests, reporting results to System.out
- doTests() - 类中的方法 weka.clusterers.CheckClusterer
-
Begin the tests, reporting results to System.out
- doTests() - 类中的方法 weka.core.Check
-
Begin the tests, reporting results to System.out
- doTests() - 类中的方法 weka.core.CheckGOE
-
Runs some diagnostic tests on the object.
- doTests() - 类中的方法 weka.core.CheckOptionHandler
-
Runs some diagnostic tests on an optionhandler object.
- doTests() - 类中的方法 weka.core.CheckScheme
-
Begin the tests, reporting results to System.out
- doTests() - 类中的方法 weka.estimators.CheckEstimator
-
Begin the tests, reporting results to System.out
- dotMultiply(AlgVector) - 类中的方法 weka.core.AlgVector
-
Returns the inner (or dot) product of two vectors
- DotParser - weka.gui.graphvisualizer中的类
-
This class parses input in DOT format, and builds the datastructures that are passed to it.
- DotParser(Reader, FastVector, FastVector) - 类的构造器 weka.gui.graphvisualizer.DotParser
-
Dot parser Constructor
- DOUBLE - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for DOUBLE used for reading experiment results.
- DOUBLE - 接口中的静态变量 weka.gui.graphvisualizer.GraphConstants
-
Types of Edges
- doubleToString(double, int) - 类中的静态方法 weka.core.Utils
-
Rounds a double and converts it into String.
- doubleToString(double, int, int) - 类中的静态方法 weka.core.Utils
-
Rounds a double and converts it into a formatted decimal-justified String.
- DoubleVector - weka.core.matrix中的类
-
A vector specialized on doubles.
- DoubleVector() - 类的构造器 weka.core.matrix.DoubleVector
-
Constructs a null vector.
- DoubleVector(double[]) - 类的构造器 weka.core.matrix.DoubleVector
-
Constructs a vector directly from a double array
- DoubleVector(int) - 类的构造器 weka.core.matrix.DoubleVector
-
Constructs an n-vector of zeros.
- DoubleVector(int, double) - 类的构造器 weka.core.matrix.DoubleVector
-
Constructs a constant n-vector.
- dp(int, String) - 类中的方法 weka.core.Debug.DBO
-
prints out text but only if debug level is set.
- dp(String) - 类中的方法 weka.core.Debug.DBO
-
prints out text if verbose is on.
- dpln(int, String) - 类中的方法 weka.core.Debug.DBO
-
prints out text + endofline but only if parameter debug type is set.
- dpln(String) - 类中的方法 weka.core.Debug.DBO
-
prints out text + endofline if verbose is on.
- draw(Shape) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- draw3DRect(int, int, int, int, boolean) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw an outlined rectangle with 3D effect in current pen color.
- Drawable - weka.core中的接口
-
Interface to something that can be drawn as a graph.
- drawArc(int, int, int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- drawBytes(byte[], int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
simply calls drawString(String,int,int)
- drawChars(char[], int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
simply calls drawString(String,int,int)
- drawGlyphVector(GlyphVector, float, float) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- drawHighlight(Graphics, int, int) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this function to draw the node highlighted.
- drawImage(BufferedImage, BufferedImageOp, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- drawImage(Image, int, int, int, int, int, int, int, int, Color, ImageObserver) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- drawImage(Image, int, int, int, int, int, int, int, int, ImageObserver) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
calls drawImage(Image,int,int,int,int,int,int,int,int,Color,ImageObserver) with Color.WHITE as background color
- drawImage(Image, int, int, int, int, Color, ImageObserver) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
PS see http://astronomy.swin.edu.au/~pbourke/geomformats/postscript/ Java http://show.docjava.com:8086/book/cgij/doc/ip/graphics/SimpleImageFrame.java.html
- drawImage(Image, int, int, int, int, ImageObserver) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
calls drawImage(Image,int,int,int,int,Color,ImageObserver) with the color WHITE as background
- drawImage(Image, int, int, Color, ImageObserver) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
calls drawImage(Image,int,int,int,int,Color,ImageObserver)
- drawImage(Image, int, int, ImageObserver) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
calls drawImage(Image,int,int,Color,ImageObserver) with Color.WHITE as background color
- drawImage(Image, AffineTransform, ImageObserver) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- drawInputLines(Graphics, int, int) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this function to draw the nodes input connections.
- drawLine(int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw a line in current pen color.
- drawNode(Graphics, int, int) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this function to draw the node.
- drawOutputLines(Graphics, int, int) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this function to draw the nodes output connections.
- drawOval(int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw an Oval outline in current pen color.
- drawPolygon(int[], int[], int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- drawPolyline(int[], int[], int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- drawRect(int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw an outlined rectangle in current pen color.
- drawRenderableImage(RenderableImage, AffineTransform) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- drawRenderedImage(RenderedImage, AffineTransform) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- drawRoundRect(int, int, int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- drawString(String, float, float) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- drawString(String, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw text in current pen color.
- drawString(AttributedCharacterIterator, float, float) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- drawString(AttributedCharacterIterator, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- DTD_ANY - 类中的静态变量 weka.core.xml.XMLDocument
-
the ANY placeholder.
- DTD_AT_LEAST_ONE - 类中的静态变量 weka.core.xml.XMLDocument
-
the at least one marker.
- DTD_ATTLIST - 类中的静态变量 weka.core.xml.XMLDocument
-
the AttList definition.
- DTD_CDATA - 类中的静态变量 weka.core.xml.XMLDocument
-
the CDATA placeholder.
- DTD_DOCTYPE - 类中的静态变量 weka.core.xml.XMLDocument
-
the DocType definition.
- DTD_ELEMENT - 类中的静态变量 weka.core.xml.XMLDocument
-
the Element definition.
- DTD_IMPLIED - 类中的静态变量 weka.core.xml.XMLDocument
-
the #IMPLIED placeholder.
- DTD_OPTIONAL - 类中的静态变量 weka.core.xml.XMLDocument
-
the optional marker.
- DTD_PCDATA - 类中的静态变量 weka.core.xml.XMLDocument
-
the #PCDATA placeholder.
- DTD_REQUIRED - 类中的静态变量 weka.core.xml.XMLDocument
-
the #REQUIRED placeholder.
- DTD_SEPARATOR - 类中的静态变量 weka.core.xml.XMLDocument
-
the option separator.
- DTD_ZERO_OR_MORE - 类中的静态变量 weka.core.xml.XMLDocument
-
the zero or more marker.
- DTNB - weka.classifiers.rules中的类
-
Class for building and using a decision table/naive bayes hybrid classifier.
- DTNB() - 类的构造器 weka.classifiers.rules.DTNB
- DUMMY_STRING_VAL - 类中的静态变量 weka.core.Attribute
-
Dummy first value for String attributes (useful for sparse instances)
- dumpDistribution() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Prints distribution.
- dumpLabel(int, Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Prints label for subset index of instances (eg class).
- dumpLabelG(int, Instances) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
Prints label for subset index of instances (eg class).
- dumpModel(Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Prints the split model.
E
- EAST_CONNECTOR - 类中的静态变量 weka.gui.beans.BeanVisual
- Edge - weka.gui.treevisualizer中的类
-
This class is used in conjunction with the Node class to form a tree structure.
- Edge(String, String, String) - 类的构造器 weka.gui.treevisualizer.Edge
-
This constructs an Edge with the specified label and parent , child serial tags.
- edit() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
edits the current instances object in the viewer
- EditableBayesNet - weka.classifiers.bayes.net中的类
-
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. - EditableBayesNet() - 类的构造器 weka.classifiers.bayes.net.EditableBayesNet
-
standard constructor *
- EditableBayesNet(boolean) - 类的构造器 weka.classifiers.bayes.net.EditableBayesNet
-
constructor that potentially initializes instances as well
- EditableBayesNet(BIFReader) - 类的构造器 weka.classifiers.bayes.net.EditableBayesNet
-
constructor, copies Bayesian network structure from a Bayesian network encapsulated in a BIFReader
- EditableBayesNet(Instances) - 类的构造器 weka.classifiers.bayes.net.EditableBayesNet
-
constructor, creates empty network with nodes based on the attributes in a data set
- editableProperties() - 类中的方法 weka.gui.PropertySheetPanel
-
Gets the number of editable properties for the current target.
- EditDistance - weka.core中的类
-
Computes the Levenshtein edit distance between two strings.
- EditDistance() - 类的构造器 weka.core.EditDistance
- EditDistance(Instances) - 类的构造器 weka.core.EditDistance
- EDITION - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The edition of a book---for example, ``Second''.
- EDITOR - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
Name(s) of editor(s), typed as indicated in the LaTeX book.
- eig() - 类中的方法 weka.core.matrix.Matrix
-
Eigenvalue Decomposition
- eigenvalueDecomposition(double[][], double[]) - 类中的方法 weka.core.Matrix
-
已过时。Performs Eigenvalue Decomposition using Householder QR Factorization Matrix must be symmetrical.
- EigenvalueDecomposition - weka.core.matrix中的类
-
Eigenvalues and eigenvectors of a real matrix.
- EigenvalueDecomposition(Matrix) - 类的构造器 weka.core.matrix.EigenvalueDecomposition
-
Check for symmetry, then construct the eigenvalue decomposition
- element(int) - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Returns the ith element in the stack.
- Element - weka.associations.gsp中的类
-
Class representing an Element, i.e., a set of events/items.
- Element() - 类的构造器 weka.associations.gsp.Element
-
Constructor
- Element(int) - 类的构造器 weka.associations.gsp.Element
-
Constructor accepting an initial size of the events Array as parameter.
- elementAt(int) - 类中的方法 weka.core.FastVector
-
Returns the element at the given position.
- elementAt(int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Returns the component at the specified index.
- elements - 类中的变量 weka.core.neighboursearch.covertrees.Stack
-
The elements inside the stack.
- elements() - 类中的方法 weka.core.FastVector
-
Returns an enumeration of this vector.
- elements() - 类中的方法 weka.core.Stopwords
-
Returns a sorted enumeration over all stored stopwords
- elements(int) - 类中的方法 weka.core.FastVector
-
Returns an enumeration of this vector, skipping the element with the given index.
- eliminateColinearAttributesTipText() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns the tip text for this property
- EM - weka.clusterers中的类
-
Simple EM (expectation maximisation) class.
EM assigns a probability distribution to each instance which indicates the probability of it belonging to each of the clusters. - EM() - 类的构造器 weka.clusterers.EM
-
Constructor.
- empiricalBayesEstimate(double) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Returns the empirical Bayes estimate of a single value.
- empiricalBayesEstimate(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Returns the empirical Bayes estimate of a vector.
- empiricalProbability(DoubleVector, PaceMatrix) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Computes the empirical probabilities of the data over a set of intervals.
- empty() - 类中的方法 weka.core.Queue
-
Checks if queue is empty.
- EMPTY_NOMINAL_ATTRIBUTES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle empty nominal attributes
- EMPTY_NOMINAL_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle empty nominal classes
- enable(Capabilities.Capability) - 类中的方法 weka.core.Capabilities
-
enables the given capability.
- enable(Capabilities.Capability) - 类中的方法 weka.core.FindWithCapabilities
-
enables the given capability.
- enableAll() - 类中的方法 weka.core.Capabilities
-
enables all attribute and class types (including dependencies)
- enableAllAttributeDependencies() - 类中的方法 weka.core.Capabilities
-
enables all attribute type dependencies
- enableAllAttributes() - 类中的方法 weka.core.Capabilities
-
enables all attribute types
- enableAllClassDependencies() - 类中的方法 weka.core.Capabilities
-
enables all class type dependencies
- enableAllClasses() - 类中的方法 weka.core.Capabilities
-
enables all class types
- enableDependency(Capabilities.Capability) - 类中的方法 weka.core.Capabilities
-
enables the dependency flag for the given capability Enabling NOMINAL_ATTRIBUTES also enables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
- enableNot(Capabilities.Capability) - 类中的方法 weka.core.FindWithCapabilities
-
enables the given "not to have" capability.
- enclosureCharactersTipText() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the tip text for this property.
- END - weka.classifiers.meta中的类
-
A meta classifier for handling multi-class datasets with 2-class classifiers by building an ensemble of nested dichotomies.
For more info, check
Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. - END() - 类的构造器 weka.classifiers.meta.END
-
Constructor.
- entropicAutoBlendTipText() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns the tip text for this property
- entropy(double[]) - 类中的静态方法 weka.core.ContingencyTables
-
Computes the entropy of the given array.
- ENTROPY - 接口中的静态变量 weka.classifiers.bayes.net.search.local.Scoreable
- EntropyBasedSplitCrit - weka.classifiers.trees.j48中的类
-
"Abstract" class for computing splitting criteria based on the entropy of a class distribution.
- EntropyBasedSplitCrit() - 类的构造器 weka.classifiers.trees.j48.EntropyBasedSplitCrit
- entropyConditionedOnColumns(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Computes conditional entropy of the rows given the columns.
- entropyConditionedOnRows(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Computes conditional entropy of the columns given the rows.
- entropyConditionedOnRows(double[][], double[][], double) - 类中的静态方法 weka.core.ContingencyTables
-
Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix.
- entropyGain() - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Computes entropy gain for current split.
- entropyOverColumns(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Computes the columns' entropy for the given contingency table.
- entropyOverRows(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Computes the rows' entropy for the given contingency table.
- EntropySplitCrit - weka.classifiers.trees.j48中的类
-
Class for computing the entropy for a given distribution.
- EntropySplitCrit() - 类的构造器 weka.classifiers.trees.j48.EntropySplitCrit
- enumerateAttributes() - 类中的方法 weka.core.Instance
-
Returns an enumeration of all the attributes.
- enumerateAttributes() - 类中的方法 weka.core.Instances
-
Returns an enumeration of all the attributes.
- enumerateInstances() - 类中的方法 weka.core.Instances
-
Returns an enumeration of all instances in the dataset.
- enumerateLiterals() - 类中的方法 weka.associations.tertius.LiteralSet
-
Enumerate the literals contained in this set.
- enumerateMeasures() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns an enumeration of the measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns an enumeration of the measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns an enumeration of the additional measure names produced by the neighbour search algorithm, plus the chosen K in case cross-validation is enabled.
- enumerateMeasures() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns an enumeration of the additional measure names produced by the neighbour search algorithm.
- enumerateMeasures() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.meta.Bagging
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns an enumeration of the measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.rules.DTNB
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.rules.JRip
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.rules.PART
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.BFTree
-
Return an enumeration of the measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.FT
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.J48
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.LMT
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns an enumeration of the additional measure names
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Return an enumeration of the measure names.
- enumerateMeasures() - 接口中的方法 weka.core.AdditionalMeasureProducer
-
Returns an enumeration of the measure names.
- enumerateMeasures() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns an enumeration of the additional measure names.
- enumerateMeasures() - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns an enumeration of any additional measure names that might be in the result producer
- enumerateMeasures() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Returns an enumeration of any additional measure names that might be in the classifier
- enumerateMeasures() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns an enumeration of any additional measure names that might be in the SplitEvaluator
- enumerateMeasures() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Returns an enumeration of any additional measure names that might be in the result producer
- enumerateMeasures() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Returns an enumeration of any additional measure names that might be in the classifier
- enumerateMeasures() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns an enumeration of any additional measure names that might be in the result producer
- enumerateMeasures() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns an enumeration of any additional measure names that might be in the SplitEvaluator
- enumerateMeasures() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Returns an enumeration of any additional measure names that might be in the classifier
- enumerateRequests() - 类中的方法 weka.gui.beans.Associator
-
Return an enumeration of requests that can be made by the user
- enumerateRequests() - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Return an enumeration of actions that the user can ask this bean to perform
- enumerateRequests() - 类中的方法 weka.gui.beans.Classifier
-
Return an enumeration of requests that can be made by the user
- enumerateRequests() - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Return an enumeration of user activated requests for this bean
- enumerateRequests() - 类中的方法 weka.gui.beans.Clusterer
-
Return an enumeration of requests that can be made by the user
- enumerateRequests() - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Return an enumeration of user activated requests for this bean
- enumerateRequests() - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- enumerateRequests() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Return an enumeration of user requests
- enumerateRequests() - 类中的方法 weka.gui.beans.DataVisualizer
-
Describe
enumerateRequests
method here. - enumerateRequests() - 类中的方法 weka.gui.beans.Filter
-
Return an enumeration of user requests
- enumerateRequests() - 类中的方法 weka.gui.beans.GraphViewer
-
Return an enumeration of user requests
- enumerateRequests() - 类中的方法 weka.gui.beans.MetaBean
-
Return an enumeration of requests that can be made by the user
- enumerateRequests() - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Describe
enumerateRequests
method here. - enumerateRequests() - 类中的方法 weka.gui.beans.StripChart
-
Describe
enumerateRequests
method here. - enumerateRequests() - 类中的方法 weka.gui.beans.TextViewer
-
Get a list of user requests
- enumerateRequests() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Get list of user requests
- enumerateRequests() - 接口中的方法 weka.gui.beans.UserRequestAcceptor
-
Get a list of performable requests
- enumerateValues() - 类中的方法 weka.core.Attribute
-
Returns an enumeration of all the attribute's values if the attribute is nominal, string, or relation-valued, null otherwise.
- Environment - weka.core中的类
-
This class encapsulates a map of all environment and java system properties.
- Environment() - 类的构造器 weka.core.Environment
- EnvironmentHandler - weka.core中的接口
-
Interface for something that can utilize environment variables.
- EOF - 接口中的静态变量 weka.core.mathematicalexpression.sym
- EOF - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- EOF_sym() - 类中的方法 weka.core.mathematicalexpression.Parser
-
EOF
Symbol index. - EOF_sym() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
EOF
Symbol index. - epochsTipText() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns the tip text for this property
- EPSILON - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- epsilonParameterTipText() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns a tip text for this property suitable for display in the GUI
- epsilonParameterTipText() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Returns the tip text for this property
- EpsilonRange_ListElement - weka.clusterers.forOPTICSAndDBScan.Utils中的类
-
EpsilonRange_ListElement.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Sep 7, 2004
Time: 2:12:34 PM
$ Revision 1.4 $ - EpsilonRange_ListElement(double, DataObject) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.Utils.EpsilonRange_ListElement
-
Constructs a new Element that is stored in the ArrayList which is built in the k_nextNeighbourQuery-method from a specified database.
- epsilonRangeQuery(double, DataObject) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Performs an epsilon range query for this dataObject
- epsilonRangeQuery(double, DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Performs an epsilon range query for this dataObject
- epsilonTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- epsilonTipText() - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Returns the tip text for this property
- epsilonTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- epsilonTipText() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the tip text for this property
- epsilonTipText() - 类中的方法 weka.clusterers.OPTICS
-
Returns the tip text for this property
- epsTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- epsTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- eq(double, double) - 类中的静态方法 weka.core.Utils
-
Tests if a is equal to b.
- EQ - 接口中的静态变量 weka.core.mathematicalexpression.sym
- EQ - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- equalCondset(Object) - 类中的方法 weka.associations.LabeledItemSet
-
Compares two item sets
- equalExemplars(Instance, Instance) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Wether the instances of two exemplars are or are not equal
- equalHeaders(Instance) - 类中的方法 weka.core.Instance
-
Tests if the headers of two instances are equivalent.
- equalHeaders(Instances) - 类中的方法 weka.core.Instances
-
Checks if two headers are equivalent.
- equals(Object) - 类中的方法 weka.associations.AssociatorEvaluation
-
Tests whether the current evaluation object is equal to another evaluation object
- equals(Object) - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Return true if this rule is equal to the supplied one.
- equals(Object) - 类中的方法 weka.associations.FPGrowth.BinaryItem
- equals(Object) - 类中的方法 weka.associations.gsp.Element
-
Checks if two Elements are equal.
- equals(Object) - 类中的方法 weka.associations.gsp.Sequence
-
Checks if two Sequences are equal.
- equals(Object) - 类中的方法 weka.associations.ItemSet
-
Tests if two item sets are equal.
- equals(Object) - 类中的方法 weka.associations.LabeledItemSet
-
Tests if two item sets are equal.
- equals(Object) - 类中的方法 weka.associations.RuleItem
-
returns whether two RuleItems are equal
- equals(Object) - 类中的方法 weka.attributeSelection.ConsistencySubsetEval.hashKey
-
Tests if two instances are equal
- equals(Object) - 类中的方法 weka.classifiers.Evaluation
-
Tests whether the current evaluation object is equal to another evaluation object
- equals(Object) - 类中的方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
Tests whether the current evaluation object is equal to another evaluation object
- equals(Object) - 类中的方法 weka.classifiers.rules.DecisionTableHashKey
-
Tests if two instances are equal
- equals(Object) - 类中的方法 weka.clusterers.ClusterEvaluation
-
Tests whether the current evaluation object is equal to another evaluation object
- equals(Object) - 类中的方法 weka.core.Attribute
-
Tests if given attribute is equal to this attribute.
- equals(Object) - 类中的方法 weka.core.AttributeLocator
-
Indicates whether some other object is "equal to" this one.
- equals(Object) - 类中的方法 weka.core.ClassDiscovery.StringCompare
-
Indicates whether some other object is "equal to" this Comparator.
- equals(Object) - 类中的方法 weka.core.SelectedTag
-
Returns true if this SelectedTag equals another object
- equals(Object) - 类中的方法 weka.core.SerializedObject
- equals(Object) - 类中的方法 weka.core.Trie
-
Compares the specified object with this collection for equality.
- equals(Object) - 类中的方法 weka.core.Trie.TrieNode
-
Indicates whether some other object is "equal to" this one.
- equals(Object) - 类中的方法 weka.core.Version
-
whether the given version string is equal to this version
- equals(Object) - 类中的方法 weka.estimators.Estimator
-
Tests whether the current estimation object is equal to another estimation object
- equals(Object) - 类中的方法 weka.gui.graphvisualizer.GraphEdge
- equals(Object) - 类中的方法 weka.gui.graphvisualizer.GraphNode
-
Returns true if passed in argument is an instance of GraphNode and is equal to this node.
- equals(Object) - 类中的方法 weka.gui.SortedTableModel.SortContainer
-
Indicates whether some other object is "equal to" this one.
- equals(DataObject) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Compares two DataObjects in respect to their attribute-values
- equals(DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Compares two DataObjects in respect to their attribute-values
- equals(DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Compares two DataObjects in respect to their attribute-values
- equalTo(Splitter) - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Tests whether two splitters are equivalent.
- equalTo(Splitter) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Tests whether two splitters are equivalent.
- equalTo(Splitter) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Tests whether two splitters are equivalent.
- equalTo(Test) - 类中的方法 weka.datagenerators.Test
-
Compares the test with the test that is given as parameter.
- equivalentTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- equivalentTo(Rule) - 类中的方法 weka.associations.tertius.Rule
-
Test if this rule is equivalent to another rule.
- errms(StreamTokenizer, String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
Throws error message with line number and last token read.
- error - 接口中的静态变量 weka.core.mathematicalexpression.sym
- error - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- error() - 类中的方法 weka.classifiers.evaluation.NumericPrediction
-
Calculates the prediction error.
- ERROR_SHAPE - 类中的静态变量 weka.gui.visualize.Plot2D
- error_sym() - 类中的方法 weka.core.mathematicalexpression.Parser
-
error
Symbol index. - error_sym() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
error
Symbol index. - ErrorBasedMeritEvaluator - weka.attributeSelection中的接口
-
Interface for evaluators that calculate the "merit" of attributes/subsets as the error of a learning scheme
- errorFunction(double) - 类中的静态方法 weka.core.Statistics
-
Returns the error function of the normal distribution.
- errorFunctionComplemented(double) - 类中的静态方法 weka.core.Statistics
-
Returns the complementary Error function of the normal distribution.
- errorOnProbabilitiesTipText() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the tip text for this property
- errorOnProbabilitiesTipText() - 类中的方法 weka.classifiers.trees.FT
-
Returns the tip text for this property
- errorOnProbabilitiesTipText() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the tip text for this property
- errorRate() - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Returns the estimated error rate.
- errorRate() - 类中的方法 weka.classifiers.Evaluation
-
Returns the estimated error rate or the root mean squared error (if the class is numeric).
- errorValue(boolean) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this to get the error value of this unit.
- errorValue(boolean) - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Call this to get the error value of this unit.
- errorValue(NeuralNode) - 类中的方法 weka.classifiers.functions.neural.LinearUnit
-
This function calculates what the error value should be.
- errorValue(NeuralNode) - 接口中的方法 weka.classifiers.functions.neural.NeuralMethod
-
This function calculates what the error value should be.
- errorValue(NeuralNode) - 类中的方法 weka.classifiers.functions.neural.SigmoidUnit
-
This function calculates what the error value should be.
- ErrorVisualizePlugin - weka.gui.visualize.plugins中的接口
-
Interface implemented by classes loaded dynamically to visualize classifier errors in the explorer.
- estimateCPTs() - 类中的方法 weka.classifiers.bayes.BayesNet
-
estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
- estimateCPTs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
- estimateCPTs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
- estimateCPTs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
- estimateCPTs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.estimate.SimpleEstimator
-
estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
- estimatePrior() - 类中的方法 weka.associations.PriorEstimation
-
Method to estimate the prior probabilities
- Estimator - weka.estimators中的类
-
Abstract class for all estimators.
- Estimator() - 类的构造器 weka.estimators.Estimator
- estimatorTipText() - 类中的方法 weka.classifiers.bayes.BayesNet
-
This will return a string describing the BayesNetEstimator.
- estimatorTipText() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns the tip text for this property
- EstimatorUtils - weka.estimators中的类
-
Contains static utility functions for Estimators.
- EstimatorUtils() - 类的构造器 weka.estimators.EstimatorUtils
- EstTypes() - 类的构造器 weka.estimators.CheckEstimator.EstTypes
-
Constructor
- EstTypes(boolean, boolean, boolean) - 类的构造器 weka.estimators.CheckEstimator.EstTypes
-
Constructor
- EuclideanDataObject - weka.clusterers.forOPTICSAndDBScan.DataObjects中的类
-
EuclideanDataObject.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 19, 2004
Time: 5:50:22 PM
$ Revision 1.4 $ - EuclideanDataObject(Instance, String, Database) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Constructs a new DataObject.
- EuclideanDistance - weka.core中的类
-
Implementing Euclidean distance (or similarity) function.
One object defines not one distance but the data model in which the distances between objects of that data model can be computed.
Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.
For more information, see:
Wikipedia. - EuclideanDistance() - 类的构造器 weka.core.EuclideanDistance
-
Constructs an Euclidean Distance object, Instances must be still set.
- EuclideanDistance(Instances) - 类的构造器 weka.core.EuclideanDistance
-
Constructs an Euclidean Distance object and automatically initializes the ranges.
- eval(int, int, Instance) - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Implements the abstract function of Kernel using the cache.
- eval(int, int, Instance) - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Computes the result of the kernel function for two instances.
- eval(int, int, Instance) - 类中的方法 weka.classifiers.functions.supportVector.NormalizedPolyKernel
-
Computes the result of the kernel function for two instances.
- eval(int, int, Instance) - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
- eval(int, int, Instance) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Computes the result of the kernel function for two instances.
- EVAL_ACCURACY - 类中的静态变量 weka.classifiers.rules.DecisionTable
- EVAL_AUC - 类中的静态变量 weka.classifiers.rules.DecisionTable
- EVAL_CROSS_VALIDATION - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
n-fold cross-validation
- EVAL_DEFAULT - 类中的静态变量 weka.classifiers.rules.DecisionTable
-
default is accuracy for discrete class and RMSE for numeric class
- EVAL_MAE - 类中的静态变量 weka.classifiers.rules.DecisionTable
- EVAL_RMSE - 类中的静态变量 weka.classifiers.rules.DecisionTable
- EVAL_TRAINING_SET - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
entire training set
- EVAL_TUNED_SPLIT - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
single tuned fold
- evalBoolean(String) - 类中的方法 weka.core.xml.XMLDocument
-
Evaluates and returns the boolean result of the XPath expression.
- evalDouble(String) - 类中的方法 weka.core.xml.XMLDocument
-
Evaluates and returns the double result of the XPath expression.
- evalString(String) - 类中的方法 weka.core.xml.XMLDocument
-
Evaluates and returns the boolean result of the XPath expression.
- evaluate(String, String[]) - 类中的静态方法 weka.associations.AssociatorEvaluation
-
Evaluates an associator with the options given in an array of strings.
- evaluate(String, String[]) - 类中的静态方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
Evaluates a kernel with the options given in an array of strings.
- evaluate(String, HashMap) - 类中的静态方法 weka.core.MathematicalExpression
-
Parses and evaluates the given expression.
- evaluate(Associator, String[]) - 类中的静态方法 weka.associations.AssociatorEvaluation
-
Evaluates the associator with the given commandline options and returns the evaluation string.
- evaluate(Associator, Instances) - 类中的方法 weka.associations.AssociatorEvaluation
-
Evaluates the associator with the given commandline options and returns the evaluation string.
- evaluate(Kernel, String[]) - 类中的静态方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
Evaluates the Kernel with the given commandline options and returns the evaluation string.
- evaluate(Kernel, Instances) - 类中的方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
Evaluates the Kernel with the given commandline options and returns the evaluation string.
- evaluateAttribute(int) - 接口中的方法 weka.attributeSelection.AttributeEvaluator
-
evaluates an individual attribute
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.AttributeSetEvaluator
-
evaluates an individual attribute
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
evaluates an individual attribute by measuring its chi-squared value.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.CostSensitiveAttributeEval
-
Evaluates an individual attribute.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Evaluates an individual attribute by delegating to the base evaluator.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
evaluates an individual attribute by measuring the gain ratio of the class given the attribute.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Evaluates the merit of a transformed attribute.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Evaluates the merit of a transformed attribute.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Evaluates an individual attribute using ReliefF's instance based approach.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Evaluates an attribute by returning the rank of the square of its coefficient in a linear support vector machine.
- evaluateAttribute(int) - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
evaluates an individual attribute by measuring the symmetrical uncertainty between it and the class.
- evaluateAttribute(int[], int[]) - 类中的方法 weka.attributeSelection.AttributeSetEvaluator
-
Evaluates a set of attributes
- evaluateClusterer(Clusterer, String[]) - 类中的静态方法 weka.clusterers.ClusterEvaluation
-
Evaluates a clusterer with the options given in an array of strings.
- evaluateClusterer(Instances) - 类中的方法 weka.clusterers.ClusterEvaluation
-
Evaluate the clusterer on a set of instances.
- evaluateClusterer(Instances, String) - 类中的方法 weka.clusterers.ClusterEvaluation
-
Evaluate the clusterer on a set of instances.
- evaluateClusterer(Instances, String, boolean) - 类中的方法 weka.clusterers.ClusterEvaluation
-
Evaluate the clusterer on a set of instances.
- evaluateExpression(double[]) - 类中的方法 weka.core.AttributeExpression
-
Evaluate the expression using the supplied array of attribute values.
- evaluateExpression(Instance) - 类中的方法 weka.core.AttributeExpression
-
Evaluate the expression using the supplied Instance.
- evaluateModel(String, String[]) - 类中的静态方法 weka.classifiers.Evaluation
-
Evaluates a classifier with the options given in an array of strings.
- evaluateModel(Classifier, String[]) - 类中的静态方法 weka.classifiers.Evaluation
-
Evaluates a classifier with the options given in an array of strings.
- evaluateModel(Classifier, Instances, Object...) - 类中的方法 weka.classifiers.Evaluation
-
Evaluates the classifier on a given set of instances.
- evaluateModelOnce(double[], Instance) - 类中的方法 weka.classifiers.Evaluation
-
Evaluates the supplied distribution on a single instance.
- evaluateModelOnce(double, Instance) - 类中的方法 weka.classifiers.Evaluation
-
Evaluates the supplied prediction on a single instance.
- evaluateModelOnce(Classifier, Instance) - 类中的方法 weka.classifiers.Evaluation
-
Evaluates the classifier on a single instance.
- evaluateModelOnceAndRecordPrediction(double[], Instance) - 类中的方法 weka.classifiers.Evaluation
-
Evaluates the supplied distribution on a single instance.
- evaluateModelOnceAndRecordPrediction(Classifier, Instance) - 类中的方法 weka.classifiers.Evaluation
-
Evaluates the classifier on a single instance and records the prediction (if the class is nominal).
- evaluateSubset(BitSet) - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
evaluates a subset of attributes
- evaluateSubset(BitSet) - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Evaluates a subset of attributes
- evaluateSubset(BitSet) - 类中的方法 weka.attributeSelection.ConsistencySubsetEval
-
Evaluates a subset of attributes
- evaluateSubset(BitSet) - 类中的方法 weka.attributeSelection.CostSensitiveSubsetEval
-
Evaluates a subset of attributes.
- evaluateSubset(BitSet) - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
evaluates a subset of attributes
- evaluateSubset(BitSet) - 接口中的方法 weka.attributeSelection.SubsetEvaluator
-
evaluates a subset of attributes
- evaluateSubset(BitSet) - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Evaluates a subset of attributes
- evaluateSubset(BitSet, Instance, boolean) - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Evaluates a subset of attributes with respect to a single instance.
- evaluateSubset(BitSet, Instance, boolean) - 类中的方法 weka.attributeSelection.HoldOutSubsetEvaluator
-
Evaluates a subset of attributes with respect to a single instance.
- evaluateSubset(BitSet, Instances) - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Evaluates a subset of attributes with respect to a set of instances.
- evaluateSubset(BitSet, Instances) - 类中的方法 weka.attributeSelection.HoldOutSubsetEvaluator
-
Evaluates a subset of attributes with respect to a set of instances.
- Evaluation - weka.classifiers中的类
-
Class for evaluating machine learning models.
- Evaluation(Instances) - 类的构造器 weka.classifiers.Evaluation
-
Initializes all the counters for the evaluation.
- Evaluation(Instances, CostMatrix) - 类的构造器 weka.classifiers.Evaluation
-
Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
- EVALUATION_ACC - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation via: Accuracy
- EVALUATION_CC - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation via: Correlation coefficient
- EVALUATION_COMBINED - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation via: Combined = (1-CC) + RRSE + RAE
- EVALUATION_KAPPA - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation via: kappa statistic
- EVALUATION_MAE - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation via: Mean absolute error
- EVALUATION_RAE - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation via: Relative absolute error
- EVALUATION_RMSE - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation via: Root mean squared error
- EVALUATION_RRSE - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation via: Root relative squared error
- evaluationMeasureTipText() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns the tip text for this property
- evaluationModeTipText() - 类中的方法 weka.classifiers.meta.ThresholdSelector
- evaluationTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- EvaluationUtils - weka.classifiers.evaluation中的类
-
Contains utility functions for generating lists of predictions in various manners.
- EvaluationUtils() - 类的构造器 weka.classifiers.evaluation.EvaluationUtils
- evaluatorTipText() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Returns the tip text for this property
- evaluatorTipText() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns the tip text for this property
- evaluatorTipText() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Returns the tip text for this property
- evalUsingTrainingDataTipText() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns a string for this option suitable for display in the gui as a tip text
- EventConstraints - weka.gui.beans中的接口
-
Interface for objects that want to be able to specify at any given time whether their current configuration allows a particular event to be generated.
- eventGeneratable(EventSetDescriptor) - 类中的方法 weka.gui.beans.Associator
-
Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
- eventGeneratable(EventSetDescriptor) - 类中的方法 weka.gui.beans.Classifier
-
Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
- eventGeneratable(EventSetDescriptor) - 类中的方法 weka.gui.beans.Clusterer
-
Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
- eventGeneratable(EventSetDescriptor) - 类中的方法 weka.gui.beans.MetaBean
-
Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.Associator
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.ClassAssigner
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.Classifier
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.ClassValuePicker
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.Clusterer
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 接口中的方法 weka.gui.beans.EventConstraints
-
Returns true if, at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.Filter
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Returns true if, at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.Loader
-
Returns true if the named event can be generated at this time
- eventGeneratable(String) - 类中的方法 weka.gui.beans.MetaBean
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.PredictionAppender
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.TestSetMaker
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.TextViewer
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.TrainingSetMaker
-
Returns true, if at the current time, the named event could be generated.
- eventGeneratable(String) - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Returns true, if at the current time, the named event could be generated.
- exclusiveTipText() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns the tip text for this property
- execute() - 类中的方法 weka.classifiers.CheckSource
-
performs the comparison test
- execute() - 类中的方法 weka.experiment.RemoteExperimentSubTask
-
Run the experiment
- execute() - 接口中的方法 weka.experiment.Task
-
Execute this task.
- execute() - 类中的方法 weka.filters.CheckSource
-
performs the comparison test
- execute() - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Perform the sub task
- execute() - 类中的方法 weka.gui.explorer.DataGeneratorPanel
-
generates the instances, returns TRUE if successful
- execute() - 类中的方法 weka.gui.GenericPropertiesCreator
-
generates the props-file for the GenericObjectEditor and stores it
- execute() - 类中的方法 weka.gui.sql.QueryPanel
-
executes the current query.
- execute(boolean) - 类中的方法 weka.gui.GenericPropertiesCreator
-
generates the props-file for the GenericObjectEditor and stores it only if the the param
store
is TRUE. - execute(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Executes a SQL query.
- executeTask(Task) - 接口中的方法 weka.experiment.Compute
-
Execute a task
- executeTask(Task) - 类中的方法 weka.experiment.RemoteEngine
-
Takes a task object and queues it for execution
- ExhaustiveSearch - weka.attributeSelection中的类
-
ExhaustiveSearch :
Performs an exhaustive search through the space of attribute subsets starting from the empty set of attrubutes. - ExhaustiveSearch() - 类的构造器 weka.attributeSelection.ExhaustiveSearch
-
Constructor
- exists(TechnicalInformation.Field) - 类中的方法 weka.core.TechnicalInformation
-
returns TRUE if the field is stored and has a value different from the empty string.
- EXP - 接口中的静态变量 weka.core.mathematicalexpression.sym
- EXP - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- EXP_INDEX_TABLE - 类中的静态变量 weka.experiment.DatabaseUtils
-
The name of the table containing the index to experiments.
- EXP_RESULT_COL - 类中的静态变量 weka.experiment.DatabaseUtils
-
The name of the column containing the results table name.
- EXP_RESULT_PREFIX - 类中的静态变量 weka.experiment.DatabaseUtils
-
The prefix for result table names.
- EXP_SETUP_COL - 类中的静态变量 weka.experiment.DatabaseUtils
-
The name of the column containing the experiment setup (parameters).
- EXP_TYPE_COL - 类中的静态变量 weka.experiment.DatabaseUtils
-
The name of the column containing the experiment type (ResultProducer).
- expectation(double, int, double[], Hashtable) - 类中的静态方法 weka.associations.RuleGeneration
-
calculates the expected predctive accuracy of a rule
- expectedCosts(double[]) - 类中的方法 weka.classifiers.CostMatrix
-
Calculates the expected misclassification cost for each possible class value, given class probability estimates.
- expectedCosts(double[], Instance) - 类中的方法 weka.classifiers.CostMatrix
-
Calculates the expected misclassification cost for each possible class value, given class probability estimates.
- expectedResultsPerAverageTipText() - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns the tip text for this property
- Experiment - weka.experiment中的类
-
Holds all the necessary configuration information for a standard type experiment.
- Experiment() - 类的构造器 weka.experiment.Experiment
- Experimenter - weka.gui.experiment中的类
-
The main class for the experiment environment.
- Experimenter(boolean) - 类的构造器 weka.gui.experiment.Experimenter
-
Creates the experiment environment gui with no initial experiment
- ExperimenterDefaults - weka.gui.experiment中的类
-
This class offers get methods for the default Experimenter settings in the props file
weka/gui/experiment/Experimenter.props
. - ExperimenterDefaults() - 类的构造器 weka.gui.experiment.ExperimenterDefaults
- experimentIndexExists() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns true if the experiment index exists.
- EXPLICIT - 类中的静态变量 weka.associations.Tertius
-
Way of handling missing values: min counterinstances
- Explorer - weka.gui.explorer中的类
-
The main class for the Weka explorer.
- Explorer() - 类的构造器 weka.gui.explorer.Explorer
-
Creates the experiment environment gui with no initial experiment
- Explorer.CapabilitiesFilterChangeEvent - weka.gui.explorer中的类
-
This event can be fired in case the capabilities filter got changed
- Explorer.CapabilitiesFilterChangeListener - weka.gui.explorer中的接口
-
Interface for classes that listen for filter changes.
- Explorer.ExplorerPanel - weka.gui.explorer中的接口
-
A common interface for panels to be displayed in the Explorer
- Explorer.LogHandler - weka.gui.explorer中的接口
-
A common interface for panels in the explorer that can handle logs
- ExplorerDefaults - weka.gui.explorer中的类
-
This class offers get methods for the default Explorer settings in the props file
weka/gui/explorer/Explorer.props
. - ExplorerDefaults() - 类的构造器 weka.gui.explorer.ExplorerDefaults
- ExponentialFormat - weka.core.matrix中的类
- ExponentialFormat() - 类的构造器 weka.core.matrix.ExponentialFormat
- ExponentialFormat(int) - 类的构造器 weka.core.matrix.ExponentialFormat
- ExponentialFormat(int, boolean) - 类的构造器 weka.core.matrix.ExponentialFormat
- ExponentialFormat(int, int, boolean, boolean) - 类的构造器 weka.core.matrix.ExponentialFormat
- exponentTipText() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Returns the tip text for this property
- exponentTipText() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns the tip text for this property
- Expression - weka.core.pmml中的类
- Expression - weka.datagenerators.classifiers.regression中的类
-
A data generator for generating y according to a given expression out of randomly generated x.
E.g., the mexican hat can be generated like this:
sin(abs(a1)) / abs(a1)
In addition to this function, the amplitude can be changed and gaussian noise can be added. - Expression() - 类的构造器 weka.datagenerators.classifiers.regression.Expression
-
initializes the generator
- Expression(FieldMetaInfo.Optype, ArrayList<Attribute>) - 类的构造器 weka.core.pmml.Expression
- expressionTipText() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Returns the tip text for this property
- expressionTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Returns the tip text for this property
- expressionTipText() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Returns the tip text for this property
- expressionTipText() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Returns the tip text for this property.
- ExtensionFileFilter - weka.gui中的类
-
Provides a file filter for FileChoosers that accepts or rejects files based on their extension.
- ExtensionFileFilter(String[], String) - 类的构造器 weka.gui.ExtensionFileFilter
-
Creates an ExtensionFileFilter that accepts files that have any of the extensions contained in the supplied array.
- ExtensionFileFilter(String, String) - 类的构造器 weka.gui.ExtensionFileFilter
-
Creates the ExtensionFileFilter
- extraArcs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
Count nr of exta arcs from other network compared to current network Note that an arc is not 'extra' if it is reversed.
- extract(String) - 类中的静态方法 weka.core.RevisionUtils
-
Extracts the revision string.
- extract(RevisionHandler) - 类中的静态方法 weka.core.RevisionUtils
-
Extracts the revision string returned by the RevisionHandler.
- extractFilterAttributes(String) - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Parses a given String containing attribute numbers which are used for result filtering.
- extremeValuesAsOutliersTipText() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns the tip text for this property
- extremeValuesFactorTipText() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns the tip text for this property
F
- f(double) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Computes the value of f(x) given the mixture.
- f(double) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Computes the value of f(x) given the mixture.
- f(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Computes the value of f(x) given the mixture, where x is a vector.
- f(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Computes the value of f(x) given the mixture, where x is a vector.
- failed() - 类中的方法 weka.gui.sql.event.ConnectionEvent
-
whether an exception happened and is stored
- failed() - 类中的方法 weka.gui.sql.event.QueryExecuteEvent
-
is TRUE in case the exception is not NULL, i.e.
- FAILED - 类中的静态变量 weka.experiment.TaskStatusInfo
- FALLOUT_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: Fallout
- FALSE - 接口中的静态变量 weka.core.mathematicalexpression.sym
- FALSE - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- FALSE_NEG_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: False Negatives
- FALSE_POS_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: False Positives
- falseNegativeRate(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the false negative rate with respect to a particular class.
- falsePositiveRate(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the false positive rate with respect to a particular class.
- FarthestFirst - weka.clusterers中的类
-
Cluster data using the FarthestFirst algorithm.
For more information see:
Hochbaum, Shmoys (1985). - FarthestFirst() - 类的构造器 weka.clusterers.FarthestFirst
- fastRegressionTipText() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the tip text for this property
- FastVector - weka.core中的类
-
Implements a fast vector class without synchronized methods.
- FastVector() - 类的构造器 weka.core.FastVector
-
Constructs an empty vector with initial capacity zero.
- FastVector(int) - 类的构造器 weka.core.FastVector
-
Constructs a vector with the given capacity.
- FastVector.FastVectorEnumeration - weka.core中的类
-
Class for enumerating the vector's elements.
- FastVectorEnumeration(FastVector) - 类的构造器 weka.core.FastVector.FastVectorEnumeration
-
Constructs an enumeration.
- FastVectorEnumeration(FastVector, int) - 类的构造器 weka.core.FastVector.FastVectorEnumeration
-
Constructs an enumeration with a special element.
- FieldMetaInfo - weka.core.pmml中的类
-
Abstract superclass for various types of field meta data.
- FieldMetaInfo(Element) - 类的构造器 weka.core.pmml.FieldMetaInfo
-
Construct a new FieldMetaInfo.
- FieldMetaInfo.Interval - weka.core.pmml中的类
-
Inner class for an Interval.
- FieldMetaInfo.Interval.Closure - weka.core.pmml中的Enum Class
-
Enumerated type for the closure.
- FieldMetaInfo.Optype - weka.core.pmml中的Enum Class
-
Enumerated type for the Optype
- FieldMetaInfo.Value - weka.core.pmml中的类
-
Inner class for Values
- FieldMetaInfo.Value.Property - weka.core.pmml中的Enum Class
-
Enumerated type for the property.
- FieldRef - weka.core.pmml中的类
-
Class encapsulating a FieldRef Expression.
- FieldRef(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - 类的构造器 weka.core.pmml.FieldRef
- fields() - 类中的方法 weka.core.TechnicalInformation
-
returns an enumeration over all the stored fields
- FILE_EXTENSION - 类中的静态变量 weka.classifiers.CostMatrix
-
The deafult file extension for cost matrix files
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.ArffLoader
-
the file extension
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.C45Loader
-
the file extension
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.CSVLoader
-
the file extension.
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.LibSVMLoader
-
the file extension.
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.LibSVMSaver
-
the file extension
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.SerializedInstancesLoader
-
the file extension
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.SVMLightLoader
-
the file extension.
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.SVMLightSaver
-
the file extension.
- FILE_EXTENSION - 类中的静态变量 weka.core.converters.XRFFLoader
-
the file extension
- FILE_EXTENSION - 类中的静态变量 weka.core.Instances
-
The filename extension that should be used for arff files
- FILE_EXTENSION - 类中的静态变量 weka.core.xml.KOML
-
the extension for KOML files (including '.')
- FILE_EXTENSION - 类中的静态变量 weka.core.xml.XMLInstances
-
The filename extension that should be used for xrff files
- FILE_EXTENSION - 类中的静态变量 weka.core.xml.XStream
-
the extension for XStream files (including '.')
- FILE_EXTENSION - 类中的静态变量 weka.experiment.Experiment
-
The filename extension that should be used for experiment files
- FILE_EXTENSION - 类中的静态变量 weka.gui.beans.Classifier
-
the extension for serialized models (binary Java serialization)
- FILE_EXTENSION - 类中的静态变量 weka.gui.beans.KnowledgeFlowApp
-
the extension for the serialized setups (Java serialization)
- FILE_EXTENSION - 类中的静态变量 weka.gui.beans.SerializedModelSaver
-
the extension for serialized models (binary Java serialization)
- FILE_EXTENSION_COMPRESSED - 类中的静态变量 weka.core.converters.AbstractFileLoader
-
the extension for compressed files
- FILE_EXTENSION_COMPRESSED - 类中的静态变量 weka.core.converters.ArffLoader
- FILE_EXTENSION_COMPRESSED - 类中的静态变量 weka.core.converters.XRFFLoader
-
the extension for compressed files
- FILE_EXTENSION_XML - 类中的静态变量 weka.gui.beans.KnowledgeFlowApp
-
the extension for the serialized setups (Java serialization)
- FileEditor - weka.gui中的类
-
A PropertyEditor for File objects that lets the user select a file.
- FileEditor() - 类的构造器 weka.gui.FileEditor
- FileLogger - weka.core.logging中的类
-
A simple file logger, that just logs to a single file.
- FileLogger() - 类的构造器 weka.core.logging.FileLogger
- filePrefix() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Gets the file name prefix
- filePrefix() - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- filePrefix() - 接口中的方法 weka.core.converters.Saver
-
Gets the file prefix This method is used in the KnowledgeFlow GUI.
- FileSourcedConverter - weka.core.converters中的接口
-
Interface to a loader/saver that loads/saves from a file source.
- fill(Shape) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- fill3DRect(int, int, int, int, boolean) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw a filled rectangle with 3D effect in current pen color.
- fillArc(int, int, int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- fillFrame(Component) - 接口中的方法 weka.gui.MainMenuExtension
-
Fills the frame with life, like adding components, window listeners, setting size, location, etc.
- fillIn(int[], boolean[][]) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
-
Apply Tarjan and Yannakakis (1984) fill in algorithm for graph triangulation.
- fillOval(int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw a filled Oval in current pen color.
- fillPolygon(int[], int[], int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- fillPolygon(Polygon) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- fillRect(int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Draw a filled rectangle in current pen color.
- fillRoundRect(int, int, int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- fillWithMissingTipText() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Returns the tip text for this property
- filter(String, Instances) - 类中的静态方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Filters the input dataset against the provided expression.
- Filter - weka.filters中的类
-
An abstract class for instance filters: objects that take instances as input, carry out some transformation on the instance and then output the instance.
- Filter - weka.gui.beans中的类
-
A wrapper bean for Weka filters
- Filter() - 类的构造器 weka.filters.Filter
- Filter() - 类的构造器 weka.gui.beans.Filter
- FILTER_NONE - 类中的静态变量 weka.classifiers.functions.GaussianProcesses
-
no filter
- FILTER_NONE - 类中的静态变量 weka.classifiers.functions.SMO
-
filter: No normalization/standardization
- FILTER_NONE - 类中的静态变量 weka.classifiers.functions.SMOreg
-
The filter to apply to the training data: None
- FILTER_NONE - 类中的静态变量 weka.classifiers.mi.MDD
-
No normalization/standardization
- FILTER_NONE - 类中的静态变量 weka.classifiers.mi.MIDD
-
No normalization/standardization
- FILTER_NONE - 类中的静态变量 weka.classifiers.mi.MIEMDD
-
No normalization/standardization
- FILTER_NONE - 类中的静态变量 weka.classifiers.mi.MIOptimalBall
-
No normalization/standardization
- FILTER_NONE - 类中的静态变量 weka.classifiers.mi.MISMO
-
No normalization/standardization
- FILTER_NONE - 类中的静态变量 weka.classifiers.mi.MISVM
-
No normalization/standardization
- FILTER_NONE - 类中的静态变量 weka.filters.unsupervised.attribute.StringToWordVector
-
normalization: No normalization.
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.functions.GaussianProcesses
-
normalizes the data
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.functions.SMO
-
filter: Normalize training data
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.functions.SMOreg
-
The filter to apply to the training data: Normalzie
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.mi.MDD
-
Normalize training data
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.mi.MIDD
-
Normalize training data
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.mi.MIEMDD
-
Normalize training data
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.mi.MIOptimalBall
-
Normalize training data
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.mi.MISMO
-
Normalize training data
- FILTER_NORMALIZE - 类中的静态变量 weka.classifiers.mi.MISVM
-
Normalize training data
- FILTER_NORMALIZE_ALL - 类中的静态变量 weka.filters.unsupervised.attribute.StringToWordVector
-
normalization: Normalize all data.
- FILTER_NORMALIZE_TEST_ONLY - 类中的静态变量 weka.filters.unsupervised.attribute.StringToWordVector
-
normalization: Normalize test data only.
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.functions.GaussianProcesses
-
standardizes the data
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.functions.SMO
-
filter: Standardize training data
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.functions.SMOreg
-
The filter to apply to the training data: Standardize
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.mi.MDD
-
Standardize training data
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.mi.MIDD
-
Standardize training data
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.mi.MIEMDD
-
Standardize training data
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.mi.MIOptimalBall
-
Standardize training data
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.mi.MISMO
-
Standardize training data
- FILTER_STANDARDIZE - 类中的静态变量 weka.classifiers.mi.MISVM
-
Standardize training data
- filterAfterFirstBatchTipText() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Returns the tip text for this property.
- filterAttributesTipText() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the filterAttributes option tip text for the Weka GUI.
- FilterBeanInfo - weka.gui.beans中的类
-
Bean info class for the Filter bean
- FilterBeanInfo() - 类的构造器 weka.gui.beans.FilterBeanInfo
- FilterCustomizer - weka.gui.beans中的类
-
GUI customizer for the filter bean
- FilterCustomizer() - 类的构造器 weka.gui.beans.FilterCustomizer
- FilteredAssociator - weka.associations中的类
-
Class for running an arbitrary associator on data that has been passed through an arbitrary filter.
- FilteredAssociator() - 类的构造器 weka.associations.FilteredAssociator
-
Default constructor.
- FilteredAttributeEval - weka.attributeSelection中的类
-
Class for running an arbitrary attribute evaluator on data that has been passed through an arbitrary filter (note: filters that alter the order or number of attributes are not allowed).
- FilteredAttributeEval() - 类的构造器 weka.attributeSelection.FilteredAttributeEval
- FilteredClassifier - weka.classifiers.meta中的类
-
Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.
- FilteredClassifier() - 类的构造器 weka.classifiers.meta.FilteredClassifier
-
Default constructor.
- FilteredClusterer - weka.clusterers中的类
-
Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter.
- FilteredClusterer() - 类的构造器 weka.clusterers.FilteredClusterer
-
Default constructor.
- FilteredSubsetEval - weka.attributeSelection中的类
-
Class for running an arbitrary subset evaluator on data that has been passed through an arbitrary filter (note: filters that alter the order or number of attributes are not allowed).
- FilteredSubsetEval() - 类的构造器 weka.attributeSelection.FilteredSubsetEval
- filterFile(Filter, String[]) - 类中的静态方法 weka.filters.Filter
-
Method for testing filters.
- filtersTipText() - 类中的方法 weka.filters.MultiFilter
-
Returns the tip text for this property
- filtersTipText() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Returns the tip text for this property.
- filterSubset(List<ScatterSearchV1.Subset>, int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Filter a given Lis of Subsets removing the equals subsets
- filterTipText() - 类中的方法 weka.associations.FilteredAssociator
-
Returns the tip text for this property
- filterTipText() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Returns the tip text for this property
- filterTipText() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Returns the tip text for this property
- filterTipText() - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Returns the tip text for this property
- filterTipText() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Returns the tip text for this property
- filterTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- filterTipText() - 类中的方法 weka.clusterers.FilteredClusterer
-
Returns the tip text for this property.
- filterTipText() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns a tip text for this property suitable for display in the GUI
- filterTypeTipText() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.classifiers.mi.MDD
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.classifiers.mi.MIDD
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- filterTypeTipText() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns the tip text for this property
- finalize() - 类中的方法 weka.gui.sql.ResultSetTable
-
frees up the memory
- finalize() - 类中的方法 weka.gui.sql.ResultSetTableModel
-
frees up the memory.
- finalize() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- find() - 类中的方法 weka.core.FindWithCapabilities
-
returns a list with all the classnames that fit the criteria.
- find(Class, String) - 类中的静态方法 weka.core.ClassDiscovery
-
Checks the given package for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
- find(Class, String[]) - 类中的静态方法 weka.core.ClassDiscovery
-
Checks the given packages for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
- find(Object, PropertyPath.Path) - 类中的静态方法 weka.core.PropertyPath
-
returns the property and object associated with the given path, null if a problem occurred.
- find(String) - 类中的方法 weka.core.Trie.TrieNode
-
returns the node with the given suffix
- find(String, String) - 类中的静态方法 weka.core.ClassDiscovery
-
Checks the given package for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
- find(String, String[]) - 类中的静态方法 weka.core.ClassDiscovery
-
Checks the given packages for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
- findAllRulesForSupportLevelTipText() - 类中的方法 weka.associations.FPGrowth
-
Tip text for this property suitable for displaying in the GUI.
- findArgmin(double[], double[][]) - 类中的方法 weka.core.Optimization
-
Main algorithm.
- findBestLeaf(double[], RuleNode[]) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Find the leaf with greatest coverage
- findCentralTendencies(double[]) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Finds the central tendency, given the classifications for an instance.
- findInstance(Point) - 类中的静态方法 weka.gui.beans.BeanInstance
-
Looks for a bean (if any) whose bounds contain the supplied point
- findInstances(Rectangle) - 类中的静态方法 weka.gui.beans.BeanInstance
-
Looks for all beans (if any) located within the supplied bounding box.
- findIntervall(double) - 类中的方法 weka.associations.PriorEstimation
-
searches the mid point of the interval a given confidence value falls into
- findMinDistance(Instances, int) - 类中的静态方法 weka.estimators.EstimatorUtils
-
Find the minimum distance between values
- findNodes(String) - 类中的方法 weka.core.xml.XMLDocument
-
Returns the nodes that the given xpath expression will find in the document.
- findNumBinsTipText() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the tip text for this property
- findNumBinsTipText() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Returns the tip text for this property
- findPackages() - 类中的静态方法 weka.core.ClassDiscovery
-
Lists all packages it can find in the classpath.
- findRadius(Instances) - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Find the maximum radius for the optimal ball.
- findReadMethod(Object, String) - 类中的静态方法 weka.core.xml.XMLSerializationMethodHandler
-
returns the method with the given name that has the same signature as
readFromXML()
of theXMLSerialiation
class. - findWeights(int, double[][]) - 类中的方法 weka.classifiers.mi.MINND
-
Use gradient descent to distort the MU parameter for the exemplar.
- FindWithCapabilities - weka.core中的类
-
Locates all classes with certain capabilities.
- FindWithCapabilities() - 类的构造器 weka.core.FindWithCapabilities
- findWriteMethod(Object, String) - 类中的静态方法 weka.core.xml.XMLSerializationMethodHandler
-
returns the method with the given name that has the same signature as
writeToXML()
of theXMLSerialiation
class. - FINE - enum class 中的枚举常量 weka.core.logging.Logger.Level
-
FINER level.
- FINE - 类中的静态变量 weka.core.Debug
-
the log level Fine
- FINER - enum class 中的枚举常量 weka.core.logging.Logger.Level
-
FINEST level.
- FINER - 类中的静态变量 weka.core.Debug
-
the log level Finer
- FINEST - enum class 中的枚举常量 weka.core.logging.Logger.Level
-
FINEST level.
- FINEST - 类中的静态变量 weka.core.Debug
-
the log level Finest
- finished() - 类中的方法 weka.experiment.OutputZipper
-
Closes the zip file.
- finished() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Finalizes output file.
- FINISHED - 类中的静态变量 weka.experiment.TaskStatusInfo
- fireLayoutCompleteEvent(LayoutCompleteEvent) - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
Fires a LayoutCompleteEvent.
- fireLayoutCompleteEvent(LayoutCompleteEvent) - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
This fires a LayoutCompleteEvent once a layout has been completed.
- FIRST - 类中的静态变量 weka.filters.unsupervised.attribute.ClassAssigner
-
use the first attribute as class.
- firstElement() - 类中的方法 weka.core.FastVector
-
Returns the first element of the vector.
- firstElement() - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Returns the first component of this list.
- firstInstance() - 类中的方法 weka.core.Instances
-
Returns the first instance in the set.
- FirstOrder - weka.filters.unsupervised.attribute中的类
-
This instance filter takes a range of N numeric attributes and replaces them with N-1 numeric attributes, the values of which are the difference between consecutive attribute values from the original instance.
- FirstOrder() - 类的构造器 weka.filters.unsupervised.attribute.FirstOrder
- firstValueIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
- firstValueIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
- fit(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Fits the mixture (or mixing) distribution to the data.
- fit(DoubleVector, int) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Fits the mixture (or mixing) distribution to the data.
- fitForSingleCluster(DoubleVector, int) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Fits the mixture (or mixing) distribution to the data.
- fittingIntervals(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Contructs the set of fitting intervals for mixture estimation.
- fittingIntervals(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Contructs the set of fitting intervals for mixture estimation.
- fittingIntervals(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Contructs the set of fitting intervals for mixture estimation.
- fitToScreen() - 类中的方法 weka.gui.hierarchyvisualizer.HierarchyVisualizer
-
Fits the tree to the current screen size.
- fitToScreen() - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Fits the tree to the current screen size.
- FlexibleDecimalFormat - weka.core.matrix中的类
- FlexibleDecimalFormat() - 类的构造器 weka.core.matrix.FlexibleDecimalFormat
- FlexibleDecimalFormat(double) - 类的构造器 weka.core.matrix.FlexibleDecimalFormat
- FlexibleDecimalFormat(int) - 类的构造器 weka.core.matrix.FlexibleDecimalFormat
- FlexibleDecimalFormat(int, boolean) - 类的构造器 weka.core.matrix.FlexibleDecimalFormat
- FlexibleDecimalFormat(int, boolean, boolean, boolean) - 类的构造器 weka.core.matrix.FlexibleDecimalFormat
- FLOAT - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for FLOAT used for reading experiment results.
- floatingForwardSearch(int, BitSet, int[], int, boolean, int, Instances, SubsetEvaluator, boolean) - 类中的方法 weka.attributeSelection.LFSMethods
-
Performs linear floating forward selection ( the stopping criteria cannot be changed to a specific size value )
- FloatingPointFormat - weka.core.matrix中的类
-
Class for the format of floating point numbers
- FloatingPointFormat() - 类的构造器 weka.core.matrix.FloatingPointFormat
-
Default constructor
- FloatingPointFormat(int) - 类的构造器 weka.core.matrix.FloatingPointFormat
- FloatingPointFormat(int, int) - 类的构造器 weka.core.matrix.FloatingPointFormat
- FloatingPointFormat(int, int, boolean) - 类的构造器 weka.core.matrix.FloatingPointFormat
- FLOOR - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- FLOOR - 接口中的静态变量 weka.core.mathematicalexpression.sym
- FLOOR - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- FLOOR1 - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- FlowRunner - weka.gui.beans中的类
-
Small utility class for executing KnowledgeFlow flows outside of the KnowledgeFlow application
- FlowRunner() - 类的构造器 weka.gui.beans.FlowRunner
-
Constructor
- FlowRunner.SimpleLogger - weka.gui.beans中的类
- flush() - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
ignored.
- flush() - 类中的方法 weka.core.Tee
-
flushes all the printstreams.
- fMeasure(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the F-Measure with respect to a particular class.
- FMEASURE - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
F-measure
- FMEASURE_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: FMeasure
- FOLD_FIELD_NAME - 类中的静态变量 weka.experiment.CrossValidationResultProducer
-
The name of the key field containing the fold number
- foldsTipText() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns a string for this option suitable for display in the gui as a tip text
- foldsTipText() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns the tip text for this property
- foldsTipText() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns the tip text for this property
- foldsTipText() - 类中的方法 weka.classifiers.rules.JRip
-
Returns the tip text for this property
- foldsTipText() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns the tip text for this property
- foldsTipText() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Tip text for this property
- foldsTypeTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- foldTipText() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Returns the tip text for this property
- foldTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Returns the tip text for this property
- forCapabilities(Capabilities) - 类中的静态方法 weka.core.TestInstances
-
returns a TestInstances instance setup already for the the given capabilities.
- forInstances(Instances) - 类中的静态方法 weka.core.Capabilities
-
returns a Capabilities object specific for this data.
- forInstances(Instances, boolean) - 类中的静态方法 weka.core.Capabilities
-
returns a Capabilities object specific for this data.
- format(double, StringBuffer, FieldPosition) - 类中的方法 weka.core.matrix.ExponentialFormat
- format(double, StringBuffer, FieldPosition) - 类中的方法 weka.core.matrix.FlexibleDecimalFormat
- format(double, StringBuffer, FieldPosition) - 类中的方法 weka.core.matrix.FloatingPointFormat
- FORMAT_AVAILABLE - 类中的静态变量 weka.gui.beans.InstanceEvent
- FORMAT_AVAILABLE - 类中的静态变量 weka.gui.streams.InstanceEvent
-
Specifies that the instance format is available
- FORMAT_HHMMSS - 类中的静态变量 weka.core.Debug.Clock
-
the output format in hours:minutes:seconds, with fraction of msecs
- FORMAT_MILLISECONDS - 类中的静态变量 weka.core.Debug.Clock
-
the output format in milli-seconds
- FORMAT_SECONDS - 类中的静态变量 weka.core.Debug.Clock
-
the output format in seconds, with fraction of msecs
- formatDate(double) - 类中的方法 weka.core.Attribute
-
Returns the given amount of milliseconds formatted according to the current Date format.
- formatString(String) - 类中的方法 weka.core.matrix.FlexibleDecimalFormat
- formatTipText() - 类中的方法 weka.datagenerators.DataGenerator
-
Returns the tip text for this property
- forName(Class, String, String[]) - 类中的静态方法 weka.core.Utils
-
Creates a new instance of an object given it's class name and (optional) arguments to pass to it's setOptions method.
- forName(String, String[]) - 类中的静态方法 weka.associations.AbstractAssociator
-
Creates a new instance of a associator given it's class name and (optional) arguments to pass to it's setOptions method.
- forName(String, String[]) - 类中的静态方法 weka.attributeSelection.ASEvaluation
-
Creates a new instance of an attribute/subset evaluator given it's class name and (optional) arguments to pass to it's setOptions method.
- forName(String, String[]) - 类中的静态方法 weka.attributeSelection.ASSearch
-
Creates a new instance of a search class given it's class name and (optional) arguments to pass to it's setOptions method.
- forName(String, String[]) - 类中的静态方法 weka.classifiers.Classifier
-
Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method.
- forName(String, String[]) - 类中的静态方法 weka.classifiers.functions.supportVector.Kernel
-
Creates a new instance of a kernel given it's class name and (optional) arguments to pass to it's setOptions method.
- forName(String, String[]) - 类中的静态方法 weka.clusterers.AbstractClusterer
-
Creates a new instance of a clusterer given it's class name and (optional) arguments to pass to it's setOptions method.
- forName(String, String[]) - 类中的静态方法 weka.estimators.Estimator
-
Creates a new instance of a estimatorr given it's class name and (optional) arguments to pass to it's setOptions method.
- forward(PaceMatrix, IntVector, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Forward ordering of columns in terms of response explanation.
- forwardSearch(int, BitSet, int[], int, boolean, int, int, Instances, SubsetEvaluator, boolean) - 类中的方法 weka.attributeSelection.LFSMethods
-
Performs linear forward selection
- forwardSelectionMethodTipText() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the tip text for this property
- foundUsefulAttribute() - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Returns true if a usable attribute was found.
- FP_RATE_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: False Positive Rate"
- FPGrowth - weka.associations中的类
-
Class implementing the FP-growth algorithm for finding large item sets without candidate generation.
- FPGrowth() - 类的构造器 weka.associations.FPGrowth
-
Construct a new FPGrowth object.
- FPGrowth.AssociationRule - weka.associations中的类
- FPGrowth.AssociationRule.METRIC_TYPE - weka.associations中的Enum Class
-
Enum for holding different metric types
- FPGrowth.BinaryItem - weka.associations中的类
-
Inner class that handles a single binary item
- FProbability(double, int, int) - 类中的静态方法 weka.core.Statistics
-
Computes probability of F-ratio.
- freeNotCoveredInstances() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Free up memory consumed by the set of instances not covered by this rule.
- FREQ_ASCEND - 类中的静态变量 weka.filters.supervised.attribute.ClassOrder
-
The class values are sorted in ascending order based on their frequencies
- FREQ_DESCEND - 类中的静态变量 weka.filters.supervised.attribute.ClassOrder
-
The class values are sorted in descending order based on their frequencies
- frequencyLimitTipText() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns the tip text for this property
- frequencyLimitTipText() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns the tip text for this property
- frequencyThresholdTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- FromFile - weka.classifiers.bayes.net.search.fixed中的类
-
The FromFile reads the structure of a Bayes net from a file in BIFF format.
- FromFile() - 类的构造器 weka.classifiers.bayes.net.search.fixed.FromFile
- fromXML(Document) - 类中的方法 weka.core.xml.XMLSerialization
-
returns the given DOM document as an instance of the specified class
- FT - weka.classifiers.trees中的类
-
Classifier for building 'Functional trees', which are classification trees that could have logistic regression functions at the inner nodes and/or leaves.
- FT() - 类的构造器 weka.classifiers.trees.FT
-
Creates an instance of FT with standard options
- FTInnerNode - weka.classifiers.trees.ft中的类
-
Class for Functional Inner tree structure.
- FTInnerNode(boolean, int, int, double, boolean) - 类的构造器 weka.classifiers.trees.ft.FTInnerNode
-
Constructor for Functional Inner tree node.
- FTLeavesNode - weka.classifiers.trees.ft中的类
-
Class for Functional Leaves tree version.
- FTLeavesNode(boolean, int, int, double, boolean) - 类的构造器 weka.classifiers.trees.ft.FTLeavesNode
-
Constructor for Functional Leaves tree node.
- FTNode - weka.classifiers.trees.ft中的类
-
Class for Functional tree structure.
- FTNode(boolean, int, int, double, boolean) - 类的构造器 weka.classifiers.trees.ft.FTNode
-
Constructor for Functional tree node.
- FTtree - weka.classifiers.trees.ft中的类
-
Abstract class for Functional tree structure.
- FTtree() - 类的构造器 weka.classifiers.trees.ft.FTtree
- fullValue() - 类中的方法 weka.gui.HierarchyPropertyParser
-
The full value of the current node, i.e.
- Function - weka.core.pmml中的类
-
Abstract superclass for PMML built-in and DefineFunctions.
- Function() - 类的构造器 weka.core.pmml.Function
- FUNCTION_1 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 1
- FUNCTION_10 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 10
- FUNCTION_2 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 2
- FUNCTION_3 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 3
- FUNCTION_4 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 4
- FUNCTION_5 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 5
- FUNCTION_6 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 6
- FUNCTION_7 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 7
- FUNCTION_8 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 8
- FUNCTION_9 - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
function 9
- FUNCTION_TAGS - 类中的静态变量 weka.datagenerators.classifiers.classification.Agrawal
-
the funtion tags
- functionTipText() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Returns the tip text for this property
G
- g1(double, double) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Constructs the Givens rotation
- g2(double[], int, int, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Performs the Givens rotation
- gainRatio() - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Returns (C4.5-type) gain ratio for the generated split.
- gainRatio() - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns (C4.5-type) gain ratio for the generated split.
- gainRatio(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Computes gain ratio for contingency table (split on rows).
- GainRatioAttributeEval - weka.attributeSelection中的类
-
GainRatioAttributeEval :
Evaluates the worth of an attribute by measuring the gain ratio with respect to the class.
GainR(Class, Attribute) = (H(Class) - H(Class | Attribute)) / H(Attribute). - GainRatioAttributeEval() - 类的构造器 weka.attributeSelection.GainRatioAttributeEval
-
Constructor
- GainRatioSplitCrit - weka.classifiers.trees.j48中的类
-
Class for computing the gain ratio for a given distribution.
- GainRatioSplitCrit() - 类的构造器 weka.classifiers.trees.j48.GainRatioSplitCrit
- gamma(double) - 类中的静态方法 weka.core.Statistics
-
Returns the Gamma function of the argument.
- gammaTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- gammaTipText() - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Returns the tip text for this property
- GAUSSIAN - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Distributions available
- GAUSSIAN - 类中的静态变量 weka.datagenerators.clusterers.SubspaceCluster
-
cluster type: gaussian
- GAUSSIAN - 类中的静态变量 weka.filters.unsupervised.attribute.RandomProjection
-
distribution type: gaussian
- GaussianPriorImpl - weka.classifiers.bayes.blr中的类
-
Implementation of the Gaussian Prior update function based on CLG Algorithm with a certain Trust Region Update.
- GaussianPriorImpl() - 类的构造器 weka.classifiers.bayes.blr.GaussianPriorImpl
- GaussianProcesses - weka.classifiers.functions中的类
-
Implements Gaussian Processes for regression without hyperparameter-tuning.
- GaussianProcesses() - 类的构造器 weka.classifiers.functions.GaussianProcesses
-
the default constructor
- GE - 接口中的静态变量 weka.core.mathematicalexpression.sym
- GE - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- GeneralizedSequentialPatterns - weka.associations中的类
-
Class implementing a GSP algorithm for discovering sequential patterns in a sequential data set.
The attribute identifying the distinct data sequences contained in the set can be determined by the respective option. - GeneralizedSequentialPatterns() - 类的构造器 weka.associations.GeneralizedSequentialPatterns
-
Constructor.
- GeneralRegression - weka.classifiers.pmml.consumer中的类
-
Class implementing import of PMML General Regression model.
- GeneralRegression(Element, Instances, MiningSchema) - 类的构造器 weka.classifiers.pmml.consumer.GeneralRegression
-
Constructs a GeneralRegression classifier.
- generate() - 类中的方法 weka.core.Javadoc
-
generates either the plain Javadoc (if no filename specified) or the updated file (if a filename is specified).
- generate() - 类中的方法 weka.core.ListOptions
-
generates the options string.
- generate() - 类中的方法 weka.core.TestInstances
-
Generates a new dataset
- generate(String) - 类中的方法 weka.core.TestInstances
-
generates a new dataset.
- generateDistribution() - 类中的方法 weka.associations.PriorEstimation
-
Calculates the prior distribution.
- generateExample() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Generates one example of the dataset.
- generateExample() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Generates one example of the dataset.
- generateExample() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Generates one example of the dataset.
- generateExample() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Generates one example of the dataset.
- generateExample() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Generate an example of the dataset dataset.
- generateExample() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Generates one example of the dataset.
- generateExample() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Generates one example of the dataset.
- generateExample() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Generate an example of the dataset.
- generateExample() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Generate an example of the dataset.
- generateExample() - 类中的方法 weka.datagenerators.DataGenerator
-
Generates one example of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Generates all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Generates all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Generates all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Generates all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Generate all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Generates all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Generates all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Generate all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Generate all examples of the dataset.
- generateExamples() - 类中的方法 weka.datagenerators.DataGenerator
-
Generates all examples of the dataset.
- generateExamples(int, Random, Instances) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Generate all examples of the dataset.
- generateExamples(Random, Instances) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Generate all examples of the dataset.
- generateFinished() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Generates a comment string that documentats the data generator.
- generateFinished() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Generates a comment string that documentats the data generator.
- generateFinished() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Generates a comment string that documentats the data generator.
- generateFinished() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Generates a comment string that documentats the data generator.
- generateFinished() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Compiles documentation about the data generation.
- generateFinished() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Generates a comment string that documentats the data generator.
- generateFinished() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Generates a comment string that documentats the data generator.
- generateFinished() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Compiles documentation about the data generation after the generation process
- generateFinished() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Compiles documentation about the data generation after the generation process
- generateFinished() - 类中的方法 weka.datagenerators.DataGenerator
-
Generates a comment string that documentates the data generator.
- generateHelp() - 类中的方法 weka.core.Javadoc
-
generates a string to print as help on the console
- generateHelp() - 类中的方法 weka.core.ListOptions
-
generates a string to print as help on the console
- generateInstances() - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
GenerateInstances generates random instances sampling from the distribution represented by the Bayes network structure.
- generateInstances() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
sets Instances generated via DataGenerators (pops up a Dialog)
- generateInstances(int[]) - 接口中的方法 weka.gui.boundaryvisualizer.DataGenerator
-
Generate an instance.
- generateInstances(int[]) - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
-
Generates a new instance using one kernel estimator.
- generateOutput() - 类中的方法 weka.gui.visualize.BMPWriter
-
generates the actual output
- generateOutput() - 类中的方法 weka.gui.visualize.JPEGWriter
-
generates the actual output.
- generateOutput() - 类中的方法 weka.gui.visualize.PNGWriter
-
generates the actual output
- generateOutput() - 类中的方法 weka.gui.visualize.PostscriptWriter
-
generates the actual output
- generatePartition(Instances) - 类中的方法 weka.classifiers.trees.RandomTree
-
Builds the classifier to generate a partition.
- generateRandomNetwork() - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
Generate random connected Bayesian network with discrete nodes having all the same cardinality.
- generateRandomNetworkStructure(int, int) - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
GenerateRandomNetworkStructure generate random connected Bayesian network
- generateRandomNumber(int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
- generateRankingTipText() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns the tip text for this property
- generateRankingTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- generateRankingTipText() - 类中的方法 weka.attributeSelection.Ranker
-
Returns the tip text for this property
- GenerateReferenceSet(List<ScatterSearchV1.Subset>, int, int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Generate the a ReferenceSet containing the n best solutions and the m most diverse solutions of the initial Population.
- generateRuleItem(ItemSet, ItemSet, Instances, int, int, double[], Hashtable) - 类中的方法 weka.associations.RuleItem
-
Constructs a new RuleItem if the support of the given rule is above the support threshold.
- generateRules(double, boolean) - 类中的方法 weka.associations.LabeledItemSet
-
Generates rules out of item sets
- generateRules(double, FastVector, int) - 类中的方法 weka.associations.AprioriItemSet
-
Generates all rules for an item set.
- generateRules(int, double[], Hashtable, double, Instances, TreeSet, int) - 类中的方法 weka.associations.CaRuleGeneration
-
Generates all rules for an item set.
- generateRules(int, double[], Hashtable, double, Instances, TreeSet, int) - 类中的方法 weka.associations.RuleGeneration
-
Generates all rules for an item set.
- generateRulesBruteForce(double, int, FastVector, int, int, double) - 类中的方法 weka.associations.AprioriItemSet
-
Generates all significant rules for an item set.
- generateRulesBruteForce(FPGrowth.FrequentItemSets, FPGrowth.AssociationRule.METRIC_TYPE, double, int, int, int) - 类中的静态方法 weka.associations.FPGrowth.AssociationRule
-
Generate all association rules, from the supplied frequet item sets, that meet a given minimum metric threshold.
- generateRulesTipText() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns the tip text for this property
- generateStart() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Generates a comment string that documentates the data generator.
- generateStart() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Generates a comment string that documentates the data generator.
- generateStart() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Generates a comment string that documentates the data generator.
- generateStart() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Generates a comment string that documentates the data generator.
- generateStart() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Generates a comment string that documentates the data generator.
- generateStart() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Generates a comment string that documentates the data generator.
- generateStart() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Generates a comment string that documentates the data generator.
- generateStart() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Compiles documentation about the data generation before the generation process
- generateStart() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Compiles documentation about the data generation before the generation process
- generateStart() - 类中的方法 weka.datagenerators.DataGenerator
-
Generates a comment string that documentates the data generator.
- GeneratorPropertyIteratorPanel - weka.gui.experiment中的类
-
This panel controls setting a list of values for an arbitrary resultgenerator property for an experiment to iterate over.
- GeneratorPropertyIteratorPanel() - 类的构造器 weka.gui.experiment.GeneratorPropertyIteratorPanel
-
Creates the property iterator panel initially disabled.
- GeneratorPropertyIteratorPanel(Experiment) - 类的构造器 weka.gui.experiment.GeneratorPropertyIteratorPanel
-
Creates the property iterator panel and sets the experiment.
- GenericArrayEditor - weka.gui中的类
-
A PropertyEditor for arrays of objects that themselves have property editors.
- GenericArrayEditor() - 类的构造器 weka.gui.GenericArrayEditor
-
Sets up the array editor.
- GenericObjectEditor - weka.gui中的类
-
A PropertyEditor for objects.
- GenericObjectEditor() - 类的构造器 weka.gui.GenericObjectEditor
-
Default constructor.
- GenericObjectEditor(boolean) - 类的构造器 weka.gui.GenericObjectEditor
-
Constructor that allows specifying whether it is possible to change the class within the editor dialog.
- GenericObjectEditor.CapabilitiesFilterDialog - weka.gui中的类
-
A dialog for selecting Capabilities to look for in the GOE tree.
- GenericObjectEditor.GOEPanel - weka.gui中的类
-
Handles the GUI side of editing values.
- GenericObjectEditor.GOETreeNode - weka.gui中的类
-
A specialized TreeNode for supporting filtering via Capabilities.
- GenericObjectEditor.JTreePopupMenu - weka.gui中的类
-
Creates a popup menu containing a tree that is aware of the screen dimensions.
- GenericPropertiesCreator - weka.gui中的类
-
This class can generate the properties object that is normally loaded from the
GenericObjectEditor.props
file (= PROPERTY_FILE). - GenericPropertiesCreator() - 类的构造器 weka.gui.GenericPropertiesCreator
-
initializes the creator, locates the props file with the Utils class.
- GenericPropertiesCreator(String) - 类的构造器 weka.gui.GenericPropertiesCreator
-
initializes the creator, the given file overrides the props-file search of the Utils class
- GeneticSearch - weka.attributeSelection中的类
-
GeneticSearch:
Performs a search using the simple genetic algorithm described in Goldberg (1989).
For more information see:
David E. - GeneticSearch - weka.classifiers.bayes.net.search.global中的类
-
This Bayes Network learning algorithm uses genetic search for finding a well scoring Bayes network structure.
- GeneticSearch - weka.classifiers.bayes.net.search.local中的类
-
This Bayes Network learning algorithm uses genetic search for finding a well scoring Bayes network structure.
- GeneticSearch() - 类的构造器 weka.attributeSelection.GeneticSearch
-
Constructor.
- GeneticSearch() - 类的构造器 weka.classifiers.bayes.net.search.global.GeneticSearch
- GeneticSearch() - 类的构造器 weka.classifiers.bayes.net.search.local.GeneticSearch
- get(int) - 类中的方法 weka.core.matrix.DoubleVector
-
Gets a single element.
- get(int) - 类中的方法 weka.core.matrix.IntVector
-
Gets the value of an element.
- get(int) - 类中的方法 weka.core.PropertyPath.Path
-
returns the element at the given index
- get(int) - 类中的方法 weka.core.Tee
-
returns the specified PrintStream from the list.
- get(int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Returns the element at the specified position in this list.
- get(int, int) - 类中的方法 weka.core.matrix.Matrix
-
Get a single element.
- get(Class) - 类中的方法 weka.core.xml.MethodHandler
-
returns the stored method for the given class
- get(String) - 类中的方法 weka.core.xml.MethodHandler
-
returns the stored method for the given property
- get(String, String) - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the value for the specified property, if non-existent then the default value.
- get(String, String) - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the value for the specified property, if non-existent then the default value.
- getAboutPanel() - 类中的方法 weka.gui.PropertySheetPanel
-
Return the panel containing global info and help for the object being edited.
- getAccu() - 类中的方法 weka.classifiers.rules.JRip.Antd
- getAccuRate() - 类中的方法 weka.classifiers.rules.JRip.Antd
- getActionListener(JFrame) - 接口中的方法 weka.gui.MainMenuExtension
-
If the extension has a custom ActionListener for the menu item, then it must be returned here.
- getActualIndex(int) - 类中的方法 weka.core.AttributeLocator
-
returns actual index in the Instances object.
- getActualRow(int) - 类中的方法 weka.gui.SortedTableModel
-
Returns the actual underlying row the given visible one represents.
- getAcuity() - 类中的方法 weka.clusterers.Cobweb
-
get the acuity value
- getAddress() - 类中的静态方法 weka.core.Copyright
-
returns the address of the owner
- getAdjustWeights() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns true if instance weights will be adjusted to maintain total weight per class.
- getADTree() - 类中的方法 weka.classifiers.bayes.BayesNet
-
get ADTree strucrture containing efficient representation of counts.
- getAdvanceDataSetFirst() - 类中的方法 weka.experiment.Experiment
-
Get the value of m_DataSetFirstFirst.
- getAlgorithm() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Gets the type of algorithm to use
- getAlgorithm() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Gets the type of algorithm to use
- getAlgorithmStart() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the time/date string the algorithm was started
- getAlgorithmType() - 类中的方法 weka.classifiers.mi.MILR
-
Gets the type of algorithm.
- getAllBits(List<ScatterSearchV1.Subset>) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Save in Bitset all the gens that are in many others subsets.
- getAllowedIndices() - 类中的方法 weka.core.AttributeLocator
-
returns the indices that are allowed to check for the attribute type
- getAllowUnclassifiedInstances() - 类中的方法 weka.classifiers.trees.RandomTree
-
Get the value of NumFolds.
- getAllTheRules() - 类中的方法 weka.associations.Apriori
-
returns all the rules
- getAllTheRules() - 类中的方法 weka.associations.PredictiveApriori
-
returns all the rules
- getAlpha() - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
Get prior used in probability table estimation
- getAlpha() - 类中的方法 weka.classifiers.functions.Winnow
-
Get the value of Alpha.
- getAmplitude() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Gets the amplitude multiplier.
- getAnimatedIcon() - 类中的方法 weka.gui.beans.BeanVisual
-
Returns the animated icon
- getAnimatedIconPath() - 类中的方法 weka.gui.beans.BeanVisual
-
returns the path for the animated icon
- getAntds() - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Return the antecedents
- getAppendPredictedProbabilities() - 类中的方法 weka.gui.beans.PredictionAppender
-
Return true if predicted probabilities are to be appended rather than class value
- getArffFile() - 类中的方法 weka.gui.streams.InstanceLoader
- getArffFile() - 类中的方法 weka.gui.streams.InstanceSavePanel
- getArray() - 类中的方法 weka.core.matrix.DoubleVector
-
Access the internal one-dimensional array.
- getArray() - 类中的方法 weka.core.matrix.IntVector
-
Access the internal one-dimensional array.
- getArray() - 类中的方法 weka.core.matrix.Matrix
-
Access the internal two-dimensional array.
- getArrayClass(Class) - 类中的静态方法 weka.core.Utils
-
Returns the basic class of an array class (handles multi-dimensional arrays).
- getArrayCopy() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns a copy of the DoubleVector usng a double array.
- getArrayCopy() - 类中的方法 weka.core.matrix.IntVector
-
Returns a copy of the internal one-dimensional array.
- getArrayCopy() - 类中的方法 weka.core.matrix.Matrix
-
Copy the internal two-dimensional array.
- getArrayDimensions(Class) - 类中的静态方法 weka.core.Utils
-
Returns the dimensions of the given array.
- getArrayDimensions(Object) - 类中的静态方法 weka.core.Utils
-
Returns the dimensions of the given array.
- getArtificialSize() - 类中的方法 weka.classifiers.meta.Decorate
-
Factor that determines number of artificial examples to generate.
- getASCrossvalidationFolds() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default number of folds of the CV in the attribute selection panel.
- getASEvaluator() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default attribute evalautor (fully configured) for the attribute selection panel.
- getAsInstance(Instances, Random) - 类中的方法 weka.core.AlgVector
-
Gets the elements of the vector as an instance.
- getASRandomSeed() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default random seed value in the attribute selection panel.
- getASSearch() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default attribute selection search scheme (fully configured) for the attribute selection panel.
- getAssignments() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets the assignments for each instance
- getAssociatedConnections() - 类中的方法 weka.gui.beans.MetaBean
- getAssociationRules() - 类中的方法 weka.associations.FPGrowth
-
Gets the list of mined association rules.
- getAssociator() - 类中的方法 weka.associations.CheckAssociator
-
Get the associator being tested
- getAssociator() - 类中的方法 weka.associations.SingleAssociatorEnhancer
-
Get the associator used as the base associator.
- getAssociator() - 类中的方法 weka.gui.beans.Associator
-
Get the associator currently set for this wrapper
- getAssociator() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default associator (fully configured) for the associations panel.
- getASTestMode() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default attribute selection test mode for the attribute selection panel.
- getAsText() - 类中的方法 weka.gui.CostMatrixEditor
-
Some objects can be represented as text, but a cost matrix cannot.
- getAsText() - 类中的方法 weka.gui.GenericArrayEditor
-
Returns null as we don't support getting/setting values as text.
- getAsText() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns null as we don't support getting/setting values as text.
- getAsText() - 类中的方法 weka.gui.SelectedTagEditor
-
Gets the current value as text.
- getAsText() - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Returns the date format string.
- getAttIndex(int) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the boolean value at the specified index in the Attribute Indexes array
- getAttList_Irr() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the array that defines which of the attributes are seen to be irrelevant.
- getAttr() - 类中的方法 weka.classifiers.rules.JRip.Antd
- getAttribute() - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
Get the attribute that this item corresponds to.
- getAttribute1() - 类中的方法 weka.gui.visualize.VisualizePanelEvent
- getAttribute2() - 类中的方法 weka.gui.visualize.VisualizePanelEvent
- getAttributeAt(int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns the attribute at the given index, can be NULL if not an attribute column
- getAttributeAt(int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the attribute at the given index, can be NULL if not an attribute column
- getAttributeCapabilities() - 类中的方法 weka.core.Capabilities
-
returns all attribute capabilities
- getAttributeColumn(String) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns the column of the given attribute name, -1 if not found
- getAttributeColumn(String) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the column of the given attribute name, -1 if not found
- getAttributeEvaluator() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Get the attribute evaluator to use
- getAttributeEvaluator() - 类中的方法 weka.attributeSelection.RaceSearch
-
Get the attribute evaluator used to generate the ranking.
- getAttributeEvaluator() - 类中的方法 weka.attributeSelection.RankSearch
-
Get the attribute evaluator used to generate the ranking.
- getAttributeID() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Get the index of Attibute Identifying the instances
- getAttributeIndex() - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Returns the index of the attribute used in the regression.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Get the index of the attribute used.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Get the index of the attribute used.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Get the index of the attribute used.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Gets the index of the attribute converted.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Get the index of the attribute used.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Get the index of the attribute used.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Get the index of the attribute used.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Get the index of the attribute used.
- getAttributeIndex() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Get the index of the attribute used.
- getAttributeIndexes() - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Get the index of the attribute used.
- getAttributeIndices() - 类中的方法 weka.core.AttributeLocator
-
Returns the indices of the attributes.
- getAttributeIndices() - 接口中的方法 weka.core.DistanceFunction
-
Gets the range of attributes used in the calculation of the distance.
- getAttributeIndices() - 类中的方法 weka.core.NormalizableDistance
-
Gets the range of attributes used in the calculation of the distance.
- getAttributeIndices() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Gets the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Get the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Get the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Gets the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Get the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Gets the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Gets the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Gets the selection of the columns, e.g., first-last or first-3,5-last
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Gets the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Get the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Get the current range selection.
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Get the current range selection
- getAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets the current range selection.
- getAttributeMaxValues() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Returns the array of maximum-values for each attribute
- getAttributeMaxValues() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Returns the array of maximum-values for each attribute
- getAttributeMinValues() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Returns the array of minimum-values for each attribute
- getAttributeMinValues() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Returns the array of minimum-values for each attribute
- getAttributeName() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Get the name of the attribute to be created.
- getAttributeName() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Get the name of the attribute to be created
- getAttributeNamePrefix() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Get the attribute name prefix.
- getAttributeRange() - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Get the range of indices of the attributes used.
- getAttributes() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
- getAttributes() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns a list with the attributes
- getAttributeSelectionMethod() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Gets the method used to select attributes for use in the linear regression.
- getAttributeType() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Gets the type of attribute to generate.
- getAttributeType() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Gets the attribute type to be deleted by the filter.
- getAttributeTypes() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Returns the current attribute - attribute-type relation in use.
- getAttrIndexRange() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
returns the attribute range(s).
- getAttrValue() - 类中的方法 weka.classifiers.rules.JRip.Antd
- getAttsToEliminatePerIteration() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Get the constant rate of attribute elimination per iteration
- getAutoBuild() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getAutoKeyGeneration() - 类中的方法 weka.core.converters.DatabaseSaver
-
Gets whether or not a primary key will be generated automatically.
- getAverage(int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the average of the mean at the given position, if the position is valid, otherwise 0
- getBackground() - 类中的方法 weka.gui.visualize.BMPWriter
-
returns the current background color
- getBackground() - 类中的方法 weka.gui.visualize.JPEGWriter
-
returns the current background color.
- getBackground() - 类中的方法 weka.gui.visualize.PNGWriter
-
returns the current background color
- getBackground() - 类中的方法 weka.gui.visualize.PostscriptGraphics
- getBackup() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns the backup object (may be null if there is no backup.
- getBagSizePercent() - 类中的方法 weka.classifiers.meta.Bagging
-
Gets the size of each bag, as a percentage of the training set size.
- getBagSizePercent() - 类中的方法 weka.classifiers.meta.MetaCost
-
Gets the size of each bag, as a percentage of the training set size.
- getBalanceClass() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Gets whether the class is balanced.
- getBalanced() - 类中的方法 weka.classifiers.functions.Winnow
-
Get the value of Balanced.
- getBallSplitter() - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Returns the BallSplitter algorithm set that would be used by the TopDown BallTree constructor.
- getBallTreeConstructor() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the BallTreeConstructor currently in use.
- getBase() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the base in use for expansion constant.
- getBaseExperiment() - 类中的方法 weka.experiment.RemoteExperiment
-
Get the base experiment used by this remote experiment
- getBean() - 类中的方法 weka.gui.beans.BeanInstance
-
Gets the bean encapsulated in this instance
- getBeanContext() - 类中的方法 weka.gui.beans.AbstractDataSource
-
Return the bean context (if any) that this bean is embedded in
- getBeanContext() - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- getBeanContext() - 类中的方法 weka.gui.beans.DataVisualizer
-
Return the bean context (if any) that this bean is embedded in
- getBeanContext() - 类中的方法 weka.gui.beans.GraphViewer
-
Return the bean context (if any) that this bean is embedded in
- getBeanContext() - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Return the bean context (if any) that this bean is embedded in
- getBeanContext() - 类中的方法 weka.gui.beans.TextViewer
-
Return the bean context (if any) that this bean is embedded in
- getBeanDescriptor() - 类中的方法 weka.gui.beans.AssociatorBeanInfo
-
Get the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.ClassAssignerBeanInfo
- getBeanDescriptor() - 类中的方法 weka.gui.beans.ClassifierBeanInfo
-
Get the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.ClassValuePickerBeanInfo
- getBeanDescriptor() - 类中的方法 weka.gui.beans.ClustererBeanInfo
-
Get the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.CrossValidationFoldMakerBeanInfo
-
Return the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.FilterBeanInfo
-
Get the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo
-
Return the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.LoaderBeanInfo
-
Get the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.PredictionAppenderBeanInfo
-
Return the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.SaverBeanInfo
-
Get the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.SerializedModelSaverBeanInfo
-
Get the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.StripChartBeanInfo
-
Get the bean descriptor for this bean
- getBeanDescriptor() - 类中的方法 weka.gui.beans.TrainTestSplitMakerBeanInfo
-
Get the bean descriptor for this bean
- getBeanInfoInputs() - 类中的方法 weka.gui.beans.MetaBean
- getBeanInfoOutputs() - 类中的方法 weka.gui.beans.MetaBean
- getBeanInfoSubFlow() - 类中的方法 weka.gui.beans.MetaBean
- getBeanInstances() - 类中的静态方法 weka.gui.beans.BeanInstance
-
Return the list of displayed beans
- getBeansInInputs() - 类中的方法 weka.gui.beans.MetaBean
-
Return all the beans in the inputs
- getBeansInOutputs() - 类中的方法 weka.gui.beans.MetaBean
-
Return all the beans in the outputs
- getBeansInSubFlow() - 类中的方法 weka.gui.beans.MetaBean
-
Return all the beans in the sub flow
- getBestClassifier() - 类中的方法 weka.classifiers.meta.GridSearch
-
returns the best Classifier setup
- getBestClassifierIndex() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Get the index of the classifier that was determined as best during cross-validation.
- getBestClassifierOptions() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns (a copy of) the best options found for the classifier.
- getBestCommitteeChunkSize() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get the best committee chunk size
- getBestCommitteeErrorEstimate() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get the best committee's error on the validation data
- getBestCommitteeLLEstimate() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get the best committee's log likelihood on the validation data
- getBestCommitteeSize() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get the number of members in the best committee
- getBestFilter() - 类中的方法 weka.classifiers.meta.GridSearch
-
returns the best filter setup
- getBestgen(ScatterSearchV1.Subset, BitSet) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Evaluate each gen of a BitSet inserted in a Subset and get the most significant for that Subset
- getBestGroup() - 类中的方法 weka.attributeSelection.LFSMethods
- getBestGroupOfSize(int) - 类中的方法 weka.attributeSelection.LFSMethods
- getBestMerit() - 类中的方法 weka.attributeSelection.LFSMethods
- getBeta() - 类中的方法 weka.classifiers.functions.Winnow
-
Get the value of Beta.
- getBias() - 类中的方法 weka.classifiers.BVDecompose
-
Get the calculated bias squared
- getBias() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns bias term value (default 1) No bias term is added if value < 0
- getBias() - 类中的方法 weka.classifiers.misc.VFI
-
Get the value of the bias parameter
- getBiasToUniformClass() - 类中的方法 weka.filters.supervised.instance.Resample
-
Gets the bias towards a uniform class.
- getBIFFile() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Get name of network in BIF file to compare with
- getBIFFile() - 类中的方法 weka.classifiers.bayes.net.search.fixed.FromFile
-
Get name of network in BIF file to read structure from
- getBIFHeader() - 类中的方法 weka.classifiers.bayes.BayesNet
- getBinarizeNumericAttributes() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
get whether numeric attributes are just being binarized.
- getBinarizeNumericAttributes() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
get whether numeric attributes are just being binarized.
- getBinaryAttributesNominal() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Gets if binary attributes are to be treated as nominal ones.
- getBinaryAttributesNominal() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Gets if binary attributes are to be treated as nominal ones.
- getBinarySplits() - 类中的方法 weka.classifiers.rules.PART
-
Get the value of binarySplits.
- getBinarySplits() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of binarySplits.
- getBinarySplits() - 类中的方法 weka.classifiers.trees.J48graft
-
Get the value of binarySplits.
- getBins() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Gets the number of bins numeric attributes will be divided into
- getBins() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Ignored
- getBinSplit() - 类中的方法 weka.classifiers.trees.FT
-
Get the value of binarySplits.
- getBinValue() - 类中的方法 weka.clusterers.XMeans
-
Gets value that represents true in a new numeric attribute.
- getBooleanCols() - 类中的方法 weka.datagenerators.ClusterGenerator
-
returns the range of boolean attributes.
- getBuilder() - 类中的方法 weka.core.xml.XMLDocument
-
returns the DocumentBuilder.
- getBuildLogisticModels() - 类中的方法 weka.classifiers.functions.SMO
-
Get the value of buildLogisticModels.
- getBuildLogisticModels() - 类中的方法 weka.classifiers.mi.MISMO
-
Get the value of buildLogisticModels.
- getBuildRegressionTree() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Get the value of regressionTree.
- getC() - 类中的方法 weka.classifiers.functions.SMO
-
Get the value of C.
- getC() - 类中的方法 weka.classifiers.functions.SMOreg
-
Get the value of C.
- getC() - 类中的方法 weka.classifiers.mi.MISMO
-
Get the value of C.
- getC() - 类中的方法 weka.classifiers.mi.MISVM
-
Get the value of C.
- getCacheHits() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
return the number of kernel cache hits
- getCacheKeyName() - 类中的方法 weka.experiment.DatabaseResultListener
-
Get the value of CacheKeyName.
- getCacheSize() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets cache memory size in MB
- getCacheSize() - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Gets the size of the cache
- getCacheSize() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Gets the size of the cache
- getCacheValues(double) - 类中的方法 weka.classifiers.lazy.kstar.KStarCache
-
Returns the values in the cache mapped by the specified key
- getCalcOutOfBag() - 类中的方法 weka.classifiers.meta.Bagging
-
Get whether the out of bag error is calculated.
- getCalculatedNumToSelect() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Gets the calculated number of attributes to retain.
- getCalculatedNumToSelect() - 类中的方法 weka.attributeSelection.RaceSearch
-
Gets the calculated number of attributes to retain.
- getCalculatedNumToSelect() - 接口中的方法 weka.attributeSelection.RankedOutputSearch
-
Gets the calculated number of attributes to retain.
- getCalculatedNumToSelect() - 类中的方法 weka.attributeSelection.Ranker
-
Gets the calculated number to select.
- getCalculateStdDevs() - 类中的方法 weka.experiment.AveragingResultProducer
-
Get the value of CalculateStdDevs.
- getCanChangeClassInDialog() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns whether the user can change the class in the dialog.
- getCapabilities() - 类中的方法 weka.associations.AbstractAssociator
-
Returns the Capabilities of this associator.
- getCapabilities() - 类中的方法 weka.associations.Apriori
-
Returns default capabilities of the classifier.
- getCapabilities() - 接口中的方法 weka.associations.Associator
-
Returns the Capabilities of this associator.
- getCapabilities() - 类中的方法 weka.associations.FilteredAssociator
-
Returns default capabilities of the associator.
- getCapabilities() - 类中的方法 weka.associations.FPGrowth
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the Capabilities of the algorithm.
- getCapabilities() - 类中的方法 weka.associations.PredictiveApriori
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.associations.SingleAssociatorEnhancer
-
Returns default capabilities of the base associator.
- getCapabilities() - 类中的方法 weka.associations.Tertius
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.attributeSelection.ASEvaluation
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Returns default capabilities of the evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Returns default capabilities of the evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
This method tests what kind of data this classifier can handle.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.HNB
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.NaiveBayesSimple
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.bayes.WAODE
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.Classifier
-
Returns the Capabilities of this classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.IsotonicRegression
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns default capabilities of the classifier, i.e., and "or" of Logistic and LinearRegression.
- getCapabilities() - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.SMO
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns the Capabilities of this kernel.
- getCapabilities() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Returns the Capabilities of this kernel.
- getCapabilities() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Returns the Capabilities of this kernel.
- getCapabilities() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Returns the Capabilities of this kernel.
- getCapabilities() - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Returns the Capabilities of this kernel.
- getCapabilities() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the Capabilities of this kernel.
- getCapabilities() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.lazy.IB1
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.lazy.LBR
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.ClassificationViaRegression
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.END
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.Stacking
-
Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.
- getCapabilities() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.meta.Vote
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MDD
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MIBoost
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MIDD
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MILR
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MINND
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.mi.supportVector.MIPolyKernel
-
Returns the Capabilities of this kernel.
- getCapabilities() - 类中的方法 weka.classifiers.mi.supportVector.MIRBFKernel
-
Returns the Capabilities of this kernel.
- getCapabilities() - 类中的方法 weka.classifiers.misc.HyperPipes
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Returns default capabilities of the base classifier.
- getCapabilities() - 类中的方法 weka.classifiers.misc.VFI
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.MultipleClassifiersCombiner
-
Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.
- getCapabilities() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.DTNB
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.JRip
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.NNge
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.OneR
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.PART
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.part.MakeDecList
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.Prism
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.rules.ZeroR
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.SingleClassifierEnhancer
-
Returns default capabilities of the base classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.DecisionStump
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.FT
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.Id3
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTree
-
Returns default capabilities of the classifier tree.
- getCapabilities() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Returns default capabilities of the classifier tree.
- getCapabilities() - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns default capabilities of the classifier tree.
- getCapabilities() - 类中的方法 weka.classifiers.trees.J48
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.j48.NBTreeClassifierTree
-
Returns default capabilities of the classifier tree.
- getCapabilities() - 类中的方法 weka.classifiers.trees.j48.PruneableClassifierTree
-
Returns default capabilities of the classifier tree.
- getCapabilities() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.LMT
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns default capabilities of the classifier, i.e., of LinearRegression.
- getCapabilities() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.classifiers.trees.UserClassifier
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.clusterers.AbstractClusterer
-
Returns the Capabilities of this clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.CLOPE
-
Returns default capabilities of the clusterer.
- getCapabilities() - 接口中的方法 weka.clusterers.Clusterer
-
Returns the Capabilities of this clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.Cobweb
-
Returns default capabilities of the clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.DBSCAN
-
Returns default capabilities of the clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.EM
-
Returns default capabilities of the clusterer (i.e., the ones of SimpleKMeans).
- getCapabilities() - 类中的方法 weka.clusterers.FarthestFirst
-
Returns default capabilities of the clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.FilteredClusterer
-
Returns default capabilities of the clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.HierarchicalClusterer
- getCapabilities() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns default capabilities of the clusterer (i.e., of the wrapper clusterer).
- getCapabilities() - 类中的方法 weka.clusterers.OPTICS
-
Returns default capabilities of the clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.sIB
-
Returns default capabilities of the clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns default capabilities of the clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.SingleClustererEnhancer
-
Returns default capabilities of the clusterer.
- getCapabilities() - 类中的方法 weka.clusterers.XMeans
-
Returns default capabilities of the clusterer.
- getCapabilities() - 接口中的方法 weka.core.CapabilitiesHandler
-
Returns the capabilities of this object.
- getCapabilities() - 类中的方法 weka.core.converters.AbstractSaver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.converters.ArffSaver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.converters.C45Saver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.converters.CSVSaver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.converters.LibSVMSaver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.converters.SerializedInstancesSaver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.converters.SVMLightSaver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.converters.XRFFSaver
-
Returns the Capabilities of this saver.
- getCapabilities() - 类中的方法 weka.core.FindWithCapabilities
-
The capabilities to search for.
- getCapabilities() - 类中的方法 weka.estimators.DiscreteEstimator
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.estimators.Estimator
-
Returns the Capabilities of this Estimator.
- getCapabilities() - 类中的方法 weka.estimators.KernelEstimator
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.estimators.MahalanobisEstimator
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.estimators.NormalEstimator
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.estimators.PoissonEstimator
-
Returns default capabilities of the classifier.
- getCapabilities() - 类中的方法 weka.filters.AllFilter
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.Filter
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.MultiFilter
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Center
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.NumericToBinary
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Obfuscate
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Returns the capabilities of this evaluator.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.ReplaceMissingValues
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Standardize
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.TimeSeriesDelta
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.TimeSeriesTranslate
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.NonSparseToSparse
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.SparseToNonSparse
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Returns the Capabilities of this filter.
- getCapabilities() - 类中的方法 weka.gui.GenericObjectEditor.CapabilitiesFilterDialog
-
returns the currently selected capabilities.
- getCapabilities(Instances) - 类中的方法 weka.filters.Filter
-
Returns the Capabilities of this filter, customized based on the data.
- getCapabilities(Instances) - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Returns the Capabilities of this filter, makes sure that the class is never set (for the clusterer).
- getCapabilities(Instances) - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Returns the Capabilities of this filter, makes sure that the class is never set (for the clusterer).
- getCapabilitiesFilter() - 类中的方法 weka.gui.ConverterFileChooser
-
returns the capabilities filter for the savers, can be null if all are listed.
- getCapabilitiesFilter() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns the current Capabilities filter, can be null.
- getCar() - 类中的方法 weka.associations.Apriori
-
Gets whether class association ruels are mined
- getCar() - 类中的方法 weka.associations.PredictiveApriori
-
Gets whether class association ruels are mined
- getCardinality() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Gets the cardinality of the attributes (incl class attribute)
- getCardinality(int) - 类中的方法 weka.classifiers.bayes.BayesNet
-
get number of values a node can take
- getCardinalityOfParents() - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
returns cardinality of parents
- getCell(int, int) - 类中的方法 weka.classifiers.CostMatrix
-
Return the contents of a particular cell.
- getCellEditor(int, int) - 类中的方法 weka.gui.arffviewer.ArffTable
-
returns the cell editor for the given cell
- getCells() - 类中的方法 weka.gui.sql.ResultSetHelper
-
returns an 2-dimensional array with the content of the resultset, the first dimension is the row, the second the column (i.e., getCells()[y][x]).
- getCenter() - 类中的方法 weka.gui.treevisualizer.Node
-
Get the value of center.
- getCenterData() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Get whether to center (rather than standardize) the data.
- getCenterData() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Get whether to center (rather than standardize) the data.
- getChangeInWeights() - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
call this function to get the chnage in weights array.
- getChar() - 类中的方法 weka.core.Trie.TrieNode
-
returns the stored character
- getCharSet() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Get the character set to use when reading text files.
- getChecked(int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
returns the checked state of the element at the given index
- getChecked(int) - 类中的方法 weka.gui.CheckBoxList
-
returns the checked state of the element at the given index
- getCheckedIndices() - 类中的方法 weka.gui.CheckBoxList
-
returns an array with the indices of all checked items
- getCheckErrorRate() - 类中的方法 weka.classifiers.rules.JRip
-
Gets whether to check for error rate is in stopping criterion
- getChecksTurnedOff() - 类中的方法 weka.classifiers.functions.SMO
-
Returns whether the checks are turned off or not.
- getChecksTurnedOff() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns whether the checks are turned off or not.
- getChecksTurnedOff() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns whether the checks are turned off or not.
- getChecksTurnedOff() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns whether the checks are turned off or not.
- getChild(int) - 类中的方法 weka.gui.treevisualizer.Node
-
Get the Edge for the child number 'i'.
- getChildForBranch(int) - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Gets the child for a branch of the split.
- getChildForBranch(int) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Gets the child for a branch of the split.
- getChildForBranch(int) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Gets the child for a branch of the split.
- getChildren() - 类中的方法 weka.classifiers.trees.adtree.PredictionNode
-
Gets the children of this node.
- getChildren(int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
return list of children of a node
- getChildTags(Node) - 类中的静态方法 weka.core.xml.XMLDocument
-
returns all non tag-children from the given node.
- getChildTags(Node, String) - 类中的静态方法 weka.core.xml.XMLDocument
-
returns all non tag-children from the given node.
- getChooseClassPopupMenu() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns a popup menu that allows the user to change the class of object.
- getCindex() - 类中的方法 weka.gui.visualize.PlotData2D
-
Get the currently set colouring index of the data
- getCIndex() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Get the index of the attribute selected for coloring
- getClassAttribute() - 类中的方法 weka.gui.beans.ThresholdDataEvent
-
Return the class attribute for which the threshold data was generated for.
- getClassCapabilities() - 类中的方法 weka.core.Capabilities
-
returns all class capabilities
- getClassColumn() - 类中的方法 weka.gui.beans.ClassAssigner
- getClassCounts() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Get the class distribution of the sorted class values.
- getClassesToClusters() - 类中的方法 weka.clusterers.ClusterEvaluation
-
Return the array (ordered by cluster number) of minimum error class to cluster mappings
- getClassFlag() - 类中的方法 weka.datagenerators.ClusterGenerator
-
Gets the class flag.
- getClassForIRStatistics() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Get the value of ClassForIRStatistics.
- getClassification() - 类中的方法 weka.associations.Tertius
-
Get the value of classification.
- getClassifier() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Get the classifier used as the base learner.
- getClassifier() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Get the classifier used as the base learner.
- getClassifier() - 类中的方法 weka.classifiers.BVDecompose
-
Gets the name of the classifier being analysed
- getClassifier() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Gets the name of the classifier being analysed
- getClassifier() - 类中的方法 weka.classifiers.CheckClassifier
-
Get the classifier used as the classifier
- getClassifier() - 类中的方法 weka.classifiers.CheckSource
-
Gets the classifier being used for the tests, can be null.
- getClassifier() - 类中的方法 weka.classifiers.SingleClassifierEnhancer
-
Get the classifier used as the base learner.
- getClassifier() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Get the value of Classifier.
- getClassifier() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Get the value of Classifier.
- getClassifier() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Gets the classifier used by the filter.
- getClassifier() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Gets the classifier used by the filter.
- getClassifier() - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Get the classifier
- getClassifier() - 类中的方法 weka.gui.beans.Classifier
-
Get the classifier currently set for this wrapper
- getClassifier() - 类中的方法 weka.gui.beans.IncrementalClassifierEvent
-
Get the classifier
- getClassifier() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default classifier (fully configured) for the classify panel.
- getClassifier(int) - 类中的方法 weka.classifiers.meta.MultiScheme
-
Gets a single classifier from the set of available classifiers.
- getClassifier(int) - 类中的方法 weka.classifiers.MultipleClassifiersCombiner
-
Gets a single classifier from the set of available classifiers.
- getClassifierCostSensitiveEval() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether the evaluation of the classifier is done cost-sensitively.
- getClassifierCrossvalidationFolds() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default number of folds of the CV in the classify panel.
- getClassifierOutputAdditionalAttributes() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the string with the additional indices to output alongside the predictions.
- getClassifierOutputConfusionMatrix() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether the confusion matrix for the classifier is output.
- getClassifierOutputEntropyEvalMeasures() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether entropy-based evaluation meastures of the classifier are output.
- getClassifierOutputModel() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether the built model is output.
- getClassifierOutputPerClassStats() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether additional per-class stats of the classifier are output.
- getClassifierOutputPredictions() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether the predictions of the classifier are output as well.
- getClassifierOutputSourceCode() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether the source of a sourcable Classifier is output in the classify tab.
- getClassifierPercentageSplit() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default classifier test mode for the classify panel (0-99).
- getClassifierPreserveOrder() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether the order is preserved in case of the percentage split in the classify tab.
- getClassifierRandomSeed() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default random seed value for the classifier for the classify panel.
- getClassifiers() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Gets the list of possible classifers to choose from.
- getClassifiers() - 类中的方法 weka.classifiers.MultipleClassifiersCombiner
-
Gets the list of possible classifers to choose from.
- getClassifierSourceCodeClass() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default classname for a sourcable Classifier in the classify tab.
- getClassifierStorePredictionsForVis() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether the predictions of the classifier are stored for visualization.
- getClassifierTemplate() - 类中的方法 weka.gui.beans.Classifier
-
Return the classifier template currently in use.
- getClassifierTestMode() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default classifier test mode for the classify panel.
- getClassifyIterations() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Gets the number of times an instance is classified
- getClassIndex() - 类中的方法 weka.associations.Apriori
-
Gets the class index
- getClassIndex() - 类中的方法 weka.associations.FilteredAssociator
-
Gets the class index
- getClassIndex() - 类中的方法 weka.associations.PredictiveApriori
-
Gets the index of the class attribute
- getClassIndex() - 类中的方法 weka.associations.Tertius
-
Get the value of classIndex.
- getClassIndex() - 类中的方法 weka.classifiers.BVDecompose
-
Get the index (starting from 1) of the attribute used as the class.
- getClassIndex() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the index (starting from 1) of the attribute used as the class.
- getClassIndex() - 类中的方法 weka.classifiers.CheckSource
-
Gets the class index of the dataset.
- getClassIndex() - 类中的方法 weka.core.converters.LibSVMSaver
-
Get the index of the class attribute.
- getClassIndex() - 类中的方法 weka.core.converters.SVMLightSaver
-
Get the index of the class attribute.
- getClassIndex() - 类中的方法 weka.core.converters.XRFFSaver
-
Get the index of the class attribute.
- getClassIndex() - 类中的方法 weka.core.FindWithCapabilities
-
returns the current current class index, -1 if no class attribute.
- getClassIndex() - 类中的方法 weka.core.TestInstances
-
returns the current class index (0-based), -1 is last attribute
- getClassIndex() - 类中的方法 weka.filters.CheckSource
-
Gets the class index of the dataset.
- getClassIndex() - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
returns the class index.
- getClassIndex() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Gets the attribute on which misclassifications are based.
- getClassMatches(String) - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
returns all the class/package matches with the partial search string.
- getClassname() - 类中的方法 weka.core.Javadoc
-
returns the current classname
- getClassname() - 类中的方法 weka.core.ListOptions
-
returns the current classname
- getClassname(String) - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
returns the classname part of the partial classname.
- getClassName() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Get the class containing the transformation method.
- getClassnames(String) - 类中的静态方法 weka.gui.GenericObjectEditor
-
Returns the available classnames for a certain property in the props file.
- getClassOrder() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Get the wanted class order
- getClassPriors() - 类中的方法 weka.classifiers.Evaluation
-
Get the current weighted class counts
- getClassType() - 类中的方法 weka.core.TestInstances
-
returns the current class type
- getClassValue() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Gets the index of the class value to which SMOTE should be applied.
- getClassValue() - 类中的方法 weka.gui.beans.ClassValuePicker
-
Gets the class value considered to be the "positive" class value.
- getClearEachDataset() - 类中的方法 weka.gui.streams.InstanceViewer
- getClip() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- getClipBounds() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
This returns the full current drawing area
- getClipBounds(Rectangle) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
This returns the full current drawing area
- getClipRect() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- getClock() - 类中的方法 weka.core.Debug
-
returns the instance of the Clock that is internally used
- getClosestConnections(Point, int) - 类中的静态方法 weka.gui.beans.BeanConnection
-
Return a list of connections within some delta of a point
- getClosestConnectorPoint(Point) - 类中的方法 weka.gui.beans.BeanVisual
-
Returns the coordinates of the closest "connector" point to the supplied point.
- getCloseTo() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Get the "close to" number.
- getCloseToDefault() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Get the "close to" default.
- getCloseToTolerance() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Get the "close to" Tolerance.
- getClusterAssignments() - 类中的方法 weka.clusterers.ClusterEvaluation
-
Return an array of cluster assignments corresponding to the most recent set of instances clustered.
- getClusterCenters() - 类中的方法 weka.clusterers.XMeans
-
Return the centers of the clusters as an Instances object
- getClusterCentroids() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets the the cluster centroids
- getClusterDefinitions() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
returns the currently set clusters
- getClusterer() - 类中的方法 weka.attributeSelection.UnsupervisedSubsetEvaluator
-
Get the clusterer
- getClusterer() - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Get the clusterer used as the base learner.
- getClusterer() - 类中的方法 weka.clusterers.CheckClusterer
-
Get the clusterer used as the clusterer
- getClusterer() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Gets the clusterer being wrapped.
- getClusterer() - 类中的方法 weka.clusterers.SingleClustererEnhancer
-
Get the clusterer used as the base clusterer.
- getClusterer() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Get the value of clusterer
- getClusterer() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Gets the clusterer used by the filter.
- getClusterer() - 类中的方法 weka.gui.beans.BatchClustererEvent
-
Get the clusterer
- getClusterer() - 类中的方法 weka.gui.beans.Clusterer
-
Get the clusterer currently set for this wrapper
- getClusterer() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default clusterer (fully configured) for the clusterer panel.
- getClustererStoreClustersForVis() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns whether the clusters are storeed for visualization purposes in the cluster panel.
- getClustererTestMode() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default cluster test mode for the cluster panel.
- getClusteringSeed() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Get the random seed used by K-means.
- getClusterLabel() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Returns the clusterID, to which this DataObject belongs to
- getClusterLabel() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Returns the clusterID, to which this DataObject belongs to
- getClusterLabel() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Returns the clusterID, to which this DataObject belongs to
- getClusterModelsNumericAtts() - 类中的方法 weka.clusterers.EM
-
Return the normal distributions for the cluster models
- getClusterNominalCounts() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns for each cluster the frequency counts for the values of each nominal attribute
- getClusterPriors() - 类中的方法 weka.clusterers.EM
-
Return the priors for the clusters
- getClusterSizes() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets the number of instances in each cluster
- getClusterStandardDevs() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets the standard deviations of the numeric attributes in each cluster
- getClusterSubType() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Gets the cluster sub type.
- getClusterType() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Gets the cluster type.
- getCoef0() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets coef
- getCoefficients() - 类中的方法 weka.core.matrix.LinearRegression
-
returns the calculated coefficients
- getColCount() - 类中的方法 weka.experiment.ResultMatrix
-
returns the number of columns
- getColHidden(int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the hidden status of the column, if the index is valid, otherwise false
- getColName(int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the name of the row, if the index is valid, otherwise null.
- getColNameWidth() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current width for the column names
- getColor() - 类中的方法 weka.gui.treevisualizer.Node
-
Get the value of color.
- getColor() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Get current pen color.
- getColorBox() - 类中的方法 weka.gui.AttributeVisualizationPanel
-
Returns the class selection combo box if the parent component wants to place it in itself or in some component other than this component.
- getColOrder() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current order of the columns, null means the default order
- getColoringIndex() - 类中的方法 weka.gui.AttributeVisualizationPanel
-
Get the coloring (class) index for the plot
- getColoringIndex() - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Return the coloring index for the attribute summary plots
- getColors() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Get the current vector of Color objects used for the classes
- getColumn() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
the comma-separated list of attribute names that identify a column
- getColumn(int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Return a DoubleVector that stores a column of the matrix
- getColumn(int) - 类中的方法 weka.core.Matrix
-
已过时。Gets a column of the matrix and returns it as a double array.
- getColumn(int, int, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Return a DoubleVector that stores some elements of a column of the matrix
- getColumnClass(int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the most specific superclass for all the cell values in the column (always String)
- getColumnClass(int) - 类中的方法 weka.gui.SortedTableModel
-
Returns the most specific superclass for all the cell values in the column.
- getColumnClass(int) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
returns the most specific superclass for all the cell values in the column (always String).
- getColumnClasses() - 类中的方法 weka.gui.sql.ResultSetHelper
-
returns the classes for the columns.
- getColumnCount() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.ResultVectorTableModel
-
Returns the number of columns of this model.
- getColumnCount() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the number of columns in the model
- getColumnCount() - 类中的方法 weka.gui.SortedTableModel
-
Returns the number of columns in the model
- getColumnCount() - 类中的方法 weka.gui.sql.ResultSetHelper
-
returns the number of columns in the resultset.
- getColumnCount() - 类中的方法 weka.gui.sql.ResultSetTableModel
-
returns the number of columns in the model.
- getColumnDimension() - 类中的方法 weka.core.matrix.Matrix
-
Get column dimension.
- getColumnName(int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the name of the column at columnIndex
- getColumnName(int) - 类中的方法 weka.gui.SortedTableModel
-
Returns the name of the column at columnIndex
- getColumnName(int) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
returns the name of the column at columnIndex.
- getColumnNames() - 类中的方法 weka.gui.sql.ResultSetHelper
-
returns an array with the names of the columns in the resultset.
- getColumnPackedCopy() - 类中的方法 weka.core.matrix.Matrix
-
Make a one-dimensional column packed copy of the internal array.
- getCombination() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Get the combination
- getCombinationRule() - 类中的方法 weka.classifiers.meta.Vote
-
Gets the combination rule used
- getCommand() - 类中的方法 weka.gui.treevisualizer.TreeDisplayEvent
- getComment() - enum class中的方法 weka.core.TechnicalInformation.Field
-
returns the comment string
- getComment() - enum class中的方法 weka.core.TechnicalInformation.Type
-
returns the comment string
- getCommonPrefix() - 类中的方法 weka.core.Trie
-
returns the common prefix for all the nodes
- getCommonPrefix() - 类中的方法 weka.core.Trie.TrieNode
-
returns the common prefix for all the nodes starting with this node.
- getCommonPrefix(String) - 类中的方法 weka.core.Trie.TrieNode
-
returns the common prefix for all the nodes starting with the node for the specified prefix.
- getCommonPrefix(Vector<String>) - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
returns the common prefix for all the items in the list.
- getComparisonField() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the name of the field used for comparison
- getCompatibilityState() - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
- getCompatibilityState() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
- getCompatibilityState() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
- getCompatibilityState() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
- getCompatibilityState() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
- getCompatibilityState() - 接口中的方法 weka.experiment.ResultProducer
-
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
- getComplexityParameter() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Get the value of C used with SMO
- getComponent() - 类中的方法 weka.gui.visualize.JComponentWriter
-
returns the component that is stored in the output format
- getComponent() - 类中的方法 weka.gui.visualize.PrintableComponent
-
returns the GUI component this print dialog is part of.
- getComposite() - 类中的方法 weka.gui.visualize.PostscriptGraphics
- getCompressOutput() - 类中的方法 weka.core.converters.ArffSaver
-
Gets whether the output data is compressed.
- getCompressOutput() - 类中的方法 weka.core.converters.XRFFSaver
-
Gets whether the output data is compressed.
- getConfidenceFactor() - 类中的方法 weka.classifiers.rules.PART
-
Get the value of CF.
- getConfidenceFactor() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of CF.
- getConfidenceFactor() - 类中的方法 weka.classifiers.trees.J48graft
-
Get the value of CF.
- getConfirmation() - 类中的方法 weka.associations.tertius.Rule
-
Get the confirmation value of this rule.
- getConfirmationThreshold() - 类中的方法 weka.associations.Tertius
-
Get the value of confirmationThreshold.
- getConfirmationValues() - 类中的方法 weka.associations.Tertius
-
Get the value of confirmationValues.
- getConfirmExit() - 类中的方法 weka.gui.arffviewer.ArffViewer
-
returns the setting of whether to display a confirm messagebox or not on exit
- getConfirmExit() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the setting of whether to display a confirm messagebox or not on exit
- getConfusionMatrix() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Generates a
ConfusionMatrix
representing the current two-class statistics, using class names "negative" and "positive". - getConnectedFormat() - 类中的方法 weka.gui.beans.ClassAssigner
-
Returns the structure of the incoming instances (if any)
- getConnectedFormat() - 类中的方法 weka.gui.beans.ClassValuePicker
-
Returns the structure of the incoming instances (if any)
- getConnection() - 类中的方法 weka.gui.sql.DbUtils
-
returns the current database connection.
- getConnections() - 类中的静态方法 weka.gui.beans.BeanConnection
-
Returns the list of connections
- getConnectorPoint(int) - 类中的方法 weka.gui.beans.BeanVisual
-
Returns the coordinates of the connector point given a compass point
- getConsequence() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get the consequence of this rule.
- getConsequenceSupport() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get the support for the consequence.
- getConsequent() - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Gets the internal representation of the class label to be predicted
- getConsequent() - 类中的方法 weka.classifiers.rules.Rule
-
Get the consequent of this rule, i.e.
- getConservativeForwardSelection() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Gets whether conservative selection has been enabled
- getConstError(double[]) - 类中的方法 weka.classifiers.trees.ft.FTtree
- getContainChildBalls() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Gets whether if a parent ball should completely enclose its two child balls.
- getContent(Element) - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
Returns all TEXT children of the given node in one string.
- getContent(Element) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
XML helper function.
- getContent(Element) - 类中的静态方法 weka.core.xml.XMLDocument
-
returns the text between the opening and closing tag of a node (performs a
trim()
on the result). - getControlPanel() - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
This method returns a handle to the extra controls panel, so that the visualizing class can add it to some of it's own gui panel.
- getControlPanel() - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
This method returns the extra controls panel for the LayoutEngine, if there is any.
- getConvertNominal() - 类中的方法 weka.classifiers.trees.LMT
-
Get the value of convertNominal.
- getConvertNominalToBinary() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Gets whether conversion of nominal to binary is turned on.
- getCoreConvertersOnly() - 类中的方法 weka.gui.ConverterFileChooser
-
Returns whether only the hardcoded core converters are displayed.
- getCoreDistance() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Returns the coreDistance for this dataObject
- getCoreDistance() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Returns the coreDistance for this dataObject
- getCoreDistance() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Returns the coreDistance for this dataObject
- getCost() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the cost parameter C
- getCost() - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets the parameter C of C-SVC, epsilon-SVR, and nu-SVR
- getCostMatrix() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Gets the misclassification cost matrix.
- getCostMatrix() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Gets the misclassification cost matrix.
- getCostMatrix() - 类中的方法 weka.classifiers.meta.MetaCost
-
Gets the misclassification cost matrix.
- getCostMatrixSource() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Gets the source location method of the cost matrix.
- getCostMatrixSource() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Gets the source location method of the cost matrix.
- getCostMatrixSource() - 类中的方法 weka.classifiers.meta.MetaCost
-
Gets the source location method of the cost matrix.
- getCount(double) - 类中的方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Get a counts for a value
- getCount(double) - 类中的方法 weka.estimators.DiscreteEstimator
-
Get the count for a value
- getCount(int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the count for the row.
- getCount(Node, int) - 类中的静态方法 weka.gui.treevisualizer.Node
-
Recursively finds the number of visible nodes there are (this may accidentally count some of the invis nodes).
- getCounterInstancesFrequency() - 类中的方法 weka.associations.tertius.LiteralSet
-
Get the frequency of counter-instances of this LiteralSet in the data.
- getCounterInstancesNumber() - 类中的方法 weka.associations.tertius.LiteralSet
-
Get the number of counter-instances of this LiteralSet.
- getCounts(int[], int[], int[], int, int, boolean) - 类中的方法 weka.classifiers.bayes.net.ADNode
-
get counts for specific instantiation of a set of nodes
- getCounts(int[], int[], int[], int, int, ADNode, boolean) - 类中的方法 weka.classifiers.bayes.net.VaryNode
-
get counts for specific instantiation of a set of nodes
- getCountWidth() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current width for the counts
- getCover() - 类中的方法 weka.classifiers.rules.JRip.Antd
- getCreatorApplication() - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Get the name of the application that created this model
- getCreatorApplication() - 接口中的方法 weka.core.pmml.PMMLModel
-
Get the name of the application that created this model.
- getCriticalValue() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Gets the critical value.
- getCrossoverProb() - 类中的方法 weka.attributeSelection.GeneticSearch
-
get the probability of crossover
- getCrossVal() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Gets the number of folds for cross validation
- getCrossValidate() - 类中的方法 weka.classifiers.lazy.IBk
-
Gets whether hold-one-out cross-validation will be used to select the best k value.
- getCurrent() - 类中的方法 weka.core.Memory
-
returns the currently used size of the JVM heap, obtains a fresh MemoryUsage object to do so.
- getCurrentDatasetNumber() - 类中的方法 weka.experiment.Experiment
-
When an experiment is running, this returns the current dataset number.
- getCurrentDir() - 类中的静态方法 weka.core.Debug
-
returns the current working directory of the user
- getCurrentFilename() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the filename of the current tab
- getCurrentIndex() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the currently selected tab index
- getCurrentInstance() - 类中的方法 weka.gui.beans.IncrementalClassifierEvent
-
Get the current instance
- getCurrentModel() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Gets the currently loaded model (can be null).
- getCurrentPanel() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the currently selected panel
- getCurrentPropertyNumber() - 类中的方法 weka.experiment.Experiment
-
When an experiment is running, this returns the index of the current custom property value.
- getCurrentRunNumber() - 类中的方法 weka.experiment.Experiment
-
When an experiment is running, this returns the current run number.
- getCurve(FastVector) - 类中的方法 weka.classifiers.evaluation.CostCurve
-
Calculates the performance stats for the default class and return results as a set of Instances.
- getCurve(FastVector) - 类中的方法 weka.classifiers.evaluation.MarginCurve
-
Calculates the cumulative margin distribution for the set of predictions, returning the result as a set of Instances.
- getCurve(FastVector) - 类中的方法 weka.classifiers.evaluation.ThresholdCurve
-
Calculates the performance stats for the default class and return results as a set of Instances.
- getCurve(FastVector, int) - 类中的方法 weka.classifiers.evaluation.CostCurve
-
Calculates the performance stats for the desired class and return results as a set of Instances.
- getCurve(FastVector, int) - 类中的方法 weka.classifiers.evaluation.ThresholdCurve
-
Calculates the performance stats for the desired class and return results as a set of Instances.
- getCustomEditor() - 类中的方法 weka.gui.CostMatrixEditor
-
Gets a GUI component with which the user can edit the cost matrix.
- getCustomEditor() - 类中的方法 weka.gui.FileEditor
-
Gets the custom editor component.
- getCustomEditor() - 类中的方法 weka.gui.GenericArrayEditor
-
Returns the array editing component.
- getCustomEditor() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns the array editing component.
- getCustomEditor() - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Gets a GUI component with which the user can edit the date format.
- getCustomHeight() - 类中的方法 weka.gui.visualize.JComponentWriter
-
gets the custom height currently used
- getCustomName() - 类中的方法 weka.gui.beans.Associator
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 接口中的方法 weka.gui.beans.BeanCommon
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.ClassAssigner
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.Classifier
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.ClassValuePicker
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.Clusterer
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.Filter
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.Loader
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.MetaBean
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.PredictionAppender
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.Saver
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.StripChart
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.TestSetMaker
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.TextViewer
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.TrainingSetMaker
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomName() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Get the custom (descriptive) name for this bean (if one has been set)
- getCustomPanel() - 接口中的方法 weka.gui.CustomPanelSupplier
-
Gets the custom panel for the object.
- getCustomPanel() - 类中的方法 weka.gui.GenericObjectEditor
-
Gets the custom panel used for editing the object.
- getCustomWidth() - 类中的方法 weka.gui.visualize.JComponentWriter
-
gets the custom width currently used
- getCutoff() - 类中的方法 weka.clusterers.Cobweb
-
get the cutoff
- getCutOffFactor() - 类中的方法 weka.clusterers.XMeans
-
Gets the cutoff factor.
- getCutPoints(int) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Gets the cut points for an attribute
- getCutPoints(int) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Gets the cut points for an attribute
- getCVisible() - 类中的方法 weka.gui.treevisualizer.Node
-
Get If this node's childs are visible.
- getCVParameter(int) - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Gets the scheme paramter with the given index.
- getCVParameters() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Get method for CVParameters.
- getCVPredictions(Classifier, Instances, int) - 类中的方法 weka.classifiers.evaluation.EvaluationUtils
-
Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset.
- getCVType() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
get cross validation strategy to be used in searching for networks.
- getCycleEnd() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the time/date string the cycle ended
- getCycleStart() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the time/date string the cycle was started
- getD() - 类中的方法 weka.core.matrix.EigenvalueDecomposition
-
Return the block diagonal eigenvalue matrix
- getData() - 类中的方法 weka.attributeSelection.BestFirst.Link2
-
Get a group
- getData() - 类中的方法 weka.attributeSelection.LFSMethods.Link2
-
Get a group
- getData() - 类中的方法 weka.classifiers.rules.RuleStats
-
Get the data of the stats
- getData() - 类中的方法 weka.core.AttributeLocator
-
returns the underlying data
- getData() - 类中的方法 weka.core.converters.ArffLoader.ArffReader
-
Returns the data that was read
- getData() - 类中的方法 weka.core.TestInstances
-
returns the current dataset, can be null
- getDatabase_distanceType() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the distance-type
- getDatabase_distanceType() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the distance-type
- getDatabase_distanceType() - 类中的方法 weka.clusterers.OPTICS
-
Returns the distance-type
- getDatabase_Type() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the type of the used index (database)
- getDatabase_Type() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the type of the used index (database)
- getDatabase_Type() - 类中的方法 weka.clusterers.OPTICS
-
Returns the type of the used index (database)
- getDatabaseOutput() - 类中的方法 weka.clusterers.OPTICS
-
Returns the file to save the database to - if directory, database is not saved.
- getDatabaseSize() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the database's size
- getDatabaseURL() - 类中的方法 weka.experiment.DatabaseUtils
-
Get the value of DatabaseURL.
- getDataDictionary() - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Get the data dictionary.
- getDataFileName() - 类中的方法 weka.classifiers.BVDecompose
-
Get the name of the data file used for the decomposition
- getDataFileName() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the name of the data file used for the decomposition
- getDataObject() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.EpsilonRange_ListElement
-
Returns this dataObject
- getDataObject(String) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Select a dataObject from the database
- getDataObject(String) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Select a dataObject from the database
- getDataPoint() - 类中的方法 weka.gui.beans.ChartEvent
-
Get the data point
- getDataSeqID() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the attribute representing the data sequence ID.
- getDataset() - 类中的方法 weka.classifiers.CheckSource
-
Gets the dataset to use for testing, can be null.
- getDataset() - 类中的方法 weka.filters.CheckSource
-
Gets the dataset to use for testing, can be null.
- getDataSet() - 类中的方法 weka.core.converters.AbstractLoader
- getDataSet() - 类中的方法 weka.core.converters.ArffLoader
-
Return the full data set.
- getDataSet() - 类中的方法 weka.core.converters.C45Loader
-
Return the full data set.
- getDataSet() - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
returns the full dataset, can be null in case of an error.
- getDataSet() - 类中的方法 weka.core.converters.CSVLoader
-
Return the full data set.
- getDataSet() - 类中的方法 weka.core.converters.DatabaseLoader
-
Return the full data set in batch mode (header and all intances at once).
- getDataSet() - 类中的方法 weka.core.converters.LibSVMLoader
-
Return the full data set.
- getDataSet() - 接口中的方法 weka.core.converters.Loader
-
Return the full data set.
- getDataSet() - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Return the full data set.
- getDataSet() - 类中的方法 weka.core.converters.SVMLightLoader
-
Return the full data set.
- getDataSet() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Return the full data set.
- getDataSet() - 类中的方法 weka.core.converters.XRFFLoader
-
Return the full data set.
- getDataSet() - 类中的方法 weka.gui.beans.DataSetEvent
-
Return the instances of the data set
- getDataSet() - 类中的方法 weka.gui.beans.ThresholdDataEvent
-
Return the instances of the data set
- getDataSet() - 类中的方法 weka.gui.beans.VisualizableErrorEvent
-
Return the instances of the data set
- getDataSet(int) - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
returns the full dataset with the specified class index set, can be null in case of an error.
- getDatasetFormat() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the format of the dataset that is to be generated.
- getDatasetKeyColumns() - 类中的方法 weka.experiment.PairedTTester
-
Get the value of DatasetKeyColumns.
- getDatasetKeyColumns() - 接口中的方法 weka.experiment.Tester
-
Get the value of DatasetKeyColumns.
- getDatasets() - 类中的方法 weka.experiment.Experiment
-
Gets the datasets in the experiment.
- getDatasetsFirst() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
whether datasets or algorithms are iterated first
- getDataType() - 类中的方法 weka.gui.beans.xml.XMLBeans
-
returns the type of data that is to be read/written
- getDateAttributes() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the current attribute range to be forced to type date.
- getDateFormat() - 类中的方法 weka.core.Attribute
-
Returns the Date format pattern in case this attribute is of type DATE, otherwise an empty string.
- getDateFormat() - 类中的方法 weka.core.converters.CSVLoader
-
Get the format to use for parsing date values.
- getDateFormat() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Get the date format, complying to ISO-8601.
- getDateFormat() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Get the date format used in output.
- getDbUtils() - 类中的方法 weka.gui.sql.event.ConnectionEvent
-
returns the DbUtils instance that is responsible for the connect/disconnect.
- getDbUtils() - 类中的方法 weka.gui.sql.event.QueryExecuteEvent
-
returns the DbUtils instance that was executed the query
- getDebug() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Get whether debugging is turned on.
- getDebug() - 类中的方法 weka.attributeSelection.RaceSearch
-
Get whether output is to be verbose
- getDebug() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Get whether output is to be verbose
- getDebug() - 类中的方法 weka.classifiers.BVDecompose
-
Gets whether debugging is turned on
- getDebug() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Gets whether debugging is turned on
- getDebug() - 类中的方法 weka.classifiers.Classifier
-
Get whether debugging is turned on.
- getDebug() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns whether or not debugging output shouild be printed
- getDebug() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Controls whether debugging output will be printed
- getDebug() - 类中的方法 weka.classifiers.functions.Logistic
-
Gets whether debugging output will be printed.
- getDebug() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Controls whether debugging output will be printed
- getDebug() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Gets whether debugging output is turned on or not.
- getDebug() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Get whether debugging is turned on
- getDebug() - 类中的方法 weka.classifiers.rules.JRip
-
Gets whether debug information is output to the console
- getDebug() - 类中的方法 weka.clusterers.EM
-
Get debug mode
- getDebug() - 类中的方法 weka.clusterers.HierarchicalClusterer
-
Get whether debugging is turned on.
- getDebug() - 类中的方法 weka.clusterers.sIB
-
Get debug mode
- getDebug() - 类中的方法 weka.core.Check
-
Get whether debugging is turned on
- getDebug() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Gets whether additional debug information is printed.
- getDebug() - 类中的方法 weka.core.Debug.Random
-
returns whether to print the generated random values or not
- getDebug() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the debug flag.
- getDebug() - 类中的方法 weka.estimators.CheckEstimator
-
Get whether debugging is turned on
- getDebug() - 类中的方法 weka.estimators.Estimator
-
Get whether debugging is turned on.
- getDebug() - 类中的方法 weka.experiment.DatabaseUtils
-
Gets whether there should be printed some debugging output to stderr or not.
- getDebug() - 类中的方法 weka.filters.SimpleFilter
-
Returns the current debugging mode state.
- getDebug() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Gets whether debug is set
- getDebug() - 类中的方法 weka.gui.DatabaseConnectionDialog
-
Returns the debug flag
- getDebug() - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
returns whether debug mode is on.
- getDebug() - 类中的方法 weka.gui.streams.InstanceCounter
- getDebug() - 类中的方法 weka.gui.streams.InstanceJoiner
- getDebug() - 类中的方法 weka.gui.streams.InstanceLoader
- getDebug() - 类中的方法 weka.gui.streams.InstanceSavePanel
- getDebug() - 类中的方法 weka.gui.streams.InstanceTable
- getDebug() - 类中的方法 weka.gui.streams.InstanceViewer
- getDebugLevel() - 类中的方法 weka.clusterers.XMeans
-
Gets the debug level.
- getDebugVectorsFile() - 类中的方法 weka.clusterers.XMeans
-
Gets the file name for a file that has the random vectors stored.
- getDecay() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getDecimals() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Get the number of decimals to round to.
- getDefault() - 类中的方法 weka.core.Tee
-
returns the default printstrean, can be NULL.
- getDefaultValue() - 类中的方法 weka.core.pmml.TargetMetaInfo
-
Get the default value (numeric target)
- getDefaultWeight() - 类中的方法 weka.classifiers.functions.Winnow
-
Get the value of defaultWeight.
- getDegree() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets the degree of the kernel
- getDegreesOfFreedom() - 类中的方法 weka.experiment.PairedStats
-
Gets the degrees of freedom.
- getDeleteEmptyBins() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Gets the number of bins numeric attributes will be divided into
- getDelimiters() - 类中的方法 weka.core.tokenizers.CharacterDelimitedTokenizer
-
Get the value of delimiters (not backquoted).
- getDelta() - 类中的方法 weka.associations.Apriori
-
Get the value of delta.
- getDelta() - 类中的方法 weka.associations.FPGrowth
-
Get the value of delta.
- getDelta() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- getDelta() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- getDensityBasedClusterer() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Get the clusterer used by this filter
- getDerivedFields() - 类中的方法 weka.core.pmml.MiningSchema
- getDerivedValue(double[]) - 类中的方法 weka.core.pmml.DerivedFieldMetaInfo
-
Get the derived field value for the given incoming vector of values.
- getDescendantPopulationSize() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- getDescendantPopulationSize() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- getDescription() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERFileFilter
-
The description of this filter.
- getDescription() - 类中的方法 weka.gui.ExtensionFileFilter
-
Gets the description of accepted files.
- getDescription() - 类中的方法 weka.gui.visualize.BMPWriter
-
returns the name of the writer, to display in the FileChooser.
- getDescription() - 类中的方法 weka.gui.visualize.JComponentWriter
-
returns the name of the writer, to display in the FileChooser.
- getDescription() - 类中的方法 weka.gui.visualize.JPEGWriter
-
returns the name of the writer, to display in the FileChooser.
- getDescription() - 类中的方法 weka.gui.visualize.PNGWriter
-
returns the name of the writer, to display in the FileChooser.
- getDescription() - 类中的方法 weka.gui.visualize.PostscriptWriter
-
returns the name of the writer, to display in the FileChooser.
- getDesignatedClass() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Gets the method to determine which class value to optimize.
- getDesignVersion() - 接口中的方法 weka.gui.visualize.plugins.ErrorVisualizePlugin
-
Get the specific version of Weka the class is designed for.
- getDesignVersion() - 接口中的方法 weka.gui.visualize.plugins.GraphVisualizePlugin
-
Get the specific version of Weka the class is designed for.
- getDesignVersion() - 接口中的方法 weka.gui.visualize.plugins.TreeVisualizePlugin
-
Get the specific version of Weka the class is designed for.
- getDesignVersion() - 接口中的方法 weka.gui.visualize.plugins.VisualizePlugin
-
Get the specific version of Weka the class is designed for.
- getDesiredSize() - 类中的方法 weka.classifiers.meta.Decorate
-
Gets the desired size of the committee.
- getDesiredWeightOfInstancesPerInterval() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Get the DesiredWeightOfInstancesPerInterval value.
- getDestination() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the default destination
- getDetectionPerAttribute() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Gets whether an Outlier/ExtremeValue attribute pair is generated for each numeric attribute ("true") or just one pair for all numeric attributes together ("false").
- getDeviceConfiguration() - 类中的方法 weka.gui.visualize.PostscriptGraphics
- getDir() - 类中的方法 weka.core.Javadoc
-
returns the current dir containing the class to update.
- getDir() - 类中的方法 weka.gui.Loader
-
returns the dir prefix
- getDirection() - 类中的方法 weka.attributeSelection.BestFirst
-
Get the search direction
- getDirectory() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
get the Dir specified as the source
- getDirectory() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Get the directory that the model(s) will be saved into
- getDiscretizeBin() - 类中的方法 weka.classifiers.mi.MIBoost
-
Get the number of bins in discretization
- getDiscretizer() - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Return the discretizer used at this node
- getDisplay() - enum class中的方法 weka.core.TechnicalInformation.Field
-
returns the display string
- getDisplay() - enum class中的方法 weka.core.TechnicalInformation.Type
-
returns the display string
- getDisplayCol(int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the displayed index of the given col, depending on the order of columns, returns -1 if index out of bounds
- getDisplayedResultsets() - 类中的方法 weka.experiment.PairedTTester
-
Gets the indices of the the datasets that are displayed (if
null
then all are displayed). - getDisplayedResultsets() - 接口中的方法 weka.experiment.Tester
-
Gets the indices of the the datasets that are displayed (if
null
then all are displayed). - getDisplayModelInOldFormat() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Get whether to display model output in the old, original format.
- getDisplayModelInOldFormat() - 类中的方法 weka.clusterers.EM
-
Get whether to display model output in the old, original format.
- getDisplayName() - 类中的方法 weka.experiment.PairedCorrectedTTester
-
returns the name of the tester
- getDisplayName() - 类中的方法 weka.experiment.PairedTTester
-
returns the name of the tester
- getDisplayName() - 类中的方法 weka.experiment.ResultMatrix
-
returns the name of the output format
- getDisplayName() - 类中的方法 weka.experiment.ResultMatrixCSV
-
returns the name of the output format
- getDisplayName() - 类中的方法 weka.experiment.ResultMatrixGnuPlot
-
returns the name of the output format
- getDisplayName() - 类中的方法 weka.experiment.ResultMatrixHTML
-
returns the name of the output format
- getDisplayName() - 类中的方法 weka.experiment.ResultMatrixLatex
-
returns the name of the output format
- getDisplayName() - 类中的方法 weka.experiment.ResultMatrixPlainText
-
returns the name of the output format
- getDisplayName() - 类中的方法 weka.experiment.ResultMatrixSignificance
-
returns the name of the output format
- getDisplayName() - 接口中的方法 weka.experiment.Tester
-
returns the name of the testing algorithm
- getDisplayRow(int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the displayed index of the given row, depending on the order of rows, returns -1 if index out of bounds
- getDisplayRules() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Gets whether rules are being printed
- getDisplayStdDevs() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets whether standard deviations and nominal count Should be displayed in the clustering output
- getDisplayValue() - 类中的方法 weka.core.pmml.FieldMetaInfo.Value
- getDistance() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.EpsilonRange_ListElement
-
Returns the distance that was calulcated for this dataObject (The distance between this dataObject and the dataObject for which an epsilon-range-query was performed.)
- getDistanceF() - 类中的方法 weka.clusterers.XMeans
-
Gets the distance function.
- getDistanceFunction() - 类中的方法 weka.clusterers.HierarchicalClusterer
- getDistanceFunction() - 类中的方法 weka.clusterers.SimpleKMeans
-
returns the distance function currently in use.
- getDistanceFunction() - 类中的方法 weka.core.neighboursearch.KDTree
-
returns the distance function currently in use.
- getDistanceFunction() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
returns the distance function currently in use.
- getDistanceIsBranchLength() - 类中的方法 weka.clusterers.HierarchicalClusterer
- getDistances() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the distances of the k nearest neighbours.
- getDistances() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the distances of the (k)-NN(s) found earlier by kNearestNeighbours()/nearestNeighbour().
- getDistances() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the distances to the kNearest or 1 nearest neighbour currently found with either the kNearestNeighbours or the nearestNeighbour method.
- getDistances() - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Returns the distances of the k nearest neighbours.
- getDistances() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns the distances of the k nearest neighbours.
- getDistanceWeighting() - 类中的方法 weka.classifiers.lazy.IBk
-
Gets the distance weighting method used.
- getDistMult() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the distance multiplier.
- getDistribution() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns the current distribution that'll be used for calculating the random matrix
- getDistribution(int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)
- getDistribution(String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)
- getDistributions() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Get full set of estimators.
- getDistributions(int) - 类中的方法 weka.classifiers.rules.RuleStats
-
Get the class distribution predicted by the rule in given position
- getDistributionSpread() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Gets the value for the distribution spread
- getDocType() - 类中的方法 weka.core.xml.XMLDocument
-
returns the current DOCTYPE, can be
null
. - getDocument() - 类中的方法 weka.core.xml.XMLDocument
-
returns the parsed DOM document.
- getDocument() - 类中的方法 weka.core.xml.XMLOptions
-
returns the parsed DOM document.
- getDoNotOperateOnPerClassBasis() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Get the DoNotOperateOnPerClassBasis value.
- getDoNotReplaceMissingValues() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Gets whether automatic replacement of missing values is disabled.
- getDoNotReplaceMissingValues() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets whether automatic replacement of missing values is disabled.
- getDoNotWeightBags() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Gets whether the bags are weighted
- getDontFilterAfterFirstBatch() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Get whether to apply the filter to instances that arrive once the first (training) batch has been seen.
- getDontNormalize() - 类中的方法 weka.classifiers.functions.SPegasos
-
Get whether normalization has been turned off.
- getDontNormalize() - 类中的方法 weka.core.NormalizableDistance
-
Gets whether if the attribute values are to be normazlied in distance calculation.
- getDontReplaceMissing() - 类中的方法 weka.classifiers.functions.SPegasos
-
Get whether global replacement of missing values has been disabled.
- getDontReplaceMissingValues() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets whether missing values are to be replaced
- getDoublePivot() - 类中的方法 weka.core.matrix.LUDecomposition
-
Return pivot permutation vector as a one-dimensional double array
- getEditor() - 类中的方法 weka.gui.PropertyDialog
-
Gets the current property editor.
- getEditorActive() - 类中的方法 weka.gui.experiment.GeneratorPropertyIteratorPanel
-
Returns true if the editor is currently in an active status---that is the array is active and able to be edited.
- getElapsedTime() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the elapsed-time
- getElement(int) - 类中的方法 weka.core.AlgVector
-
Returns the value of a cell in the matrix.
- getElement(int, int) - 类中的方法 weka.classifiers.CostMatrix
-
Return the value of a cell as a double (for legacy code)
- getElement(int, int) - 类中的方法 weka.core.Matrix
-
已过时。Returns the value of a cell in the matrix.
- getElement(int, int, Instance) - 类中的方法 weka.classifiers.CostMatrix
-
Return the value of a cell as a double.
- getElementAt(int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Returns the component at the specified index.
- getElements() - 类中的方法 weka.core.AlgVector
-
Gets the elements of the vector and returns them as double array.
- getEliminateColinearAttributes() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Get the value of EliminateColinearAttributes.
- getEnabled() - 类中的方法 weka.core.Debug
-
returns whether the logging is enabled
- getEnclosureCharacters() - 类中的方法 weka.core.converters.CSVLoader
-
Get the character(s) to use/recognize as string enclosures
- getEntropicAutoBlend() - 类中的方法 weka.classifiers.lazy.KStar
-
Get whether entropic blending being used
- getEntry(double) - 类中的方法 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Returns the table entry to which the specified key is mapped in this hashtable.
- getEnumerateColNames() - 类中的方法 weka.experiment.ResultMatrix
-
returns whether column names or numbers instead are enumerateed
- getEnumerateRowNames() - 类中的方法 weka.experiment.ResultMatrix
-
returns whether row names or numbers instead are enumerateed
- getEnvironment() - 类中的方法 weka.gui.beans.FlowRunner
-
Get the environment variables that are in use.
- getEpochs() - 类中的方法 weka.classifiers.functions.SPegasos
-
Get current number of epochs
- getEps() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Gets tolerance of termination criterion
- getEps() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets tolerance of termination criterion
- getEpsilon() - 类中的方法 weka.classifiers.functions.SMO
-
Get the value of epsilon.
- getEpsilon() - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Get the value of epsilon.
- getEpsilon() - 类中的方法 weka.classifiers.mi.MISMO
-
Get the value of epsilon.
- getEpsilon() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the value of epsilon
- getEpsilon() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the value of epsilon
- getEpsilon() - 类中的方法 weka.clusterers.OPTICS
-
Returns the value of epsilon
- getEpsilonParameter() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Get the value of P used with SMO
- getEpsilonParameter() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Get the value of epsilon parameter of the epsilon insensitive loss function.
- getError() - 类中的方法 weka.classifiers.BVDecompose
-
Get the calculated error rate
- getError() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the calculated error rate
- getErrorOnProbabilities() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Get the value of errorOnProbabilities.
- getErrorOnProbabilities() - 类中的方法 weka.classifiers.trees.FT
-
Get the value of errorOnProbabilities.
- getErrorOnProbabilities() - 类中的方法 weka.classifiers.trees.LMT
-
Get the value of errorOnProbabilities.
- getErrors() - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Return the errors made by the naive bayes model at this node
- getErrors() - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Return the errors made by the naive bayes models arising from this split.
- getEstimatedErrorsForLeaf() - 类中的方法 weka.classifiers.rules.part.C45PruneableDecList
-
Computes estimated errors for leaf.
- getEstimator() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Get the BayesNetEstimator used for calculating the CPTs
- getEstimator() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Gets the estimator
- getEstimator() - 类中的方法 weka.estimators.CheckEstimator
-
Get the estimator used as the estimator
- getEstimator(double) - 接口中的方法 weka.estimators.ConditionalEstimator
-
Get a probability estimator for a value
- getEstimator(double) - 类中的方法 weka.estimators.DDConditionalEstimator
-
Get a probability estimator for a value
- getEstimator(double) - 类中的方法 weka.estimators.DKConditionalEstimator
-
Get a probability estimator for a value
- getEstimator(double) - 类中的方法 weka.estimators.DNConditionalEstimator
-
Get a probability estimator for a value
- getEstimator(double) - 类中的方法 weka.estimators.KDConditionalEstimator
-
Get a probability estimator for a value
- getEstimator(double) - 类中的方法 weka.estimators.KKConditionalEstimator
-
Get a probability estimator for a value
- getEstimator(double) - 类中的方法 weka.estimators.NDConditionalEstimator
-
Get a probability estimator for a value
- getEstimator(double) - 类中的方法 weka.estimators.NNConditionalEstimator
-
Get a probability estimator for a value
- getEvaluation() - 类中的方法 weka.classifiers.meta.GridSearch
-
Gets the criterion used for evaluating the classifier performance.
- getEvaluationMeasure() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Gets the currently set performance evaluation measure used for selecting attributes for the decision table
- getEvaluationMode() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Gets the evaluation mode used.
- getEvaluator() - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Get the current evaluator
- getEvaluator() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Get the evaluator used as the base evaluator.
- getEvaluator() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Gets the attribute evaluator used
- getEvaluator() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Get the name of the attribute/subset evaluator
- getEvalUsingTrainingData() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns true if the training data is to be used for evaluation
- getEventName() - 类中的方法 weka.gui.beans.BeanConnection
-
Returns the name of the event for this conncetion
- getEvents() - 类中的方法 weka.associations.gsp.Element
-
Returns the events Array of an Element.
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.AbstractDataSinkBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.AbstractDataSourceBeanInfo
-
Get the event set descriptors pertinent to data sources
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.AbstractTestSetProducerBeanInfo
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.AbstractTrainingSetProducerBeanInfo
-
Returns event set descriptors for this type of bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.AssociatorBeanInfo
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.AttributeSummarizerBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.ClassAssignerBeanInfo
-
Returns the event set descriptors
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.ClassifierBeanInfo
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.ClassValuePickerBeanInfo
-
Returns the event set descriptors
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.ClustererBeanInfo
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.CostBenefitAnalysisBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.DataVisualizerBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.FilterBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.GraphViewerBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.InstanceStreamToBatchMakerBeanInfo
-
Returns the event set descriptors
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.ModelPerformanceChartBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.PredictionAppenderBeanInfo
-
Get the event set descriptors pertinent to data sources
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.ScatterPlotMatrixBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.SerializedModelSaverBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.StripChartBeanInfo
-
Get the event set descriptors for this bean
- getEventSetDescriptors() - 类中的方法 weka.gui.beans.TextViewerBeanInfo
-
Get the event set descriptors for this bean
- getEvidence(int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
get evidence state of a node.
- getException() - 类中的方法 weka.gui.sql.event.ConnectionEvent
-
returns the stored exception, if any (can be NULL)
- getException() - 类中的方法 weka.gui.sql.event.QueryExecuteEvent
-
returns the exception, if one happened, otherwise NULL
- getExclusive() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns whether exclusive expressions for nominal attributes splits are considered
- getExecutionSlots() - 类中的方法 weka.gui.beans.Classifier
-
Get the number of execution slots (threads) used to train models.
- getExecutionStatus() - 类中的方法 weka.experiment.TaskStatusInfo
-
Get the execution status of this Task.
- getExitIfNoWindowsOpen() - 类中的静态方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Gets whether System.exit gets called after the last window gets closed
- getExitOnClose() - 类中的方法 weka.gui.arffviewer.ArffViewer
-
returns TRUE if a System.exit(0) is done on a close
- getExitOnClose() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns TRUE if a System.exit(0) is done on a close
- getExpectedFrequency() - 类中的方法 weka.associations.tertius.Rule
-
Get the expected frequency of counter-instances of this rule.
- getExpectedNumber() - 类中的方法 weka.associations.tertius.Rule
- getExpectedResultsPerAverage() - 类中的方法 weka.experiment.AveragingResultProducer
-
Get the value of ExpectedResultsPerAverage.
- getExperiment() - 类中的方法 weka.experiment.RemoteExperimentSubTask
-
Get the experiment for this sub task
- getExperiment() - 类中的方法 weka.gui.experiment.SetupModePanel
-
Gets the currently configured experiment.
- getExperiment() - 类中的方法 weka.gui.experiment.SetupPanel
-
Gets the currently configured experiment.
- getExperiment() - 类中的方法 weka.gui.experiment.SimpleSetupPanel
-
Gets the currently configured experiment.
- getExperimentType() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the default experiment type
- getExplicitPropsFile() - 类中的方法 weka.gui.GenericPropertiesCreator
-
returns TRUE, if a file is loaded and not the Utils class used for locating the props file.
- getExplorer() - 类中的方法 weka.gui.explorer.AssociationsPanel
-
returns the parent Explorer frame
- getExplorer() - 类中的方法 weka.gui.explorer.AttributeSelectionPanel
-
returns the parent Explorer frame
- getExplorer() - 类中的方法 weka.gui.explorer.ClassifierPanel
-
returns the parent Explorer frame
- getExplorer() - 类中的方法 weka.gui.explorer.ClustererPanel
-
returns the parent Explorer frame
- getExplorer() - 接口中的方法 weka.gui.explorer.Explorer.ExplorerPanel
-
returns the parent Explorer frame
- getExplorer() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
returns the parent Explorer frame
- getExplorer() - 类中的方法 weka.gui.explorer.VisualizePanel
-
returns the parent Explorer frame
- getExponent() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Gets the exponent value.
- getExponent() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Get the value of exponent.
- getExpression() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Gets the mathematical expression for generating y out of x
- getExpression() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Get the expression
- getExpression() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Get the expression
- getExpression() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Returns the expression used for filtering.
- getExpression(String, Node, FieldMetaInfo.Optype, ArrayList<Attribute>, TransformationDictionary) - 类中的静态方法 weka.core.pmml.Expression
-
Static factory method that returns a subclass of Expression that encapsulates the type of expression supplied as an argument.
- getExpression(Node, FieldMetaInfo.Optype, ArrayList<Attribute>, TransformationDictionary) - 类中的静态方法 weka.core.pmml.Expression
-
Static factory method that returns a subclass of Expression that encapsulates the type of expression contained in the Element supplied.
- getExtension() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the default experiment extension
- getExtension() - 类中的方法 weka.gui.visualize.BMPWriter
-
returns the extension (incl.
- getExtension() - 类中的方法 weka.gui.visualize.JComponentWriter
-
returns the extension (incl.
- getExtension() - 类中的方法 weka.gui.visualize.JPEGWriter
-
returns the extension (incl.
- getExtension() - 类中的方法 weka.gui.visualize.PNGWriter
-
returns the extension (incl.
- getExtension() - 类中的方法 weka.gui.visualize.PostscriptWriter
-
returns the extension (incl.
- getExtensions() - 类中的方法 weka.gui.ExtensionFileFilter
-
Returns a copy of the acceptable extensions.
- getExtremeValuesAsOutliers() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Get whether extreme values are also tagged as outliers.
- getExtremeValuesFactor() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Gets the factor for determining the thresholds for extreme values.
- getFactory() - 类中的方法 weka.core.xml.XMLDocument
-
returns the DocumentBuilderFactory.
- getFailReason() - 类中的方法 weka.core.Capabilities
-
returns the reason why the tests failed, is null if tests succeeded
- getFallout() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Calculate the fallout.
- getFalseNegative() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Gets the number of positive instances predicted as negative
- getFalsePositive() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Gets the number of negative instances predicted as positive
- getFalsePositiveRate() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Calculate the false positive rate.
- getFastRegression() - 类中的方法 weka.classifiers.trees.LMT
-
Get the value of fastRegression.
- getFieldAsAttribute() - 类中的方法 weka.core.pmml.DerivedFieldMetaInfo
-
Get this derived field as an Attribute.
- getFieldAsAttribute() - 类中的方法 weka.core.pmml.FieldMetaInfo
-
Return this field as an Attribute.
- getFieldAsAttribute() - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Return this mining field as an Attribute.
- getFieldAsAttribute() - 类中的方法 weka.core.pmml.TargetMetaInfo
-
Return this field as an Attribute.
- getFieldDef(String) - 类中的方法 weka.core.pmml.Expression
-
Return the named attribute from the list of reference fields.
- getFieldDefIndex(String) - 类中的方法 weka.core.pmml.Expression
- getFieldName() - 类中的方法 weka.core.pmml.FieldMetaInfo
-
Get the name of this field.
- getFieldsAsInstances() - 类中的方法 weka.core.pmml.MiningSchema
-
Get the all the fields (both mining schema and derived) as Instances.
- getFieldsMappingString() - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Get a textual description of the mapping between mining schema fields and incoming data fields.
- getFieldsMappingString() - 类中的方法 weka.core.pmml.MappingInfo
-
Get a textual description of them mapping between mining schema fields and incoming data fields.
- getFile() - 类中的方法 weka.gui.visualize.JComponentWriter
-
returns the file being used for storing the output
- getFileDescription() - 类中的方法 weka.core.converters.AbstractFileSaver
-
to be pverridden
- getFileDescription() - 类中的方法 weka.core.converters.ArffLoader
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.ArffSaver
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.C45Loader
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.C45Saver
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.CSVLoader
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.CSVSaver
-
Returns a description of the file type.
- getFileDescription() - 接口中的方法 weka.core.converters.FileSourcedConverter
-
Get a one line description of the type of file
- getFileDescription() - 类中的方法 weka.core.converters.LibSVMLoader
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.LibSVMSaver
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.SerializedInstancesSaver
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.SVMLightLoader
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.SVMLightSaver
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Returns a description of the file type, actually it's directories.
- getFileDescription() - 类中的方法 weka.core.converters.XRFFLoader
-
Returns a description of the file type.
- getFileDescription() - 类中的方法 weka.core.converters.XRFFSaver
-
Returns a description of the file type.
- getFileExtension() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Gets ihe file extension.
- getFileExtension() - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- getFileExtension() - 类中的方法 weka.core.converters.ArffLoader
-
Get the file extension used for arff files
- getFileExtension() - 类中的方法 weka.core.converters.C45Loader
-
Get the file extension used for arff files
- getFileExtension() - 类中的方法 weka.core.converters.CSVLoader
-
Get the file extension used for arff files.
- getFileExtension() - 接口中的方法 weka.core.converters.FileSourcedConverter
-
Get the file extension used for this type of file
- getFileExtension() - 类中的方法 weka.core.converters.LibSVMLoader
-
Get the file extension used for libsvm files.
- getFileExtension() - 接口中的方法 weka.core.converters.Saver
-
Gets the file extension
- getFileExtension() - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Get the file extension used for arff files
- getFileExtension() - 类中的方法 weka.core.converters.SVMLightLoader
-
Get the file extension used for svm light files.
- getFileExtension() - 类中的方法 weka.core.converters.XRFFLoader
-
Get the file extension used for libsvm files
- getFileExtensions() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Gets all the file extensions used for this type of file
- getFileExtensions() - 类中的方法 weka.core.converters.ArffLoader
-
Gets all the file extensions used for this type of file
- getFileExtensions() - 类中的方法 weka.core.converters.ArffSaver
-
Gets all the file extensions used for this type of file
- getFileExtensions() - 类中的方法 weka.core.converters.C45Loader
-
Gets all the file extensions used for this type of file
- getFileExtensions() - 类中的方法 weka.core.converters.CSVLoader
-
Gets all the file extensions used for this type of file.
- getFileExtensions() - 接口中的方法 weka.core.converters.FileSourcedConverter
-
Gets all the file extensions used for this type of file
- getFileExtensions() - 类中的方法 weka.core.converters.LibSVMLoader
-
Gets all the file extensions used for this type of file.
- getFileExtensions() - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Gets all the file extensions used for this type of file
- getFileExtensions() - 类中的方法 weka.core.converters.SVMLightLoader
-
Gets all the file extensions used for this type of file.
- getFileExtensions() - 类中的方法 weka.core.converters.XRFFLoader
-
Gets all the file extensions used for this type of file
- getFileExtensions() - 类中的方法 weka.core.converters.XRFFSaver
-
Gets all the file extensions used for this type of file
- getFileFormat() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Get the file format to use for saving.
- getFileLoaders() - 类中的静态方法 weka.core.converters.ConverterUtils
-
returns a vector with the classnames of all the file loaders.
- getFileMatches(String) - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
returns all the file/dir matches with the partial search string.
- getFileMustExist() - 类中的方法 weka.gui.ConverterFileChooser
-
Returns whether the selected file must exist (only open dialog).
- getFilename() - 类中的方法 weka.core.Debug.Log
-
returns the filename of the log, can be null
- getFilename() - 类中的方法 weka.core.Debug.SimpleLog
-
returns the filename of the log, can be null
- getFilename() - 类中的方法 weka.core.FindWithCapabilities
-
returns the current filename for the dataset to base the capabilities on.
- getFilename() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns the filename
- getFilename(int) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the filename of the specified panel
- getFileName() - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
returns the current filename
- getFileSavers() - 类中的静态方法 weka.core.converters.ConverterUtils
-
returns a vector with the classnames of all the file savers.
- getFillWithMissing() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Gets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).
- getFilter() - 类中的方法 weka.associations.FilteredAssociator
-
Gets the filter used.
- getFilter() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Get the filter to use
- getFilter() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Get the filter to use
- getFilter() - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Get the PLS filter.
- getFilter() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Gets the filter used.
- getFilter() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the kernel filter.
- getFilter() - 类中的方法 weka.clusterers.FilteredClusterer
-
Gets the filter used.
- getFilter() - 类中的方法 weka.filters.CheckSource
-
Gets the filter being used for the tests, can be null.
- getFilter() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Get the preprocessing filter.
- getFilter() - 类中的方法 weka.gui.beans.Filter
- getFilter() - 类中的方法 weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent
-
returns the associated Capabilities filter
- getFilter() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the default filter (fully configured) for the preprocess panel.
- getFilter(int) - 类中的方法 weka.filters.MultiFilter
-
Gets a single filter from the set of available filters.
- getFilter(int) - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Gets a single filter from the set of available filters.
- getFilterAfterFirstBatch() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Get whether to apply the filter to instances that arrive once the first (training) batch has been seen.
- getFilterAttributes() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the String containing the attributes which are used for output filtering.
- getFiltered(int) - 类中的方法 weka.classifiers.rules.RuleStats
-
Get the data after filtering the given rule
- getFilters() - 类中的方法 weka.filters.MultiFilter
-
Gets the list of possible filters to choose from.
- getFilters() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Gets the list of possible filters to choose from.
- getFilterType() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Get the filtering mode passed to SMO
- getFilterType() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Gets how the training data will be transformed.
- getFilterType() - 类中的方法 weka.classifiers.functions.SMO
-
Gets how the training data will be transformed.
- getFilterType() - 类中的方法 weka.classifiers.functions.SMOreg
-
Gets how the training data will be transformed.
- getFilterType() - 类中的方法 weka.classifiers.mi.MDD
-
Gets how the training data will be transformed.
- getFilterType() - 类中的方法 weka.classifiers.mi.MIDD
-
Gets how the training data will be transformed.
- getFilterType() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Gets how the training data will be transformed.
- getFilterType() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Gets how the training data will be transformed.
- getFilterType() - 类中的方法 weka.classifiers.mi.MISMO
-
Gets how the training data will be transformed.
- getFilterType() - 类中的方法 weka.classifiers.mi.MISVM
-
Gets how the training data will be transformed.
- getFindAllRulesForSupportLevel() - 类中的方法 weka.associations.FPGrowth
-
Get whether all rules meeting the lower bound on min support and the minimum metric threshold are to be found.
- getFindNumBins() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Get the value of FindNumBins.
- getFindNumBins() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Get the value of FindNumBins.
- getFirst() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- getFirstToken(StreamTokenizer) - 类中的静态方法 weka.core.converters.ConverterUtils
-
Gets token, skipping empty lines.
- getFirstValueIndex() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Get the index of the first value used.
- getFirstValueIndex() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Get the index of the first value used.
- getFlag(char, String[]) - 类中的静态方法 weka.core.Utils
-
Checks if the given array contains the flag "-Char".
- getFlag(String, String[]) - 类中的静态方法 weka.core.Utils
-
Checks if the given array contains the flag "-String".
- getFlow() - 类中的方法 weka.gui.beans.KnowledgeFlowApp
-
Gets the current flow being edited.
- getFlows() - 类中的方法 weka.gui.beans.FlowRunner
-
Get the vector holding the flow(s)
- getFMeasure() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Calculate the F-Measure.
- getFold() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Gets the fold which is selected.
- getFold() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Gets the fold which is selected.
- getFoldColumn() - 类中的方法 weka.experiment.PairedTTester
-
Get the value of FoldColumn.
- getFoldColumn() - 接口中的方法 weka.experiment.Tester
-
Get the value of FoldColumn.
- getFolds() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Get the number of folds used for cross validation
- getFolds() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Get the number of folds used for accuracy estimation
- getFolds() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
returns the current number of folds
- getFolds() - 类中的方法 weka.classifiers.rules.JRip
-
Gets the number of folds
- getFolds() - 类中的方法 weka.classifiers.rules.Ridor
- getFolds() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Get the currently set number of folds
- getFolds() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the number of folds used for cross-validation
- getFoldsType() - 类中的方法 weka.attributeSelection.RaceSearch
-
Get the xfold type
- getFont() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Get current font.
- getFontMetrics(Font) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Get Font metrics
- getFontRenderContext() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
START overridden Graphics2D methods
- getFormat() - 类中的方法 weka.core.Debug.Timestamp
-
returns the current timestamp format
- getForwardSelectionMethod() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Get the search direction
- getFPRate() - 类中的方法 weka.associations.tertius.Rule
-
Get the rate of False Positive instances of this rule.
- getFrameLocation() - 类中的方法 weka.gui.MemoryUsagePanel
-
Returns the default position for the dialog.
- getFrameTitle() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the title (incl.
- getFrequency() - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
Get the frequency of this item.
- getFrequencyLimit() - 类中的方法 weka.classifiers.bayes.AODE
-
Gets the frequency limit.
- getFrequencyLimit() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Gets the frequency limit.
- getFrequencyThreshold() - 类中的方法 weka.associations.Tertius
-
Get the value of frequencyThreshold.
- getFreshCardinalityOfParents(Instances) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
returns cardinality of parents after recalculation
- getFromYear() - 类中的静态方法 weka.core.Copyright
-
returns the start year of the copyright
- getFunction() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Gets the function for generating the data.
- getFunction(String) - 类中的静态方法 weka.core.pmml.Function
-
Get a built-in PMML Function.
- getFunction(String, TransformationDictionary) - 类中的静态方法 weka.core.pmml.Function
-
Get either a function.
- getFunctionValue(int) - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Gets a particular function value
- getGamma() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets gamma
- getGamma() - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Gets the gamma value.
- getGCount(Node, int) - 类中的静态方法 weka.gui.treevisualizer.Node
-
Recursively finds the number of visible groups of siblings there are.
- getGenerateRanking() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Gets whether ranking has been requested.
- getGenerateRanking() - 类中的方法 weka.attributeSelection.RaceSearch
-
Gets whether ranking has been requested.
- getGenerateRanking() - 接口中的方法 weka.attributeSelection.RankedOutputSearch
-
Gets whether the user has opted to see a ranked list of attributes rather than the normal result of the search
- getGenerateRanking() - 类中的方法 weka.attributeSelection.Ranker
-
This is a dummy method.
- getGenerator() - 类中的方法 weka.gui.explorer.DataGeneratorPanel
-
returns the currently selected DataGenerator
- getGeneratorSamplesBase() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Get the base used for computing the number of samples to obtain from each generator
- getGlobalBlend() - 类中的方法 weka.classifiers.lazy.KStar
-
Get the value of the global blend parameter
- getGlobalInfo(Object) - 类中的静态方法 weka.gui.beans.KnowledgeFlowApp
-
Utility method for grabbing the global info help (if it exists) from an arbitrary object
- getGlobalInfo(Object, boolean) - 类中的静态方法 weka.core.Utils
-
Utility method for grabbing the global info help (if it exists) from an arbitrary object.
- getGlobalModel() - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Return the global naive bayes model for this node
- getGraphString() - 类中的方法 weka.gui.beans.GraphEvent
-
Return the dot string for the graph
- getGraphTitle() - 类中的方法 weka.gui.beans.GraphEvent
-
Return the graph title
- getGraphType() - 类中的方法 weka.gui.beans.GraphEvent
-
Return the graph type
- getGridExtensionsPerformed() - 类中的方法 weka.classifiers.meta.GridSearch
-
returns the number of grid extensions that took place during the search (only applicable if the grid was extendable).
- getGridIsExtendable() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get whether the grid can be extended dynamically.
- getGridWidth() - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Get the width of the grid of plots
- getGroupIdentifier() - 类中的方法 weka.gui.beans.BatchClassifierEvent
- getGUI() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getGUIType() - 类中的方法 weka.gui.Main
-
Gets the currently set type of GUI to display.
- getH() - 类中的方法 weka.core.matrix.QRDecomposition
-
Return the Householder vectors
- getHandler() - 类中的方法 weka.core.FindWithCapabilities
-
returns the current set CapabilitiesHandler to generate the dataset for, can be null.
- getHandler() - 类中的方法 weka.core.TestInstances
-
returns the current set CapabilitiesHandler to generate the dataset for, can be null
- getHashtable(FastVector, int) - 类中的静态方法 weka.associations.ItemSet
-
Return a hashtable filled with the given item sets.
- getHashtable(FastVector, int) - 类中的静态方法 weka.associations.LabeledItemSet
-
Return a hashtable filled with the given item sets.
- getHDRank() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns the rank associated to the Hausdorff distance
- getHeader(String) - 类中的方法 weka.experiment.ResultMatrix
-
returns the value associated with the given key, null if if cannot be found
- getHeight() - 类中的方法 weka.gui.beans.BeanInstance
-
Gets the height of this bean
- getHeight(Node, int) - 类中的静态方法 weka.gui.treevisualizer.Node
-
Recursively finds the number of visible levels there are.
- getHeuristic() - 类中的方法 weka.classifiers.trees.BFTree
-
Get if use heuristic search for nominal attributes in multi-class problems.
- getHeuristic() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Get if use heuristic search for nominal attributes in multi-class problems.
- getHeuristicStop() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Get the value of heuristicStop.
- getHiddenLayers() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getHistory() - 类中的方法 weka.gui.sql.ConnectionPanel
-
returns the history.
- getHistory() - 类中的方法 weka.gui.sql.event.HistoryChangedEvent
-
returns the history model
- getHistory() - 类中的方法 weka.gui.sql.QueryPanel
-
returns the history.
- getHistoryName() - 类中的方法 weka.gui.sql.event.HistoryChangedEvent
-
returns the name of the history
- getHoldOutFile() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Gets the file that holds hold out/test instances.
- getHomeDir() - 类中的静态方法 weka.core.Debug
-
returns the home directory of the user
- getHornClauses() - 类中的方法 weka.associations.Tertius
-
Get the value of hornClauses.
- getHyperparameterRange() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Get the range of hyperparameter values to consider during CV-based selection.
- getHyperparameterSelection() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Get the method used to select the hyperparameter
- getHyperparameterValue() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Get the hyperparameter value.
- getIconPath() - 类中的方法 weka.gui.beans.BeanVisual
-
returns the path for the icon
- getId() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- getID() - 类中的方法 weka.core.Debug.Random
-
returns the unique ID of this number generator
- getID() - 类中的方法 weka.core.Tag
-
Gets the numeric ID of the Tag.
- getID() - 类中的方法 weka.core.TechnicalInformation
-
returns the unique ID (either the one used in creating this instance or the automatically generated one)
- getID() - 类中的方法 weka.gui.streams.InstanceEvent
-
Get the event type
- getID() - 类中的方法 weka.gui.treevisualizer.TreeDisplayEvent
- getIDFTransform() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j. - getIDIndex() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Get the index of the attribute used.
- getIDStr() - 类中的方法 weka.core.Tag
-
Gets the string ID of the Tag.
- getIgnoreClass() - 类中的方法 weka.filters.unsupervised.attribute.PotentialClassIgnorer
-
Gets the IgnoreClass value.
- getIgnoredAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Gets ranges of attributes to be ignored.
- getIgnoredAttributeIndices() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Gets ranges of attributes to be ignored.
- getIgnoredProperties() - 类中的方法 weka.core.CheckGOE
-
Get the ignored properties used in checkToolTips() as comma-separated list (sorted).
- getIgnoreRange() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Get the current range selection.
- getImage(String) - 类中的静态方法 weka.gui.ComponentHelper
-
returns the Image for a given filename, NULL if not successful
- getImage(String, String) - 类中的静态方法 weka.gui.ComponentHelper
-
returns the Image for a given directory and filename, NULL if not successful
- getImageIcon(String) - 类中的静态方法 weka.gui.ComponentHelper
-
returns the ImageIcon for a given filename, NULL if not successful
- getImageIcon(String, String) - 类中的静态方法 weka.gui.ComponentHelper
-
returns the ImageIcon for a given filename and directory, NULL if not successful
- getImagEigenvalues() - 类中的方法 weka.core.matrix.EigenvalueDecomposition
-
Return the imaginary parts of the eigenvalues
- getIncludeClass() - 类中的方法 weka.core.InstanceComparator
-
returns TRUE if the class is included in the comparison
- getIncludeClass() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Gets whether the class is included in the cleaning process or always skipped.
- getIndex() - 类中的方法 weka.associations.tertius.Predicate
- getIndex() - 类中的方法 weka.core.PropertyPath.PathElement
-
returns the index of the property, -1 if the property is not an index-based one
- getIndex() - 类中的方法 weka.core.SingleIndex
-
Gets the selected index
- getIndex() - 类中的方法 weka.gui.SortedTableModel.SortContainer
-
Returns the original index of the item.
- getIndexofBiggest(List<Integer>) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
get the index in a List where this have the biggest number
- getInitAsNaiveBayes() - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
Gets whether to init as naive bayes
- getInitAsNaiveBayes() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Gets whether to init as naive bayes
- getInitAsNaiveBayes() - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
Gets whether to init as naive bayes
- getInitAsNaiveBayes() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Gets whether to init as naive bayes
- getInitFile() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Gets the file to initialize the filter with, can be null.
- getInitFileClassIndex() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Gets the class index of the file to initialize the filter with.
- getInitGenericObjectEditorFilter() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns if the GOEs in the Explorer will be initialized based on the data that is loaded into the Explorer.
- getInitial() - 类中的方法 weka.core.Memory
-
returns the initial size of the JVM heap, obtains a fresh MemoryUsage object to do so.
- getInitialDatasetsDirectory() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the initial directory for the datasets (if empty, it returns the user's home directory)
- getInitialDirectory() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
Returns the initial directory for the file chooser used for opening datasets.
- getInputCenterFile() - 类中的方法 weka.clusterers.XMeans
-
Gets the file to read the list of centers from.
- getInputFilename() - 类中的方法 weka.gui.GenericPropertiesCreator
-
returns the name of the input file
- getInputNums() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Use this to get easy access to the input numbers.
- getInputOrder() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the input order.
- getInputProperties() - 类中的方法 weka.gui.GenericPropertiesCreator
-
returns the input properties object (template containing the packages)
- getInputs() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Use this to get easy access to the inputs.
- getInputs() - 类中的方法 weka.gui.beans.MetaBean
- getInputStream(String) - 类中的方法 weka.gui.Loader
-
returns an InputStream for the given filename, can be NULL if it fails
- getInputStream(String, String) - 类中的静态方法 weka.gui.Loader
-
returns an InputStream for the given dir and filename, can be NULL if it fails
- getInstalledLookAndFeels() - 类中的静态方法 weka.gui.LookAndFeel
-
returns an array with the classnames of all the installed LnFs
- getInstance() - 类中的静态方法 weka.associations.gsp.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.associations.Messages
-
getInstance.
- getInstance() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Returns the original instance
- getInstance() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Returns the original instance
- getInstance() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Returns the original instance
- getInstance() - 类中的静态方法 weka.gui.arffviewer.Messages
-
getInstance.
- getInstance() - 类中的方法 weka.gui.beans.InstanceEvent
-
Get the instance
- getInstance() - 类中的静态方法 weka.gui.beans.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.beans.xml.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.boundaryvisualizer.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.experiment.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.explorer.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.graphvisualizer.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.hierarchyvisualizer.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.sql.event.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.sql.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.streams.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.treevisualizer.Messages
-
getInstance.
- getInstance() - 类中的静态方法 weka.gui.visualize.Messages
-
getInstance.
- getInstanceIndex(int) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the boolean value at the specified index in the Instance Index array
- getInstanceRange() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Gets the number of instances forward to translate values between.
- getInstances() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Returns the original instances delivered from WEKA
- getInstances() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Returns the original instances delivered from WEKA
- getInstances() - 类中的方法 weka.core.converters.AbstractSaver
-
Gets instances that should be stored.
- getInstances() - 接口中的方法 weka.core.DistanceFunction
-
returns the instances currently set.
- getInstances() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
returns the instances currently set.
- getInstances() - 类中的方法 weka.core.NormalizableDistance
-
returns the instances currently set.
- getInstances() - 类中的方法 weka.core.xml.XMLInstances
-
returns the current instances, either the ones that were set or the ones that were generated from the XML structure.
- getInstances() - 类中的方法 weka.experiment.PairedTTester
-
Get the value of Instances.
- getInstances() - 接口中的方法 weka.experiment.Tester
-
Get the value of Instances.
- getInstances() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns the instances of the panel, if none then NULL
- getInstances() - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns the data
- getInstances() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the data
- getInstances() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Get the training instances
- getInstances() - 类中的方法 weka.gui.explorer.DataGeneratorPanel
-
returns the generated instances, null if the process was cancelled.
- getInstances() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Gets the working set of instances.
- getInstances() - 类中的方法 weka.gui.SetInstancesPanel
-
Gets the set of instances currently held by the panel
- getInstances() - 类中的方法 weka.gui.treevisualizer.Node
-
This will return the Instances object related to this node.
- getInstances() - 类中的方法 weka.gui.ViewerDialog
-
returns the currently displayed instances
- getInstances() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Get the master plot's instances
- getInstances1() - 类中的方法 weka.gui.visualize.VisualizePanelEvent
- getInstances2() - 类中的方法 weka.gui.visualize.VisualizePanelEvent
- getInstancesFromClass(Instances, int, double) - 类中的静态方法 weka.estimators.EstimatorUtils
-
Returns a dataset that contains of all instances of a certain class value.
- getInstancesFromClass(Instances, int, int, double, Instances) - 类中的静态方法 weka.estimators.EstimatorUtils
-
Returns a dataset that contains all instances of a certain class value.
- getInstancesFromValue(Instances, int, double) - 类中的静态方法 weka.estimators.EstimatorUtils
-
Returns a dataset that contains of all instances of a certain value for the given attribute.
- getInstancesIndices() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Gets ranges of instances selected.
- getInstancesNoClass() - 类中的方法 weka.associations.Apriori
-
Gets the instances without the class atrribute.
- getInstancesNoClass() - 接口中的方法 weka.associations.CARuleMiner
-
Gets the instances without the class attribute
- getInstancesNoClass() - 类中的方法 weka.associations.PredictiveApriori
-
Gets the instances without the class attribute
- getInstancesOnlyClass() - 类中的方法 weka.associations.Apriori
-
Gets only the class attribute of the instances.
- getInstancesOnlyClass() - 接口中的方法 weka.associations.CARuleMiner
-
Gets the class attribute and its values for all instances
- getInstancesOnlyClass() - 类中的方法 weka.associations.PredictiveApriori
-
Gets the class attribute of all instances
- getInstancesValueAt(int, int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns the double value of the underlying Instances object at the given position, -1 if out of bounds
- getInstancesValueAt(int, int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the double value of the underlying Instances object at the given position, -1 if out of bounds
- getIntercept() - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Returns the intercept of the function.
- getInternalCacheSize() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Gets the size of the internal cache
- getInternals() - 类中的方法 weka.classifiers.bayes.WAODE
-
Gets whether more internals of the classifier are printed.
- getInterpreter() - 类中的方法 weka.core.Jython
-
returns the currently used Python Interpreter
- getInvert() - 类中的方法 weka.core.Range
-
Gets whether the range sense is inverted, i.e.
- getInvert() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Get whether selection is inverted.
- getInvertSelection() - 接口中的方法 weka.core.DistanceFunction
-
Gets whether the matching sense of attribute indices is inverted or not.
- getInvertSelection() - 类中的方法 weka.core.NormalizableDistance
-
Gets whether the matching sense of attribute indices is inverted or not.
- getInvertSelection() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Gets whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.supervised.instance.Resample
-
Gets whether selection is inverted (only if instances are drawn WIHTOUT replacement).
- getInvertSelection() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Gets if selection is to be inverted.
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Get whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Get whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Gets whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Get whether the supplied columns are to be select or unselect
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Gets whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Gets whether the selection of the columns is inverted
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Gets whether the supplied columns are to be worked on or the others.
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Get whether the supplied columns are to be transformed or not
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Gets whether the supplied columns are to be processed or skipped
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Get whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Get whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets whether the supplied columns are to be processed or skipped.
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Gets if selection is to be inverted.
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Get whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Gets if selection is to be inverted.
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Gets if selection is to be inverted.
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Get whether the supplied columns are to be removed or kept
- getInvertSelection() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Gets whether selection is inverted (only if instances are drawn WIHTOUT replacement).
- getJavaInitializationString() - 类中的方法 weka.gui.CostMatrixEditor
-
Returns the Java code that generates an object the same as the one being edited.
- getJavaInitializationString() - 类中的方法 weka.gui.FileEditor
-
Returns a representation of the current property value as java source.
- getJavaInitializationString() - 类中的方法 weka.gui.GenericArrayEditor
-
Supposedly returns an initialization string to create a classifier identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
- getJavaInitializationString() - 类中的方法 weka.gui.GenericObjectEditor
-
Supposedly returns an initialization string to create a Object identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
- getJavaInitializationString() - 类中的方法 weka.gui.SelectedTagEditor
-
Returns a description of the property value as java source.
- getJavaInitializationString() - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Returns the Java code that generates an object the same as the one being edited.
- getJTable() - 类中的方法 weka.gui.JTableHelper
-
returns the JTable
- getKDTree() - 类中的方法 weka.clusterers.XMeans
-
Gets the KDTree class.
- getKernel() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Gets the kernel to use.
- getKernel() - 类中的方法 weka.classifiers.functions.SMO.BinarySMO
-
Returns the kernel to use
- getKernel() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the kernel to use
- getKernel() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns the kernel to use
- getKernel() - 类中的方法 weka.classifiers.functions.supportVector.CheckKernel
-
Get the kernel being tested
- getKernel() - 类中的方法 weka.classifiers.mi.MISMO
-
Gets the kernel to use.
- getKernel() - 类中的方法 weka.classifiers.mi.MISVM
-
Gets the kernel to use.
- getKernel() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Gets the kernel to use.
- getKernelBandwidth() - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
-
Get the kernel bandwidth
- getKernelEvaluations() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
returns the number of kernel evaluations
- getKernelFactorExpression() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Gets the expression for the kernel.
- getKernelMatrixFile() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Gets the file containing the kernel matrix.
- getKernelType() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets type of kernel function
- getKey() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Returns the key for this DataObject
- getKey() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Returns the key for this DataObject
- getKey() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Returns the key for this DataObject
- getKey() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Gets the key describing the current SplitEvaluator.
- getKey() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Gets the key describing the current SplitEvaluator.
- getKey() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Gets the key describing the current SplitEvaluator.
- getKey() - 接口中的方法 weka.experiment.SplitEvaluator
-
Gets the key describing the current SplitEvaluator.
- getKeyFieldName() - 类中的方法 weka.experiment.AveragingResultProducer
-
Get the value of KeyFieldName.
- getKeyNames() - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets the names of each of the columns produced for a single run.
- getKeyNames() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Gets the names of each of the key columns produced for a single run.
- getKeyNames() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets the names of each of the columns produced for a single run.
- getKeyNames() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets the names of each of the columns produced for a single run.
- getKeyNames() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Gets the names of each of the key columns produced for a single run.
- getKeyNames() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets the names of each of the columns produced for a single run.
- getKeyNames() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets the names of each of the columns produced for a single run.
- getKeyNames() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Gets the names of each of the key columns produced for a single run.
- getKeyNames() - 接口中的方法 weka.experiment.ResultProducer
-
Gets the names of each of the key columns produced for a single run.
- getKeyNames() - 接口中的方法 weka.experiment.SplitEvaluator
-
Gets the names of each of the key columns produced for a single run.
- getKeys() - 类中的方法 weka.core.converters.DatabaseLoader
-
Gets the key columns' name
- getKeyTypes() - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getKeyTypes() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Gets the data types of each of the key columns produced for a single run.
- getKeyTypes() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getKeyTypes() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getKeyTypes() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Gets the data types of each of the key columns produced for a single run.
- getKeyTypes() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getKeyTypes() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getKeyTypes() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Gets the data types of each of the key columns produced for a single run.
- getKeyTypes() - 接口中的方法 weka.experiment.ResultProducer
-
Gets the data types of each of the key columns produced for a single run.
- getKeyTypes() - 接口中的方法 weka.experiment.SplitEvaluator
-
Gets the data types of each of the key columns produced for a single run.
- getKeywords() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns the currently stored keywords (as comma-separated list).
- getKeywordsMaskChar() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns the currently set mask character.
- getKNN() - 类中的方法 weka.classifiers.lazy.IBk
-
Gets the number of neighbours the learner will use.
- getKNN() - 类中的方法 weka.classifiers.lazy.LWL
-
Gets the number of neighbours used for kernel bandwidth setting.
- getKValue() - 类中的方法 weka.classifiers.trees.RandomTree
-
Get the value of K.
- getKWBias() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the calculated bias squared according to the Kohavi and Wolpert definition
- getKWSigma() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the calculated sigma according to the Kohavi and Wolpert definition
- getKWVariance() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the calculated variance according to the Kohavi and Wolpert definition
- getL() - 类中的方法 weka.core.matrix.CholeskyDecomposition
-
Return triangular factor.
- getL() - 类中的方法 weka.core.Matrix
-
已过时。Returns the L part of the matrix.
- getL() - 类中的方法 weka.core.matrix.LUDecomposition
-
Return lower triangular factor
- getLabel() - 类中的方法 weka.gui.treevisualizer.Edge
-
Get the value of label.
- getLabel() - 类中的方法 weka.gui.treevisualizer.Node
-
Get the value of label.
- getLabels() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Get the comma-separated list of labels that are added.
- getLambda() - 类中的方法 weka.classifiers.functions.SPegasos
-
Get the current value of lambda
- getLambda() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Gets the lambda constant used in the string kernel
- getLast() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- getLastLiteral() - 类中的方法 weka.associations.tertius.LiteralSet
-
Give the last literal added to this set.
- getLeaf() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- getLearningRate() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getLegendText() - 类中的方法 weka.gui.beans.ChartEvent
-
Get the legend text vector
- getLevel() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Get the level of current node.
- getLikelihoodThreshold() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Get the value of Precision.
- getLine(int) - 类中的方法 weka.gui.treevisualizer.Edge
-
Returns line number n
- getLine(int) - 类中的方法 weka.gui.treevisualizer.Node
-
Returns the text String for the specfied line.
- getLineNo() - 类中的方法 weka.core.converters.ArffLoader.ArffReader
-
returns the current line number
- getLinkAt(int) - 类中的方法 weka.attributeSelection.BestFirst.LinkedList2
-
returns the element (Link) at a specific index from the list.
- getLinkAt(int) - 类中的方法 weka.attributeSelection.LFSMethods.LinkedList2
-
returns the element (Link) at a specific index from the list.
- getLinkType() - 类中的方法 weka.clusterers.HierarchicalClusterer
- getList() - 类中的方法 weka.gui.ResultHistoryPanel
-
Gets the JList used by the results list
- getListCellRendererComponent(JList, Object, int, boolean, boolean) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListRenderer
-
Return a component that has been configured to display the specified value.
- getListCellRendererComponent(JList, Object, int, boolean, boolean) - 类中的方法 weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer
-
Return a component that has been configured to display the specified value.
- getListCellRendererComponent(JList, Object, int, boolean, boolean) - 类中的方法 weka.gui.sql.InfoPanelCellRenderer
-
Return a component that has been configured to display the specified value.
- getLiteral(int) - 类中的方法 weka.associations.tertius.Predicate
- getLNorm() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Get the L Norm used.
- getLoader() - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
returns the determined loader, null if the DataSource was initialized with data alone and not a file/URL.
- getLoader() - 类中的方法 weka.gui.beans.Loader
-
Get the loader
- getLoader() - 类中的方法 weka.gui.ConverterFileChooser
-
returns the loader that was chosen by the user, can be null in case the user aborted the dialog or the save dialog was shown
- getLoader() - 类中的方法 weka.gui.SetInstancesPanel
-
Gets the currently used Loader
- getLoaderForExtension(String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the loader to use for this kind of extension, returns null if none can be found.
- getLoaderForFile(File) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the loader to use for this kind of file, returns null if none can be found.
- getLoaderForFile(String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the loader to use for this kind of file, returns null if none can be found.
- getLocallyPredictive() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Return true if including locally predictive attributes
- getLocator(int) - 类中的方法 weka.core.AttributeLocator
-
Returns the AttributeLocator at the given index.
- getLocatorIndices() - 类中的方法 weka.core.AttributeLocator
-
Returns the indices of the AttributeLocator objects.
- getLog() - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Get the logger.
- getLog() - 类中的方法 weka.core.Debug.Random
-
the currently used log, if null then stdout is used for outputting the debugging information
- getLog() - 接口中的方法 weka.core.pmml.PMMLModel
-
Get the logger.
- getLogFile() - 类中的方法 weka.classifiers.meta.GridSearch
-
Gets current log file.
- getLoglikelihood() - 类中的方法 weka.classifiers.bayes.blr.Prior
- getLoglikeliHood(double[], Instances) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
- getLogLikelihood() - 类中的方法 weka.clusterers.ClusterEvaluation
-
Return the log likelihood corresponding to the most recent set of instances clustered.
- getLogPosterior() - 类中的方法 weka.classifiers.bayes.blr.Prior
- getLogProbForTargetClass(Instance) - 类中的方法 weka.classifiers.bayes.DMNBtext.DNBBinary
-
Calculates the class membership probabilities for the given test instance.
- getLookupCacheSize() - 类中的方法 weka.attributeSelection.BestFirst
-
Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.
- getLookupCacheSize() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.
- getLookupCacheSize() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.
- getLoss() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets the epsilon in loss function of epsilon-SVR
- getLossFunction() - 类中的方法 weka.classifiers.functions.SPegasos
-
Get the current loss function.
- getLower() - 类中的方法 weka.gui.experiment.RunNumberPanel
-
Gets the current lower run number.
- getLowerBoundMinSupport() - 类中的方法 weka.associations.Apriori
-
Get the value of lowerBoundMinSupport.
- getLowerBoundMinSupport() - 类中的方法 weka.associations.FPGrowth
-
Get the value of lowerBoundMinSupport.
- getLowerCaseTokens() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets whether if the tokens are to be downcased or not.
- getLowerNumericBound() - 类中的方法 weka.core.Attribute
-
Returns the lower bound of a numeric attribute.
- getLowerSize() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Get the value of LowerSize.
- getM5RootNode() - 类中的方法 weka.classifiers.trees.m5.M5Base
- getM5RootNode() - 类中的方法 weka.classifiers.trees.m5.Rule
- getMainPanel() - 类中的方法 weka.gui.arffviewer.ArffViewer
-
returns the main panel
- getMajorityClass() - 类中的方法 weka.classifiers.rules.Ridor
- getMakeBinary() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Gets whether binary attributes should be made for discretized ones.
- getMakeBinary() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Gets whether binary attributes should be made for discretized ones.
- getManualThresholdValue() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Returns the value of the manual threshold.
- getMargin(int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
return marginal distibution for a node
- getMargin(int) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
- getMarkovBlanketClassifier() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
- getMarkovBlanketClassifier() - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
- getMasterPlot() - 类中的方法 weka.gui.visualize.Plot2D
-
Get the master plot
- getMatches() - 类中的方法 weka.core.FindWithCapabilities
-
returns the matches from the last find call.
- getMatches(String) - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
returns all the matches with the partial search string, files or classes.
- getMatchMissingValues() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Gets whether missing values are counted as a match.
- getMatrix(int[], int[]) - 类中的方法 weka.core.matrix.Matrix
-
Get a submatrix.
- getMatrix(int[], int, int) - 类中的方法 weka.core.matrix.Matrix
-
Get a submatrix.
- getMatrix(int, int, int[]) - 类中的方法 weka.core.matrix.Matrix
-
Get a submatrix.
- getMatrix(int, int, int, int) - 类中的方法 weka.core.matrix.Matrix
-
Get a submatrix.
- getMax() - 类中的方法 weka.core.Memory
-
returns the maximum size of the JVM heap, obtains a fresh MemoryUsage object to do so.
- getMax() - 类中的方法 weka.gui.beans.ChartEvent
-
Get the max y value
- getMaxArray() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns the calculated maximum values for the attributes in the data.
- getMaxBoostingIterations() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Get the value of maxBoostingIterations.
- getMaxC() - 类中的方法 weka.gui.visualize.Plot2D
-
Return the current max value of the colouring attribute
- getMaxCardinality() - 类中的方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
-
returns the max cardinality
- getMaxCardinality() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Gets the maximum number of values allowed for nominal attributes, before they're skipped.
- getMaxChunkSize() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get the maximum chunk size
- getMaxCoordsPerPoint() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the maximum of coords per point.
- getMaxCost(int) - 类中的方法 weka.classifiers.CostMatrix
-
Gets the maximum cost for a particular class value.
- getMaxCost(int, Instance) - 类中的方法 weka.classifiers.CostMatrix
-
Gets the maximum cost for a particular class value.
- getMaxCount() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Gets the value for the max count
- getMaxDefault() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Get the maximum default.
- getMaxDepth() - 类中的方法 weka.classifiers.trees.RandomForest
-
Get the maximum depth of trh tree, 0 for unlimited.
- getMaxDepth() - 类中的方法 weka.classifiers.trees.RandomTree
-
Get the maximum depth of trh tree, 0 for unlimited.
- getMaxDepth() - 类中的方法 weka.classifiers.trees.REPTree
-
Get the value of MaxDepth.
- getMaxDepth() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the depth of the built tree.
- getMaxGenerations() - 类中的方法 weka.attributeSelection.GeneticSearch
-
get the number of generations
- getMaxGridExtensions() - 类中的方法 weka.classifiers.meta.GridSearch
-
Gets the maximum number of grid extensions, -1 for unlimited.
- getMaxGroup() - 类中的方法 weka.classifiers.meta.RotationForest
-
Gets the maximum size of a group.
- getMaximumAttributeNames() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Gets maximum number of attributes to include in transformed attribute names.
- getMaximumAttributeNames() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Gets maximum number of attributes to include in transformed attribute names.
- getMaximumAttributeNames() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Gets maximum number of attributes to include in transformed attribute names.
- getMaximumAttributes() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Gets maximum number of PC attributes to retain.
- getMaximumVariancePercentageAllowed() - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Gets the maximum variance attributes are allowed to have before they are deleted by the filter.
- getMaxInfoGain() - 类中的方法 weka.classifiers.rules.JRip.Antd
- getMaxInstancesInLeaf() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the maximum number of instances allowed in a leaf.
- getMaxInstInLeaf() - 类中的方法 weka.core.neighboursearch.KDTree
-
Get the maximum number of instances in a leaf.
- getMaxInstNum() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the upper boundary for instances per cluster.
- getMaxInstNum() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Gets the upper boundary for instances per cluster.
- getMaxIntNodesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
returns the maximum of internal nodes visited.
- getMaxIterations() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Get the maximum number of iterations to perform
- getMaxIterations() - 类中的方法 weka.classifiers.mi.MIBoost
-
Get the maximum number of boost iterations
- getMaxIterations() - 类中的方法 weka.classifiers.mi.MISVM
-
Gets the maximum number of iterations.
- getMaxIterations() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Returns the maxIterations parameter.
- getMaxIterations() - 类中的方法 weka.clusterers.EM
-
Get the maximum number of iterations
- getMaxIterations() - 类中的方法 weka.clusterers.sIB
-
Get the max number of iterations
- getMaxIterations() - 类中的方法 weka.clusterers.SimpleKMeans
-
gets the number of maximum iterations to be executed
- getMaxIterations() - 类中的方法 weka.clusterers.XMeans
-
Gets the maximum number of iterations.
- getMaxIterations() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Gets the maximum number of cleansing iterations performed
- getMaxIts() - 类中的方法 weka.classifiers.functions.Logistic
-
Get the value of MaxIts.
- getMaxIts() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Get the value of MaxIts.
- getMaxK() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Get the value of maxK.
- getMaxKMeans() - 类中的方法 weka.clusterers.XMeans
-
Gets the maximum number of iterations in KMeans.
- getMaxKMeansForChildren() - 类中的方法 weka.clusterers.XMeans
-
Gets the maximum number of iterations in KMeans.
- getMaxLeavesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the maximum number of leaves visited.
- getMaxNrOfParents() - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
Gets the max number of parents.
- getMaxNrOfParents() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Gets the max number of parents.
- getMaxNrOfParents() - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
Gets the max number of parents.
- getMaxNrOfParents() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Gets the max number of parents.
- getMaxNrOfParents() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Gets the max number of parents.
- getMaxNumberOfItems() - 类中的方法 weka.associations.FPGrowth
-
Gets the maximum number of items to be included in large item sets.
- getMaxNumClusters() - 类中的方法 weka.clusterers.XMeans
-
Gets the maximum number of clusters to generate.
- getMaxPlots() - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Get the number of plots to display
- getMaxPointsVisited() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the maximum of points visited.
- getMaxRadius() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the upper boundary for the radiuses of the clusters.
- getMaxRange() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Gets the upper boundary for the range of x
- getMaxRelativeLeafRadius() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the maximum relative radius of a leaf node.
- getMaxRows() - 类中的方法 weka.gui.sql.event.QueryExecuteEvent
-
returns the maximum number of rows to retrieve.
- getMaxRows() - 类中的方法 weka.gui.sql.QueryPanel
-
returns the current value for the maximum number of rows.
- getMaxRows() - 类中的方法 weka.gui.sql.ResultSetHelper
-
the maximum number of rows to retrieve, less than 1 means unlimited.
- getMaxRuleSize() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the maximum number of tests in rules.
- getMaxRunNumber() - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Get the maximum run number
- getMaxRunNumber() - 类中的方法 weka.gui.beans.TestSetEvent
-
Get the maximum number of runs.
- getMaxRunNumber() - 类中的方法 weka.gui.beans.TrainingSetEvent
-
Get the maximum number of runs.
- getMaxSetNumber() - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Get the maximum set number (ie the total number of training and testing sets in the series).
- getMaxSetNumber() - 类中的方法 weka.gui.beans.BatchClustererEvent
-
Get the maximum set number (ie the total number of training and testing sets in the series).
- getMaxSetNumber() - 类中的方法 weka.gui.beans.TestSetEvent
-
Get the maximum set number
- getMaxSetNumber() - 类中的方法 weka.gui.beans.TrainingSetEvent
-
Get the maximum set number
- getMaxSubsequenceLength() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the maximum length of the subsequence
- getMaxThreshold() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Get the maximum threshold.
- getMaxValue() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
- getMaxVersion() - 接口中的方法 weka.gui.visualize.plugins.ErrorVisualizePlugin
-
Get the maximum version of Weka, exclusive, the class is designed to work with.
- getMaxVersion() - 接口中的方法 weka.gui.visualize.plugins.GraphVisualizePlugin
-
Get the maximum version of Weka, exclusive, the class is designed to work with.
- getMaxVersion() - 接口中的方法 weka.gui.visualize.plugins.TreeVisualizePlugin
-
Get the maximum version of Weka, exclusive, the class is designed to work with.
- getMaxVersion() - 接口中的方法 weka.gui.visualize.plugins.VisualizePlugin
-
Get the maximum version of Weka, exclusive, the class is designed to work with.
- getMaxX() - 类中的方法 weka.gui.visualize.Plot2D
-
Return the current max value of the attribute plotted on the x axis
- getMaxXBound() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Gets the maximum x-coordinate bound, in training-instance units (not mouse coordinates).
- getMaxY() - 类中的方法 weka.gui.visualize.Plot2D
-
Return the current max value of the attribute plotted on the y axis
- getMaxYBound() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Gets the maximum x-coordinate bound, in training-instance units (not mouse coordinates).
- getMean() - 类中的方法 weka.estimators.NormalEstimator
-
Return the value of the mean of this normal estimator.
- getMean(int, int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the mean at the given position, if the position is valid, otherwise 0
- getMeanCoordsPerPoint() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the mean of coords per point.
- getMeanIntNodesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the mean of internal nodes visited.
- getMeanLeavesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the mean of number of leaves visited.
- getMeanPointsVisited() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the mean of points visited.
- getMeanPrec() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current precision for the means
- getMeanPrec() - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
Gets the precision used for printing the mean.
- getMeanPrecision() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the default precision for the mean
- getMeans() - 类中的方法 weka.estimators.KernelEstimator
-
Return the means of the kernels.
- getMeanSquared() - 类中的方法 weka.classifiers.lazy.IBk
-
Gets whether the mean squared error is used rather than mean absolute error when doing cross-validation.
- getMeanStddev() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
returns the current mean/stddev setup
- getMeanValue() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
- getMeanWidth() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current width for the mean
- getMeasure() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
get measure used for determining threshold
- getMeasure(String) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the value of the named measure from the neighbour search algorithm, plus the chosen K in case cross-validation is enabled.
- getMeasure(String) - 类中的方法 weka.classifiers.lazy.LWL
-
Returns the value of the named measure from the neighbour search algorithm.
- getMeasure(String) - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.meta.Bagging
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.rules.DTNB
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.rules.JRip
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.rules.PART
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.rules.Ridor
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.trees.ADTree
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.trees.FT
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.trees.J48
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.trees.LADTree
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.classifiers.trees.LMT
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.trees.NBTree
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns the value of the named measure.
- getMeasure(String) - 接口中的方法 weka.core.AdditionalMeasureProducer
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the value of the named measure.
- getMeasure(String) - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns the value of the named measure
- getMeasure(String) - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Returns the value of the named measure
- getMeasurePerformance() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Gets whether performance statistics are being calculated or not.
- getMembershipValues(Instance) - 类中的方法 weka.classifiers.trees.RandomTree
-
Computes array that indicates node membership.
- getMenu() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the menu bar to be added in a frame
- getMenuBar() - 类中的方法 weka.classifiers.bayes.net.GUI
-
Get the menu bar for this application.
- getMenuTitle() - 接口中的方法 weka.gui.MainMenuExtension
-
Returns the name of the menu item.
- getMestWeight() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Gets the weight used in m-estimate
- getMetaClassifier() - 类中的方法 weka.classifiers.meta.Stacking
-
Gets the meta classifier.
- getMetadata() - 类中的方法 weka.core.Attribute
-
Returns the properties supplied for this attribute.
- getMetaData() - 类中的方法 weka.core.converters.DatabaseConnection
-
Gets meta data for the database connection object.
- getMethod() - 类中的方法 weka.classifiers.functions.neural.NeuralNode
- getMethod() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Gets the method used.
- getMethod() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Get the method used in testing.
- getMethodName() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Get the transformation method.
- getMetricType() - 类中的方法 weka.associations.Apriori
-
Get the metric type
- getMetricType() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get the metric type of this rule (e.g.
- getMetricType() - 类中的方法 weka.associations.FPGrowth
-
Get the metric type to use.
- getMetricValue() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get the value of the metric for this rule.
- getMiddle(double[]) - 类中的方法 weka.core.EuclideanDistance
-
Returns value in the middle of the two parameter values.
- getMidPoints() - 类中的方法 weka.associations.PriorEstimation
-
returns an ordered array of all mid points
- getMin() - 类中的方法 weka.gui.beans.ChartEvent
-
Get the min y value
- getMinArray() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns the calculated minimum values for the attributes in the data.
- getMinBoxRelWidth() - 类中的方法 weka.core.neighboursearch.KDTree
-
Gets the minimum relative box width.
- getMinBucketSize() - 类中的方法 weka.classifiers.rules.OneR
-
Get the value of minBucketSize.
- getMinC() - 类中的方法 weka.gui.visualize.Plot2D
-
Return the current min value of the colouring attribute
- getMinChange() - 类中的方法 weka.clusterers.sIB
-
get the minimum number of changes
- getMinChunkSize() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get the minimum chunk size
- getMinCoordsPerPoint() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the minimum of coords per point.
- getMinDefault() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Get the minimum default.
- getMinFunction() - 类中的方法 weka.core.Optimization
-
Get the minimal function value
- getMinGroup() - 类中的方法 weka.classifiers.meta.RotationForest
-
Gets the minimum size of a group.
- getMinimax() - 类中的方法 weka.classifiers.mi.MISMO
-
Check if the MIMinimax feature space is to be used.
- getMinimizeExpectedCost() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Gets the value of MinimizeExpectedCost.
- getMinimumBucketSize() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Get the minimum bucket size used by oneR
- getMinimumNumberInstances() - 类中的方法 weka.core.Capabilities
-
returns the minimum number of instances that have to be in the dataset
- getMiningFields() - 类中的方法 weka.core.pmml.MiningSchema
- getMiningSchema() - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Get the mining schema for this model.
- getMiningSchema() - 接口中的方法 weka.core.pmml.PMMLModel
-
Get the mining schema.
- getMiningSchemaAsInstances() - 类中的方法 weka.core.pmml.MiningSchema
-
Get the mining schema fields as an Instances object.
- getMinInstNum() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the lower boundary for instances per cluster.
- getMinInstNum() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Gets the lower boundary for instances per cluster.
- getMinIntNodesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the minimum of internal nodes visited.
- getMinLeavesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the minimum number of leaves visited.
- getMinLevel() - 类中的方法 weka.core.logging.Logger
-
Returns the minimum level log messages must have in order to appear in the log.
- getMinMax(Instances, int, double[]) - 类中的静态方法 weka.estimators.CheckEstimator
-
Find the minimum and the maximum of the attribute and return it in the last parameter..
- getMinMax(Instances, int, double[]) - 类中的静态方法 weka.estimators.EstimatorUtils
-
Find the minimum and the maximum of the attribute and return it in the last parameter..
- getMinMetric() - 类中的方法 weka.associations.Apriori
-
Get the value of minConfidence.
- getMinMetric() - 类中的方法 weka.associations.FPGrowth
-
Get the value of minConfidence.
- getMinNo() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Gets the minimum total weight of the instances in a rule
- getMinNo() - 类中的方法 weka.classifiers.rules.JRip
-
Gets the minimum total weight of the instances in a rule
- getMinNo() - 类中的方法 weka.classifiers.rules.Ridor
- getMinNum() - 类中的方法 weka.classifiers.trees.RandomTree
-
Get the value of MinNum.
- getMinNum() - 类中的方法 weka.classifiers.trees.REPTree
-
Get the value of MinNum.
- getMinNumClusters() - 类中的方法 weka.clusterers.XMeans
-
Gets the minimum number of clusters to generate.
- getMinNumInstances() - 类中的方法 weka.classifiers.trees.FT
-
Get the value of minNumInstances.
- getMinNumInstances() - 类中的方法 weka.classifiers.trees.LMT
-
Get the value of minNumInstances.
- getMinNumInstances() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Get the minimum number of instances to allow at a leaf node
- getMinNumInstances() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Get the minimum number of instances to allow at a leaf node
- getMinNumInstances() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the minimum number of instances to allow at a leaf node
- getMinNumObj() - 类中的方法 weka.classifiers.rules.PART
-
Get the value of minNumObj.
- getMinNumObj() - 类中的方法 weka.classifiers.trees.BFTree
-
Get minimal number of instances at the terminal nodes.
- getMinNumObj() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of minNumObj.
- getMinNumObj() - 类中的方法 weka.classifiers.trees.J48graft
-
Get the value of minNumObj.
- getMinNumObj() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Get minimal number of instances at the terminal nodes.
- getMinPoints() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the value of minPoints
- getMinPoints() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the number of minPoints
- getMinPoints() - 类中的方法 weka.clusterers.OPTICS
-
Returns the value of minPoints
- getMinPointsVisited() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the minimum of points visited.
- getMinRadius() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the lower boundary for the radiuses of the clusters.
- getMinRange() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Gets the lower boundary for the range of x
- getMinRuleSize() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the minimum number of tests in rules.
- getMinStdDev() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Get the MinStdDev value.
- getMinStdDev() - 类中的方法 weka.clusterers.EM
-
Get the minimum allowable standard deviation.
- getMinStdDev() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Get the minimum allowable standard deviation.
- getMinSupport() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the minimum support threshold.
- getMinTermFreq() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Get the MinTermFreq value.
- getMinThreshold() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Get the minimum threshold.
- getMinValue() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
- getMinVarianceProp() - 类中的方法 weka.classifiers.trees.REPTree
-
Get the value of MinVarianceProp.
- getMinVersion() - 接口中的方法 weka.gui.visualize.plugins.ErrorVisualizePlugin
-
Get the minimum version of Weka, inclusive, the class is designed to work with.
- getMinVersion() - 接口中的方法 weka.gui.visualize.plugins.GraphVisualizePlugin
-
Get the minimum version of Weka, inclusive, the class is designed to work with.
- getMinVersion() - 接口中的方法 weka.gui.visualize.plugins.TreeVisualizePlugin
-
Get the minimum version of Weka, inclusive, the class is designed to work with.
- getMinVersion() - 接口中的方法 weka.gui.visualize.plugins.VisualizePlugin
-
Get the minimum version of Weka, inclusive, the class is designed to work with.
- getMinX() - 类中的方法 weka.gui.visualize.Plot2D
-
Return the current min value of the attribute plotted on the x axis
- getMinXBound() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Gets the minimum x-coordinate bound, in training-instance units (not mouse coordinates).
- getMinY() - 类中的方法 weka.gui.visualize.Plot2D
-
Return the current min value of the attribute plotted on the y axis
- getMinYBound() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Gets the minimum y-coordinate bound, in training-instance units (not mouse coordinates).
- getMisses() - 类中的方法 weka.core.FindWithCapabilities
-
returns the misses from the last find call.
- getMissingMerge() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
get whether missing values are being distributed or not
- getMissingMerge() - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
get whether missing values are being distributed or not
- getMissingMerge() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
get whether missing values are being distributed or not
- getMissingMerge() - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
get whether missing values are being distributed or not
- getMissingMode() - 类中的方法 weka.classifiers.lazy.KStar
-
Gets the method to use for handling missing values.
- getMissingSeparate() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Return true is missing is treated as a separate value
- getMissingValue() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the current placeholder for missing values.
- getMissingValues() - 类中的方法 weka.associations.Tertius
-
Get the value of missingValues.
- getMissingValueTreatmentMethod() - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Get the missing value treatment method for this field.
- getMixingDistribution() - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Gets the mixing distribution
- getModel() - 类中的方法 weka.classifiers.functions.LibLINEAR
- getModel() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the linear model at this node
- getModel() - 类中的方法 weka.gui.SortedTableModel
-
returns the current model, can be null
- getModelFile() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Gets the file containing the serialized model.
- getModelParameters() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns a string describing the number of LogitBoost iterations performed at this node, the total number of LogitBoost iterations performed (including iterations at higher levels in the tree), and the number of training examples at this node.
- getModelParameters() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns a string describing the number of LogitBoost iterations performed at this node, the total number of LogitBoost iterations performed (including iterations at higher levels in the tree), and the number of training examples at this node.
- getModelType() - 类中的方法 weka.classifiers.trees.FT
-
Get the type of functional tree model being used.
- getModelValueAt(int, int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns the value at the given position
- getModifyHeader() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Gets whether the header will be modified when selecting on nominal attributes.
- getModifyHeader() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Gets whether the header will be modified when selecting on nominal attributes.
- getMomentum() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getMultiInstance() - 类中的方法 weka.core.TestInstances
-
Gets whether multi-instance data (with a fixed structure) is generated
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MDD
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MIBoost
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MIDD
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MILR
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MINND
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Returns the capabilities of this multi-instance classifier for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.supportVector.MIPolyKernel
-
Returns the capabilities of this multi-instance kernel for the relational data.
- getMultiInstanceCapabilities() - 类中的方法 weka.classifiers.mi.supportVector.MIRBFKernel
-
Returns the capabilities of this multi-instance kernel for the relational data.
- getMultiInstanceCapabilities() - 接口中的方法 weka.core.MultiInstanceCapabilitiesHandler
-
Returns the capabilities of this multi-instance classifier for the relational data (i.e., the bags).
- getMultiInstanceCapabilities() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Returns the capabilities of this multi-instance filter for the relational data (i.e., the bags).
- getMultinomialWord() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Gets whether use binary text representation
- getMutationProb() - 类中的方法 weka.attributeSelection.GeneticSearch
-
get the probability of mutation
- getNaiveBayesModel() - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Get the naive bayes model at this node
- getName() - 类中的方法 weka.classifiers.bayes.BayesNet
-
get name of the Bayes network
- getName() - 类中的方法 weka.core.pmml.Function
- getName() - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Get the name of this field.
- getName() - 类中的方法 weka.core.PropertyPath.PathElement
-
returns the name of the property
- getName() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Returns the name of the new attribute
- getName() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Returns the name associated with this plot.
- getNameAtIndex(int) - 类中的方法 weka.gui.ResultHistoryPanel
-
Gets the name of theitem in the list at the specified index
- getNamedBuffer(String) - 类中的方法 weka.gui.ResultHistoryPanel
-
Gets the named buffer
- getNamedObject(String) - 类中的方法 weka.gui.ResultHistoryPanel
-
Get the named object from the list
- getNearestNeighbors() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Gets the number of nearest neighbors to use.
- getNearestNeighbourSearchAlgorithm() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the current nearestNeighbourSearch algorithm in use.
- getNearestNeighbourSearchAlgorithm() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns the current nearestNeighbourSearch algorithm in use.
- getNegation() - 类中的方法 weka.associations.Tertius
-
Get the value of negation.
- getNegation() - 类中的方法 weka.associations.tertius.Literal
- getNext(int) - 类中的方法 weka.classifiers.functions.supportVector.SMOset
-
Gets the next element in the set.
- getNextDebugVectorsInstance(Instances) - 类中的方法 weka.clusterers.XMeans
-
Read an instance from debug vectors file.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.AbstractLoader
- getNextInstance(Instances) - 类中的方法 weka.core.converters.ArffLoader
-
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.C45Loader
-
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.CSVLoader
-
CSVLoader is unable to process a data set incrementally.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.DatabaseLoader
-
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.LibSVMLoader
-
LibSVmLoader is unable to process a data set incrementally.
- getNextInstance(Instances) - 接口中的方法 weka.core.converters.Loader
-
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.SVMLightLoader
-
SVMLightLoader is unable to process a data set incrementally.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.TextDirectoryLoader
-
TextDirectoryLoader is unable to process a data set incrementally.
- getNextInstance(Instances) - 类中的方法 weka.core.converters.XRFFLoader
-
XRFFLoader is unable to process a data set incrementally.
- getNGramMaxSize() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Gets the max N of the NGram.
- getNGramMinSize() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Gets the min N of the NGram.
- getNoClass() - 类中的方法 weka.core.TestInstances
-
whether no class attribute is generated
- getNode(String) - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
getNode finds the index of the node with name sNodeName and throws an exception if no such node can be found.
- getNode(String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
returns index of node with given name.
- getNode(String) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
- getNode(String) - 类中的方法 weka.core.xml.XMLDocument
-
Returns the node represented by the XPath expression.
- getNode2(String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
returns index of node with given name, or -1 if no such node exists
- getNodeName(int) - 类中的方法 weka.classifiers.bayes.BayesNet
-
get name of a node in the Bayes network
- getNodes() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Return a list of all inner nodes in the tree
- getNodes() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Return a list of all inner nodes in the tree
- getNodes() - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
give access to set of graph nodes
- getNodes() - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
give access to set of graph nodes
- getNodes(Vector) - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Fills a list with all inner nodes in the tree
- getNodes(Vector) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Fills a list with all inner nodes in the tree
- getNodeSplitter() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the splitting method currently in use to split the nodes of the KDTree.
- getNodeValue(int, int) - 类中的方法 weka.classifiers.bayes.BayesNet
-
get name of a particular value of a node
- getNoise() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Get the value of noise.
- getNoisePercent() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Gets the noise percentage.
- getNoiseRate() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Gets the gaussian noise rate.
- getNoiseRate() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the percentage of noise set.
- getNoiseRate() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Gets the percentage of noise set.
- getNoiseThreshold() - 类中的方法 weka.associations.Tertius
-
Get the value of noiseThreshold.
- getNoiseVariance() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Gets the noise variance
- getNominalAttributes() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the current attribute range to be forced to type nominal.
- getNominalCols() - 类中的方法 weka.datagenerators.ClusterGenerator
-
returns the range of nominal attributes
- getNominalIndices() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Get the set of nominal value indices that will be used for selection
- getNominalLabels() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Get the list of labels for nominal attribute creation.
- getNominalToBinaryFilter() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getNoPruning() - 类中的方法 weka.classifiers.trees.REPTree
-
Get the value of NoPruning.
- getNoReplacement() - 类中的方法 weka.filters.supervised.instance.Resample
-
Gets whether instances are drawn with or without replacement.
- getNoReplacement() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Gets whether instances are drawn with or without replacement.
- getNorm() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Get the instance's Norm.
- getNormalize() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Gets whether or not input data is to be normalized
- getNormalize() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
whether to normalize input data
- getNormalize() - 类中的方法 weka.classifiers.functions.LibSVM
-
whether to normalize input data
- getNormalizeAttributes() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getNormalizeDimWidths() - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Whether we are normalizing the widths(ranges) of the dimensions (attributes) or not.
- getNormalizeDocLength() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets whether if the word frequencies for a document (instance) should be normalized or not.
- getNormalizeNodeWidth() - 类中的方法 weka.core.neighboursearch.KDTree
-
Gets the normalize flag.
- getNormalizeNumericClass() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getNormalizeWordWeights() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Returns true if the word weights for each class are to be normalized
- getNot() - 类中的方法 weka.datagenerators.Test
-
Negates the test.
- getNotCapabilities() - 类中的方法 weka.core.FindWithCapabilities
-
The "not to have" capabilities to search for.
- getNotes() - 类中的方法 weka.experiment.Experiment
-
Get the user notes.
- getNotUnifyNorm() - 类中的方法 weka.clusterers.sIB
-
Get whether to normalize instances to unify prior probability before building the clusterer
- getNPointPrecision(Instances, int) - 类中的静态方法 weka.classifiers.evaluation.ThresholdCurve
-
Calculates the n point precision result, which is the precision averaged over n evenly spaced (w.r.t recall) samples of the curve.
- getNrOfGoodOperations() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Gets the number of "good operations"
- getNrOfLookAheadSteps() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Gets the number of look-ahead steps
- getNrOfNodes() - 类中的方法 weka.classifiers.bayes.BayesNet
-
get number of nodes in the Bayes network
- getNrOfParents() - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
returns number of parents
- getNrOfParents(int) - 类中的方法 weka.classifiers.bayes.BayesNet
-
get number of parents of a node in the network structure
- getNu() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)
- getNumAntds() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Gets the number of antecedants
- getNumArcs() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Gets the number of arcs for the bayesian net
- getNumAttemptsOfGeneOption() - 类中的方法 weka.classifiers.rules.NNge
-
Gets the number of attempts for generalisation.
- getNumAttributes() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the number of attributes in the dataset
- getNumAttributes() - 类中的方法 weka.core.TestInstances
-
returns the overall number of attributes (incl.
- getNumAttributes() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Gets the number of attributes that should be produced.
- getNumAttributes() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Gets the number of attributes that should be produced.
- getNumAttributes() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the number of attributes that should be produced.
- getNumAttributes() - 类中的方法 weka.datagenerators.ClusterGenerator
-
Gets the number of attributes that should be produced.
- getNumAttributes() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Get the number of attributes (< 1 percentage, >= 1 absolute number).
- getNumAttributesSet() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the number of attributes "in use"
- getNumberLiterals() - 类中的方法 weka.associations.Tertius
-
Get the value of numberLiterals.
- getNumberOfAttributes() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the number of Attributes of the specified database
- getNumberOfAttributes() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Gets the current number of attributes (dimensionality) to which the data will be reduced to.
- getNumberOfGeneratedClusters() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the number of generated clusters
- getNumberOfGroups() - 类中的方法 weka.classifiers.meta.RotationForest
-
Get whether minGroup and maxGroup refer to the number of groups or their size
- getNumBins() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Gets the number of bins numeric attributes will be divided into
- getNumBoostingIterations() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Get the value of numBoostingIterations.
- getNumBoostingIterations() - 类中的方法 weka.classifiers.trees.FT
-
Get the value of numBoostingIterations.
- getNumBoostingIterations() - 类中的方法 weka.classifiers.trees.LMT
-
Get the value of numBoostingIterations.
- getNumCentroids() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Gets the number of centroids.
- getNumCiters() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns the number of citers considered to estimate the class prediction of tests bags
- getNumClasses() - 类中的方法 weka.core.TestInstances
-
returns the current number of classes
- getNumClasses() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Gets the number of classes the dataset should have.
- getNumClasses() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the number of classes the dataset should have.
- getNumClusters() - 类中的方法 weka.attributeSelection.UnsupervisedSubsetEvaluator
-
Return the number of clusters used by the subset evaluator
- getNumClusters() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Return the number of clusters to generate.
- getNumClusters() - 类中的方法 weka.clusterers.ClusterEvaluation
-
Return the number of clusters found for the most recent call to evaluateClusterer
- getNumClusters() - 类中的方法 weka.clusterers.EM
-
Get the number of clusters
- getNumClusters() - 类中的方法 weka.clusterers.FarthestFirst
-
gets the number of clusters to generate
- getNumClusters() - 类中的方法 weka.clusterers.HierarchicalClusterer
- getNumClusters() - 类中的方法 weka.clusterers.sIB
-
Get the number of clusters
- getNumClusters() - 类中的方法 weka.clusterers.SimpleKMeans
-
gets the number of clusters to generate
- getNumClusters() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the number of clusters the dataset should have.
- getNumComponents() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
returns the maximum number of attributes to use.
- getNumCycles() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the number of cycles.
- getNumDatasets() - 类中的方法 weka.experiment.PairedTTester
-
Gets the number of datasets in the resultsets
- getNumDatasets() - 接口中的方法 weka.experiment.Tester
-
Gets the number of datasets in the resultsets
- getNumDate() - 类中的方法 weka.core.CheckScheme
-
returns the current number of date attributes
- getNumDate() - 类中的方法 weka.core.TestInstances
-
returns the current number of date attributes
- getNumeric() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Check if new attribute is to be numeric.
- getNumericColumns() - 类中的方法 weka.gui.sql.ResultSetHelper
-
returns an array that indicates whether a column is numeric or nor.
- getNumEvalsCached() - 类中的方法 weka.attributeSelection.LFSMethods
- getNumEvalsTotal() - 类中的方法 weka.attributeSelection.LFSMethods
- getNumExamples() - 类中的方法 weka.datagenerators.ClassificationGenerator
-
Gets the number of examples, given by option.
- getNumExamples() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Gets the number of examples, given by option.
- getNumExamples() - 类中的方法 weka.datagenerators.RegressionGenerator
-
Gets the number of examples, given by option.
- getNumExamplesAct() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the number of examples the dataset should have.
- getNumFeatures() - 类中的方法 weka.classifiers.trees.RandomForest
-
Get the number of features used in random selection.
- getNumFiles() - 类中的方法 weka.core.Debug.Log
-
returns the number of files being used
- getNumFoldersMIOption() - 类中的方法 weka.classifiers.rules.NNge
-
Gets the number of folder for mutual information.
- getNumFolds() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Return the number of folds for CV-based hyperparameter selection
- getNumFolds() - 类中的方法 weka.classifiers.functions.SMO
-
Get the value of numFolds.
- getNumFolds() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Gets the number of folds for the cross-validation.
- getNumFolds() - 类中的方法 weka.classifiers.meta.Dagging
-
Gets the number of folds to use for splitting the training set.
- getNumFolds() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Get the value of NumFolds.
- getNumFolds() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Gets the number of folds for cross-validation.
- getNumFolds() - 类中的方法 weka.classifiers.meta.Stacking
-
Gets the number of folds for the cross-validation.
- getNumFolds() - 类中的方法 weka.classifiers.mi.MISMO
-
Get the value of numFolds.
- getNumFolds() - 类中的方法 weka.classifiers.rules.PART
-
Get the value of numFolds.
- getNumFolds() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of numFolds.
- getNumFolds() - 类中的方法 weka.classifiers.trees.RandomTree
-
Get the value of NumFolds.
- getNumFolds() - 类中的方法 weka.classifiers.trees.REPTree
-
Get the value of NumFolds.
- getNumFolds() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Get the value of NumFolds.
- getNumFolds() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Gets the number of folds in which dataset is to be split into.
- getNumFolds() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Gets the number of folds in which dataset is to be split into.
- getNumFolds() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Gets the number of cross-validation folds used by the filter.
- getNumFoldsPruning() - 类中的方法 weka.classifiers.trees.BFTree
-
Set number of folds in internal cross-validation.
- getNumFoldsPruning() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Set number of folds in internal cross-validation.
- getNumGeneratingModels() - 接口中的方法 weka.gui.boundaryvisualizer.DataGenerator
-
Returns the number of generating models used by this DataGenerator
- getNumGeneratingModels() - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
-
Return the number of kernels (there is one per training instance)
- getNumInnerNodes() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Method to count the number of inner nodes in the tree
- getNumInnerNodes() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Method to count the number of inner nodes in the tree
- getNumInputs() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- getNumInstances() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the number of instances in the dataset
- getNumInstances() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Return the number of instances that reach this node.
- getNumInstances() - 类中的方法 weka.core.CheckScheme
-
Gets the current number of instances to use for the datasets.
- getNumInstances() - 类中的方法 weka.core.TestInstances
-
returns the current number of instances to produce
- getNumInstances() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
- getNumInstances() - 类中的方法 weka.estimators.CheckEstimator
-
Gets the current number of instances to use for the datasets.
- getNumInstancesRelational() - 类中的方法 weka.core.CheckScheme
-
returns the current number of instances in relational/bag attributes to produce
- getNumInstancesRelational() - 类中的方法 weka.core.TestInstances
-
returns the current number of instances in relational/bag attributes to produce
- getNumInstancesSet() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the number of instances "in use"
- getNumIrrelevant() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the number of irrelevant attributes.
- getNumIterations() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Gets the number of iterations to be performed
- getNumIterations() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Get the value of NumIterations.
- getNumIterations() - 类中的方法 weka.classifiers.functions.Winnow
-
Get the value of numIterations.
- getNumIterations() - 类中的方法 weka.classifiers.IteratedSingleClassifierEnhancer
-
Gets the number of bagging iterations
- getNumIterations() - 类中的方法 weka.classifiers.meta.MetaCost
-
Gets the number of bagging iterations
- getNumKernels() - 类中的方法 weka.estimators.KernelEstimator
-
Return the number of kernels in this kernel estimator
- getNumLeaves() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns the number of leaves in the tree.
- getNumLeaves() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns the number of leaves in the tree.
- getNumLeaves() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the number of leaves in the built tree.
- getNumNeighbours() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Get the number of nearest neighbours
- getNumNeighbours() - 类中的方法 weka.classifiers.mi.MINND
-
Returns the number of nearest neighbours to estimate the class prediction of tests bags
- getNumNodes() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the number of nodes (internal + leaf) in the built tree.
- getNumNominal() - 类中的方法 weka.core.CheckScheme
-
returns the current number of nominal attributes
- getNumNominal() - 类中的方法 weka.core.TestInstances
-
returns the current number of nominal attributes
- getNumNominalValues() - 类中的方法 weka.core.TestInstances
-
returns the current number of values for nominal attributes
- getNumNumeric() - 类中的方法 weka.core.CheckScheme
-
returns the current number of numeric attributes
- getNumNumeric() - 类中的方法 weka.core.TestInstances
-
returns the current number of numeric attributes
- getNumNumeric() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the number of numerical attributes.
- getNumOfBoostingIterations() - 类中的方法 weka.classifiers.trees.ADTree
-
Gets the number of boosting iterations.
- getNumOfBoostingIterations() - 类中的方法 weka.classifiers.trees.LADTree
-
Gets the number of boosting iterations.
- getNumOfBranches() - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Gets the number of branches of the split.
- getNumOfBranches() - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Gets the number of branches of the split.
- getNumOfBranches() - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Gets the number of branches of the split.
- getNumOutputs() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- getNumQueries() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the number of queries.
- getNumReferences() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns the number of references considered to estimate the class prediction of tests bags
- getNumRegressions() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Get the number of LogitBoost iterations performed (= the number of regression functions fit by LogitBoost).
- getNumRegressions() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
The number of LogitBoost iterations performed (= the number of simple regression functions fit).
- getNumRelational() - 类中的方法 weka.core.CheckScheme
-
returns the current number of relational attributes
- getNumRelational() - 类中的方法 weka.core.TestInstances
-
returns the current number of relational attributes
- getNumRelationalDate() - 类中的方法 weka.core.TestInstances
-
returns the current number of date attributes in a relational attribute
- getNumRelationalNominal() - 类中的方法 weka.core.TestInstances
-
returns the current number of nominal attributes in a relational attribute
- getNumRelationalNominalValues() - 类中的方法 weka.core.TestInstances
-
returns the current number of values for nominal attributes in a relational attribute
- getNumRelationalNumeric() - 类中的方法 weka.core.TestInstances
-
returns the current number of numeric attributes in a relational attribute
- getNumRelationalString() - 类中的方法 weka.core.TestInstances
-
returns the current number of string attributes in a relational attribute
- getNumRestarts() - 类中的方法 weka.clusterers.sIB
-
Get the number of restarts
- getNumResultsets() - 类中的方法 weka.experiment.PairedTTester
-
Gets the number of resultsets in the data.
- getNumResultsets() - 接口中的方法 weka.experiment.Tester
-
Gets the number of resultsets in the data.
- getNumRules() - 类中的方法 weka.associations.Apriori
-
Get the value of numRules.
- getNumRules() - 类中的方法 weka.associations.PredictiveApriori
-
Get the value of the number of required rules.
- getNumRulesToFind() - 类中的方法 weka.associations.FPGrowth
-
Get the number of rules to find.
- getNumRuns() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Get the value of NumRuns.
- getNumSamplesPerRegion() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Get the number of points to sample from a region (fixed dimensions).
- getNumString() - 类中的方法 weka.core.CheckScheme
-
returns the current number of string attributes
- getNumString() - 类中的方法 weka.core.TestInstances
-
returns the current number of string attributes
- getNumSubCmtys() - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Get the number of sub committees to use
- getNumSubsetSizeCVFolds() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Get the number of cross validation folds for subset size determination (default = 5).
- getNumSymbols() - 类中的方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Gets the number of symbols this estimator operates with
- getNumSymbols() - 类中的方法 weka.estimators.DiscreteEstimator
-
Gets the number of symbols this estimator operates with
- getNumTestingNoises() - 类中的方法 weka.classifiers.mi.MINND
-
Returns The number of nearest neighbour instances in the selection of noises in the test data
- getNumToSelect() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Gets the number of attributes to be retained.
- getNumToSelect() - 类中的方法 weka.attributeSelection.RaceSearch
-
Gets the number of attributes to be retained.
- getNumToSelect() - 接口中的方法 weka.attributeSelection.RankedOutputSearch
-
Gets the user specified number of attributes to be retained.
- getNumToSelect() - 类中的方法 weka.attributeSelection.Ranker
-
Gets the number of attributes to be retained.
- getNumTraining() - 类中的方法 weka.classifiers.lazy.IBk
-
Get the number of training instances the classifier is currently using.
- getNumTrainingNoises() - 类中的方法 weka.classifiers.mi.MINND
-
Returns the number of nearest neighbour instances in the selection of noises in the training data
- getNumTrees() - 类中的方法 weka.classifiers.trees.RandomForest
-
Get the value of numTrees.
- getNumUsedAttributes() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Get the number of top-ranked attributes that taken into account by the search process.
- getNumUsedAttributes() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Get the number of top-ranked attributes that taken into account by the search process.
- getNumValues() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
returns array that stores the number of values for a nominal attribute.
- getNumValues() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Gets how many values are retained
- getNumXValFolds() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Get the number of folds used for cross-validation.
- getObject() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueueElement
-
Returns the object
- getObject() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueueElement
-
Returns the object
- getObject() - 类中的方法 weka.core.CheckGOE
-
Get the object used in the tests.
- getObject() - 类中的方法 weka.core.SerializedObject
-
Returns a serialized object.
- getObjectKey() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueueElement
-
Returns the key
- getObservedFrequency() - 类中的方法 weka.associations.tertius.Rule
-
Get the observed frequency of counter-instances of this rule in the dataset.
- getObservedNumber() - 类中的方法 weka.associations.tertius.Rule
-
Get the observed number of counter-instances of this rule in the dataset.
- getOmega() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Gets the omega value.
- getOnDemandDirectory() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Returns the directory that will be searched for cost files when loading on demand.
- getOnDemandDirectory() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Returns the directory that will be searched for cost files when loading on demand.
- getOnDemandDirectory() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns the directory that will be searched for cost files when loading on demand.
- getOnDemandDirectory() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Returns the directory that will be searched for cost files when loading on demand.
- getOneElements(Instances) - 类中的静态方法 weka.associations.gsp.Element
-
Returns all events of the given data set as Elements containing a single event.
- getOptimistic() - 类中的方法 weka.associations.tertius.Rule
-
Get the optimistic estimate of the confirmation obtained by refining this rule.
- getOptimizations() - 类中的方法 weka.classifiers.rules.JRip
-
Gets the the number of optimization runs
- getOption(char, String[]) - 类中的静态方法 weka.core.Utils
-
Gets an option indicated by a flag "-Char" from the given array of strings.
- getOption(String, String[]) - 类中的静态方法 weka.core.Utils
-
Gets an option indicated by a flag "-String" from the given array of strings.
- getOptionHandler() - 类中的方法 weka.core.CheckOptionHandler
-
Get the OptionHandler used in the tests.
- getOptionPos(char, String[]) - 类中的静态方法 weka.core.Utils
-
Gets the index of an option or flag indicated by a flag "-Char" from the given array of strings.
- getOptionPos(String, String[]) - 类中的静态方法 weka.core.Utils
-
Gets the index of an option or flag indicated by a flag "-String" from the given array of strings.
- getOptions() - 类中的方法 weka.associations.Apriori
-
Gets the current settings of the Apriori object.
- getOptions() - 类中的方法 weka.associations.CheckAssociator
-
Gets the current settings of the CheckAssociator.
- getOptions() - 类中的方法 weka.associations.FilteredAssociator
-
Gets the current settings of the Associator.
- getOptions() - 类中的方法 weka.associations.FPGrowth
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns an Array containing the current options settings.
- getOptions() - 类中的方法 weka.associations.PredictiveApriori
-
Gets the current settings of the PredictiveApriori object.
- getOptions() - 类中的方法 weka.associations.SingleAssociatorEnhancer
-
Gets the current settings of the associator.
- getOptions() - 类中的方法 weka.associations.Tertius
-
Gets the current settings of the Tertius object.
- getOptions() - 类中的方法 weka.attributeSelection.BestFirst
-
Gets the current settings of BestFirst.
- getOptions() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Gets the current settings of CfsSubsetEval
- getOptions() - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Gets the current settings of the CheckAttributeSelection.
- getOptions() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Gets the current settings.
- getOptions() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Gets the current settings of ClassifierSubsetEval
- getOptions() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Gets the current settings of the subset evaluator.
- getOptions() - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
Gets the current settings of RandomSearch.
- getOptions() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Gets the current settings of the subset evaluator.
- getOptions() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Gets the current settings of the subset evaluator.
- getOptions() - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Gets the current settings of WrapperSubsetEval.
- getOptions() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Gets the current settings of ReliefFAttributeEval.
- getOptions() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Gets the current settings of ReliefFAttributeEval.
- getOptions() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Gets the current settings of WrapperSubsetEval.
- getOptions() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Gets the current settings of LatentSemanticAnalysis
- getOptions() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Gets the current settings of LinearForwardSelection.
- getOptions() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
returns the current setup.
- getOptions() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Gets the current settings of PrincipalComponents
- getOptions() - 类中的方法 weka.attributeSelection.RaceSearch
-
Gets the current settings of BestFirst.
- getOptions() - 类中的方法 weka.attributeSelection.RandomSearch
-
Gets the current settings of RandomSearch.
- getOptions() - 类中的方法 weka.attributeSelection.Ranker
-
Gets the current settings of ReliefFAttributeEval.
- getOptions() - 类中的方法 weka.attributeSelection.RankSearch
-
Gets the current settings of WrapperSubsetEval.
- getOptions() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Gets the current settings of ReliefFAttributeEval.
- getOptions() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Gets the current settings of ScatterSearchV1.
- getOptions() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Gets the current settings of LinearForwardSelection.
- getOptions() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Gets the current settings of SVMAttributeEval
- getOptions() - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Gets the current settings of WrapperSubsetEval.
- getOptions() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Gets the current settings of WrapperSubsetEval.
- getOptions() - 类中的方法 weka.classifiers.bayes.AODE
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
- getOptions() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.fixed.FromFile
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.TAN
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
-
Gets the current settings of the search algorithm.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.TAN
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.net.search.SearchAlgorithm
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.bayes.WAODE
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.classifiers.BVDecompose
-
Gets the current settings of the CheckClassifier.
- getOptions() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Gets the current settings of the CheckClassifier.
- getOptions() - 类中的方法 weka.classifiers.CheckClassifier
-
Gets the current settings of the CheckClassifier.
- getOptions() - 类中的方法 weka.classifiers.CheckSource
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.Classifier
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the current options
- getOptions() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the current options
- getOptions() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.Logistic
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
Gets the current settings of NeuralNet.
- getOptions() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.PLSClassifier
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.SMO
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.SMOreg
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.SPegasos
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Gets the current settings of the Kernel.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.CheckKernel
-
Gets the current settings of the CheckKernel.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Gets the current settings of the Kernel.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Gets the current settings of the Kernel.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Gets the current settings of the Kernel.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Gets the current settings of the Kernel.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Gets the current settings of the Kernel.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Gets the current settings of the object.
- getOptions() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Gets the current settings of the Kernel.
- getOptions() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.functions.Winnow
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.IteratedSingleClassifierEnhancer
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.lazy.IBk
-
Gets the current settings of IBk.
- getOptions() - 类中的方法 weka.classifiers.lazy.KStar
-
Gets the current settings of K*.
- getOptions() - 类中的方法 weka.classifiers.lazy.LWL
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.Bagging
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.Dagging
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.Decorate
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.GridSearch
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.MetaCost
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.RotationForest
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.Stacking
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.meta.Vote
-
Gets the current settings of Vote.
- getOptions() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.classifiers.mi.MDD
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MIBoost
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MIDD
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MILR
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MINND
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MISMO
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MISVM
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.classifiers.misc.VFI
-
Gets the current settings of VFI
- getOptions() - 类中的方法 weka.classifiers.MultipleClassifiersCombiner
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.RandomizableClassifier
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.RandomizableMultipleClassifiersCombiner
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.RandomizableSingleClassifierEnhancer
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.rules.DTNB
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.rules.JRip
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.rules.NNge
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.classifiers.rules.OneR
-
Gets the current settings of the OneR classifier.
- getOptions() - 类中的方法 weka.classifiers.rules.PART
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.rules.Ridor
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.SingleClassifierEnhancer
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.ADTree
-
Gets the current settings of ADTree.
- getOptions() - 类中的方法 weka.classifiers.trees.BFTree
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.FT
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.J48
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.J48graft
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.LADTree
-
Gets the current settings of ADTree.
- getOptions() - 类中的方法 weka.classifiers.trees.LMT
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.M5P
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.RandomForest
-
Gets the current settings of the forest.
- getOptions() - 类中的方法 weka.classifiers.trees.RandomTree
-
Gets options from this classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.REPTree
-
Gets options from this classifier.
- getOptions() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.clusterers.CheckClusterer
-
Gets the current settings of the CheckClusterer.
- getOptions() - 类中的方法 weka.clusterers.CLOPE
-
Gets the current settings of CLOPE
- getOptions() - 类中的方法 weka.clusterers.Cobweb
-
Gets the current settings of Cobweb.
- getOptions() - 类中的方法 weka.clusterers.DBSCAN
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.clusterers.EM
-
Gets the current settings of EM.
- getOptions() - 类中的方法 weka.clusterers.FarthestFirst
-
Gets the current settings of FarthestFirst
- getOptions() - 类中的方法 weka.clusterers.FilteredClusterer
-
Gets the current settings of the clusterer.
- getOptions() - 类中的方法 weka.clusterers.HierarchicalClusterer
-
Gets the current settings of the clusterer.
- getOptions() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Gets the current settings of the clusterer.
- getOptions() - 类中的方法 weka.clusterers.OPTICS
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.clusterers.RandomizableClusterer
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.clusterers.RandomizableDensityBasedClusterer
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.clusterers.RandomizableSingleClustererEnhancer
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.clusterers.sIB
-
Gets the current settings.
- getOptions() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets the current settings of SimpleKMeans
- getOptions() - 类中的方法 weka.clusterers.SingleClustererEnhancer
-
Gets the current settings of the clusterer.
- getOptions() - 类中的方法 weka.clusterers.XMeans
-
Gets the current settings of SimpleKMeans.
- getOptions() - 类中的方法 weka.core.Check
-
Gets the current settings of the CheckClassifier.
- getOptions() - 类中的方法 weka.core.CheckGOE
-
Gets the current settings of the object.
- getOptions() - 类中的方法 weka.core.CheckOptionHandler
-
Gets the current settings of the CheckClassifier.
- getOptions() - 类中的方法 weka.core.CheckScheme
-
Gets the current settings of the CheckClassifier.
- getOptions() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Gets the current settings of the Saver object.
- getOptions() - 类中的方法 weka.core.converters.ArffSaver
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.core.converters.C45Saver
-
Gets the current settings of the C45Saver object.
- getOptions() - 类中的方法 weka.core.converters.CSVLoader
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.core.converters.DatabaseLoader
-
Gets the setting
- getOptions() - 类中的方法 weka.core.converters.DatabaseSaver
-
Gets the setting.
- getOptions() - 类中的方法 weka.core.converters.LibSVMSaver
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.core.converters.SVMLightSaver
-
returns the options of the current setup.
- getOptions() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Gets the setting
- getOptions() - 类中的方法 weka.core.converters.XRFFSaver
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.core.FindWithCapabilities
-
Gets the current settings of this object.
- getOptions() - 类中的方法 weka.core.Javadoc
-
Gets the current settings of this object.
- getOptions() - 类中的方法 weka.core.ListOptions
-
Gets the current settings of this object.
- getOptions() - 类中的方法 weka.core.neighboursearch.BallTree
-
Gets the current settings of KDtree.
- getOptions() - 类中的方法 weka.core.neighboursearch.balltrees.BallSplitter
-
Gets the current settings of the object.
- getOptions() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Gets the current settings.
- getOptions() - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Gets the current settings of the object.
- getOptions() - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Gets the current settings.
- getOptions() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Gets the current settings of this BallTree MiddleOutConstructor.
- getOptions() - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Gets the current settings of KDtree.
- getOptions() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Gets the current settings of KDtree.
- getOptions() - 类中的方法 weka.core.neighboursearch.KDTree
-
Gets the current settings of KDtree.
- getOptions() - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Gets the current settings of the object.
- getOptions() - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Gets the current settings.
- getOptions() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Gets the current settings.
- getOptions() - 类中的方法 weka.core.NormalizableDistance
-
Gets the current settings.
- getOptions() - 接口中的方法 weka.core.OptionHandler
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.core.OptionHandlerJavadoc
-
Gets the current settings of this object.
- getOptions() - 类中的方法 weka.core.stemmers.SnowballStemmer
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.core.TechnicalInformationHandlerJavadoc
-
Gets the current settings of this object.
- getOptions() - 类中的方法 weka.core.TestInstances
-
Gets the current settings of this object.
- getOptions() - 类中的方法 weka.core.tokenizers.CharacterDelimitedTokenizer
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.core.tokenizers.Tokenizer
-
Gets the current option settings for the OptionHandler.
- getOptions() - 类中的方法 weka.datagenerators.ClassificationGenerator
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Gets the current settings of the datagenerator.
- getOptions() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Gets the current settings of the datagenerator.
- getOptions() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Gets the current settings of the datagenerator.
- getOptions() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Gets the current settings of the datagenerator.
- getOptions() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the current settings of the datagenerator RDG1.
- getOptions() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Gets the current settings of the datagenerator BIRCHCluster.
- getOptions() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Gets the current settings of the datagenerator BIRCHCluster.
- getOptions() - 类中的方法 weka.datagenerators.ClusterDefinition
-
Gets the current settings of the datagenerator BIRCHCluster.
- getOptions() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the current settings of the datagenerator BIRCHCluster.
- getOptions() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Gets the current settings of the datagenerator.
- getOptions() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Gets the current settings of the datagenerator BIRCHCluster.
- getOptions() - 类中的方法 weka.datagenerators.ClusterGenerator
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the current settings of the datagenerator RDG1.
- getOptions() - 类中的方法 weka.datagenerators.RegressionGenerator
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.estimators.CheckEstimator
-
Gets the current settings of the CheckEstimator.
- getOptions() - 类中的方法 weka.estimators.Estimator
-
Gets the current settings of the Estimator.
- getOptions() - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets the current settings of the result producer.
- getOptions() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets the current settings of the result producer.
- getOptions() - 类中的方法 weka.experiment.CSVResultListener
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets the current settings of the result producer.
- getOptions() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.experiment.Experiment
-
Gets the current settings of the experiment iterator.
- getOptions() - 类中的方法 weka.experiment.InstanceQuery
-
Gets the current settings of InstanceQuery
- getOptions() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets the current settings of the result producer.
- getOptions() - 类中的方法 weka.experiment.PairedTTester
-
Gets current settings of the PairedTTester.
- getOptions() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets the current settings of the result producer.
- getOptions() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Gets the current settings of the Classifier.
- getOptions() - 类中的方法 weka.filters.CheckSource
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.MultiFilter
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.SimpleFilter
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Gets the current settings for the attribute selection (search, evaluator) etc.
- getOptions() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.filters.supervised.instance.Resample
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.PotentialClassIgnorer
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Gets the current settings of the classifier.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
returns the options of the current setup
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Gets the current settings of the filter.
- getOptions() - 类中的方法 weka.gui.Main
-
returns the options of the current setup.
- getOptype() - 类中的方法 weka.core.pmml.Expression
-
Get the optype of the result of applying this Expression.
- getOptype() - 类中的方法 weka.core.pmml.FieldMetaInfo
-
Get the optype.
- getOrder() - enum class中的方法 weka.core.logging.Logger.Level
-
Returns the order of this level.
- getOrderedFlag() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the ordered flag (option O).
- getOriginalCoords() - 类中的方法 weka.gui.beans.MetaBean
-
returns the vector containing the original coordinates (instances of class Point) for the inputs
- getOtherCapabilities() - 类中的方法 weka.core.Capabilities
-
returns all other capabilities, besides class and attribute related ones
- getOtherLeaf() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- getOutlierFactor() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Gets the factor for determining the thresholds for outliers.
- getOutlierTreatmentMethod() - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Get the outlier treatment method used for this field.
- getOutput() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the print writer.
- getOutput() - 类中的方法 weka.gui.explorer.DataGeneratorPanel
-
returns the generated output as text
- getOutputCenterFile() - 类中的方法 weka.clusterers.XMeans
-
Gets the file to write the list of centers to.
- getOutputClassification() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Get whether the classifiction of the classifier is output.
- getOutputDef() - 类中的方法 weka.core.pmml.BuiltInArithmetic
-
Get the structure of the result produced by this function.
- getOutputDef() - 类中的方法 weka.core.pmml.BuiltInMath
-
Get the structure of the result produced by this function.
- getOutputDef() - 类中的方法 weka.core.pmml.BuiltInString
-
Get the structure of the result produced by this function.
- getOutputDef() - 类中的方法 weka.core.pmml.DefineFunction
-
Get the structure of the result produced by this function.
- getOutputDef() - 类中的方法 weka.core.pmml.FieldRef
-
Return the structure of the result of applying this Expression as an Attribute.
- getOutputDef() - 类中的方法 weka.core.pmml.Function
-
Get the structure of the result produced by this function.
- getOutputDistribution() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Get whether the classifiction of the classifier is output.
- getOutputErrorFlag() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Get whether the classifiction of the classifier is output.
- getOutputFile() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Get the value of OutputFile.
- getOutputFile() - 类中的方法 weka.experiment.CSVResultListener
-
Get the value of OutputFile.
- getOutputFile() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Get the value of OutputFile.
- getOutputFilename() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Gets whether the filename will be stored as an extra attribute.
- getOutputFilename() - 类中的方法 weka.gui.GenericPropertiesCreator
-
returns the name of the output file
- getOutputFormat() - 类中的方法 weka.core.Debug.Clock
-
returns the output format
- getOutputFormat() - 类中的方法 weka.filters.Filter
-
Gets the format of the output instances.
- getOutputFormat() - 类中的方法 weka.filters.unsupervised.attribute.PotentialClassIgnorer
-
Gets the format of the output instances.
- getOutputFormat() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the classname of the ResultMatrix class, responsible for the output format
- getOutputItemSets() - 类中的方法 weka.associations.Apriori
-
Gets whether itemsets are output as well
- getOutputNums() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Use this to get easy access to the output numbers.
- getOutputOffsetMultiplier() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Gets whether an additional attribute "Offset" is generated per Outlier/ExtremeValue attribute pair that lists the multiplier the value is off the median: value = median + 'multiplier' * IQR.
- getOutputPerClassInfoRetrievalStats() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Get whether per-class information retrieval stats are to be output.
- getOutputProperties() - 类中的方法 weka.gui.GenericPropertiesCreator
-
returns the output properties object (structure like the template, but filled with classes instead of packages)
- getOutputs() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Use this to get easy access to the outputs.
- getOutputs() - 类中的方法 weka.gui.beans.MetaBean
- getOutputTypes() - 类中的方法 weka.core.Debug.DBO
-
Gets the current output type selection
- getOutputWordCounts() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets whether output instances contain 0 or 1 indicating word presence, or word counts.
- getOverwriteWarning() - 类中的方法 weka.gui.ConverterFileChooser
-
Returns whether a popup appears with a warning that the file already exists (only save dialog).
- getOwner() - 类中的方法 weka.core.Capabilities
-
returns the owner of this capabilities object
- getOwner() - 类中的静态方法 weka.core.Copyright
-
returns the entity owning the copyright
- getP() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the proportion of instances that are common between two training sets.
- getPackage(String) - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
returns the packages part of the partial classname.
- getPadding() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Gets the type of Padding to use
- getPaint() - 类中的方法 weka.gui.visualize.PostscriptGraphics
- getPanel(int) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the specified panel,
null
if index is out of bounds - getPanelCount() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the number of panels currently open
- getPanels() - 类中的方法 weka.gui.explorer.Explorer
-
returns all the panels, apart from the PreprocessPanel
- getParameterNames() - 类中的方法 weka.core.pmml.BuiltInArithmetic
-
Returns an array of the names of the parameters expected as input by this function
- getParameterNames() - 类中的方法 weka.core.pmml.BuiltInMath
-
Returns an array of the names of the parameters expected as input by this function.
- getParameterNames() - 类中的方法 weka.core.pmml.BuiltInString
-
Returns an array of the names of the parameters expected as input by this function.
- getParameterNames() - 类中的方法 weka.core.pmml.DefineFunction
-
Returns an array of the names of the parameters expected as input by this function.
- getParameterNames() - 类中的方法 weka.core.pmml.Function
-
Returns an array of the names of the parameters expected as input by this function.
- getParent() - 类中的方法 weka.datagenerators.ClusterDefinition
-
returns the parent datagenerator this cluster belongs to
- getParent(int) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
returns index parent of parent specified by index
- getParent(int) - 类中的方法 weka.gui.treevisualizer.Node
-
Get the parent edge.
- getParent(int, int) - 类中的方法 weka.classifiers.bayes.BayesNet
-
get node index of a parent of a node in the network structure
- getParentCardinality(int) - 类中的方法 weka.classifiers.bayes.BayesNet
-
get number of values the collection of parents of a node can take
- getParentDialog(Container) - 类中的静态方法 weka.gui.PropertyDialog
-
Tries to determine the dialog this panel is part of.
- getParentFrame() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the parent frame, if it's a JFrame, otherwise null
- getParentFrame() - 类中的方法 weka.gui.GUIChooser.ChildFrameSDI
-
returns the parent frame, can be null.
- getParentFrame() - 类中的方法 weka.gui.Main.ChildFrameMDI
-
returns the parent frame, can be null.
- getParentFrame() - 类中的方法 weka.gui.Main.ChildFrameSDI
-
returns the parent frame, can be null.
- getParentFrame() - 类中的方法 weka.gui.SetInstancesPanel
-
Returns the current frame the panel knows of, that it resides in.
- getParentFrame(Container) - 类中的静态方法 weka.gui.PropertyDialog
-
Tries to determine the frame this panel is part of.
- getParentInternalFrame() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the parent frame, if it's a JInternalFrame, otherwise null
- getParents() - 类中的方法 weka.classifiers.bayes.net.ParentSet
- getParentSet(int) - 类中的方法 weka.classifiers.bayes.BayesNet
-
get the parent set of a node
- getParentSets() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Get full set of parent sets.
- getParts() - 类中的方法 weka.associations.tertius.IndividualInstance
- getPassword() - 类中的方法 weka.core.converters.DatabaseLoader
-
Returns the database password
- getPassword() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the database password.
- getPassword() - 类中的方法 weka.experiment.DatabaseUtils
-
Get the database password.
- getPassword() - 类中的方法 weka.gui.DatabaseConnectionDialog
-
Returns password from dialog
- getPassword() - 类中的方法 weka.gui.sql.ConnectionPanel
-
returns the current Password.
- getPassword() - 类中的方法 weka.gui.sql.event.ResultChangedEvent
-
returns the password that produced the table model
- getPassword() - 类中的方法 weka.gui.sql.ResultSetTable
-
returns the password that produced the table model
- getPassword() - 类中的方法 weka.gui.sql.SqlViewer
-
returns the password from the currently active tab in the ResultPanel, otherwise an empty string.
- getPassword() - 类中的方法 weka.gui.sql.SqlViewerDialog
-
returns the chosen password, if any
- getPath() - 类中的方法 weka.gui.PropertySelectorDialog
-
Gets the path of property nodes to the selected property.
- getPattern() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the pattern type.
- getPenalty() - 类中的方法 weka.classifiers.bayes.blr.Prior
- getPercent() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Gets the size of noise data as a percentage of the original set.
- getPercent() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Gets the percent the attributes (dimensions) of the data will be reduced to
- getPercentage() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Gets the percentage of SMOTE instances to create.
- getPercentage() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Gets the percentage of instances to select.
- getPercentCompleted() - 类中的方法 weka.gui.boundaryvisualizer.RemoteResult
-
Return the progress for this row
- getPercentThreshold() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Get the threshold below which percentage elimination reverts to constant elimination.
- getPercentToEliminatePerIteration() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Get the percentage rate of attribute elimination per iteration
- getPerformanceStats() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Gets the class object that contains the performance statistics of the search method.
- getPerformPrediction() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Gets whether the class attribute is updated with the predicted value.
- getPerformRanking() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Get boolean if initial ranking should be performed to select the top-ranked attributes
- getPerformRanking() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Get boolean if initial ranking should be performed to select the top-ranked attributes
- getPeriodicPruning() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.
- getPerturbationFraction() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Gets the perturbation fraction.
- getPivot() - 类中的方法 weka.core.matrix.LUDecomposition
-
Return pivot permutation vector
- getPivot() - 类中的方法 weka.core.neighboursearch.balltrees.BallNode
-
Returns the pivot/centre of the node's ball.
- getPlainColumnName(int) - 类中的方法 weka.gui.arffviewer.ArffTable
-
returns the basically the attribute name of the column and not the HTML column name via getColumnName(int)
- getPlotInstances() - 类中的方法 weka.gui.visualize.PlotData2D
-
Returns the instances for this plot
- getPlotName() - 类中的方法 weka.gui.visualize.PlotData2D
-
Get the name of this plot
- getPlotNameHTML() - 类中的方法 weka.gui.visualize.PlotData2D
-
Get the name of the plot for use in a tool tip text.
- getPlotPanel() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Returns the underlying plot panel.
- getPlots() - 类中的方法 weka.gui.visualize.Plot2D
-
Return the list of plots
- getPlotTrainingData() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Returns true if training data is to be superimposed
- getPMMLModel(File) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Read and return a PMML model.
- getPMMLModel(File, Logger) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Read and return a PMML model.
- getPMMLModel(InputStream) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Read and return a PMML model.
- getPMMLModel(InputStream, Logger) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Read and return a PMML model.
- getPMMLModel(String) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Read and return a PMML model.
- getPMMLModel(String, Logger) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Read and return a PMML model.
- getPMMLVersion() - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Get the PMML version used for this model.
- getPMMLVersion() - 接口中的方法 weka.core.pmml.PMMLModel
-
Get the version of PMML used to encode this model.
- getPointValue(int) - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Gets a particular point value
- getPopulationSize() - 类中的方法 weka.attributeSelection.GeneticSearch
-
get the size of the population
- getPopulationSize() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Get the population size
- getPopulationSize() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- getPopulationSize() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- getPopup() - 类中的方法 weka.gui.GenericObjectEditor.CapabilitiesFilterDialog
-
returns the currently set JPopupMenu.
- getPositionX(int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
get x position of a node
- getPositionY(int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
get y position of a node
- getPositiveIndex() - 类中的方法 weka.associations.FPGrowth
-
Get the index of the attribute value to consider as positive for binary attributes in normal dense instances.
- getPostFixExpression() - 类中的方法 weka.core.AttributeExpression
-
Return the postfix expression
- getPostProcessor() - 类中的方法 weka.core.CheckScheme
-
returns the current PostProcessor, can be null
- getPostProcessor() - 类中的方法 weka.estimators.CheckEstimator
-
returns the current PostProcessor, can be null
- getPrecision() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Calculate the precision.
- getPrecision() - 类中的方法 weka.estimators.KernelEstimator
-
Return the precision of this kernel estimator.
- getPrecision() - 类中的方法 weka.estimators.NormalEstimator
-
Return the value of the precision of this normal estimator.
- getPredicate() - 类中的方法 weka.associations.tertius.Literal
- getPrediction(Classifier, Instance) - 类中的方法 weka.classifiers.evaluation.EvaluationUtils
-
Generate a single prediction for a test instance given the pre-trained classifier.
- getPredTargetColumn() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
- getPreferredScrollableViewportSize() - 类中的方法 weka.gui.AttributeSelectionPanel
- getPrefix() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Get the prefix to prepend to the model file names.
- getPremise() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get the premise of this rule.
- getPremiseSupport() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get the support for the premise.
- getPreprocessing() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Gets the type of preprocessing to use
- getPreprocessing() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Gets the filter used for preprocessing
- getPreprocessPanel() - 类中的方法 weka.gui.explorer.Explorer
-
returns the instance of the PreprocessPanel being used in this instance of the Explorer
- getPreserveInstancesOrder() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets whether order of instances must be preserved
- getPrintColNames() - 类中的方法 weka.experiment.ResultMatrix
-
returns whether column names or numbers instead are printed
- getPrintNewick() - 类中的方法 weka.clusterers.HierarchicalClusterer
- getPrintRowNames() - 类中的方法 weka.experiment.ResultMatrix
-
returns whether row names or numbers instead are printed
- getPriorClass() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Get the type of prior to use.
- getPriority() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueueElement
-
Returns the priority for this object
- getPriority() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueueElement
-
Returns the priority for this object
- getPriority(int) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue
-
Returns the priority for the object at the specified index
- getPriority(int) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue
-
Returns the priority for the object at the specified index
- getPriorProbability(String) - 类中的方法 weka.core.pmml.TargetMetaInfo
-
Get the prior probability for the supplied value.
- getProbabilities() - 类中的方法 weka.gui.boundaryvisualizer.RemoteResult
-
Return the probability distributions for this row in the visualization
- getProbability(double) - 类中的方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Get a probability estimate for a value
- getProbability(double) - 类中的方法 weka.estimators.DiscreteEstimator
-
Get a probability estimate for a value
- getProbability(double) - 类中的方法 weka.estimators.Estimator
-
Get a probability estimate for a value.
- getProbability(double) - 类中的方法 weka.estimators.KernelEstimator
-
Get a probability estimate for a value.
- getProbability(double) - 类中的方法 weka.estimators.MahalanobisEstimator
-
Get a probability estimate for a value
- getProbability(double) - 类中的方法 weka.estimators.NormalEstimator
-
Get a probability estimate for a value
- getProbability(double) - 类中的方法 weka.estimators.PoissonEstimator
-
Get a probability estimate for a value
- getProbability(double, double) - 接口中的方法 weka.estimators.ConditionalEstimator
-
Get a probability for a value conditional on another value
- getProbability(double, double) - 类中的方法 weka.estimators.DDConditionalEstimator
-
Get a probability estimate for a value
- getProbability(double, double) - 类中的方法 weka.estimators.DKConditionalEstimator
-
Get a probability estimate for a value
- getProbability(double, double) - 类中的方法 weka.estimators.DNConditionalEstimator
-
Get a probability estimate for a value
- getProbability(double, double) - 类中的方法 weka.estimators.KDConditionalEstimator
-
Get a probability estimate for a value
- getProbability(double, double) - 类中的方法 weka.estimators.KKConditionalEstimator
-
Get a probability estimate for a value
- getProbability(double, double) - 类中的方法 weka.estimators.NDConditionalEstimator
-
Get a probability estimate for a value
- getProbability(double, double) - 类中的方法 weka.estimators.NNConditionalEstimator
-
Get a probability estimate for a value
- getProbability(int, int, int) - 类中的方法 weka.classifiers.bayes.BayesNet
-
get particular probability of the conditional probability distribtion of a node given its parents.
- getProbabilityEstimates() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Sets whether to generate probability estimates instead of -1/+1 for classification problems.
- getProbabilityEstimates() - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets whether to generate probability estimates instead of -1/+1 for classification problems.
- getProgressBar() - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
Returns a handle to the progressBar of this LayoutEngine.
- getProgressBar() - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
This method returns the progress bar for the LayoutEngine, which shows the progress of the layout process, if it takes a while to layout the graph
- getProjectionFilter() - 类中的方法 weka.classifiers.meta.RotationForest
-
Gets the filter used to project the data.
- getProlog() - 类中的方法 weka.core.OptionHandlerJavadoc
-
whether "Valid options are..." prolog is included in the Javadoc
- getProlog() - 类中的方法 weka.core.TechnicalInformationHandlerJavadoc
-
whether "Valid options are..." prolog is included in the Javadoc
- getProperties() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the associated properties file
- getProperties() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns the associated properties file.
- getProperty() - 类中的方法 weka.core.pmml.FieldMetaInfo.Value
- getPropertyArray() - 类中的方法 weka.experiment.Experiment
-
Gets the array of values to set the custom property to.
- getPropertyArrayLength() - 类中的方法 weka.experiment.Experiment
-
Gets the number of custom iterator values that have been defined for the experiment.
- getPropertyArrayValue(int) - 类中的方法 weka.experiment.Experiment
-
Gets a specified value from the custom property iterator array.
- getPropertyDescriptor(Object, String) - 类中的静态方法 weka.core.PropertyPath
-
returns the property associated with the given path
- getPropertyDescriptor(Object, PropertyPath.Path) - 类中的静态方法 weka.core.PropertyPath
-
returns the property associated with the given path, null if a problem occurred.
- getPropertyDescriptors() - 类中的方法 weka.gui.beans.ClassAssignerBeanInfo
-
Returns the property descriptors
- getPropertyDescriptors() - 类中的方法 weka.gui.beans.ClassValuePickerBeanInfo
-
Returns the property descriptors
- getPropertyDescriptors() - 类中的方法 weka.gui.beans.CrossValidationFoldMakerBeanInfo
-
Return the property descriptors for this bean
- getPropertyDescriptors() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo
-
Return the property descriptors for this bean
- getPropertyDescriptors() - 类中的方法 weka.gui.beans.PredictionAppenderBeanInfo
-
Return the property descriptors for this bean
- getPropertyDescriptors() - 类中的方法 weka.gui.beans.StripChartBeanInfo
-
Get the property descriptors for this bean
- getPropertyDescriptors() - 类中的方法 weka.gui.beans.TrainTestSplitMakerBeanInfo
-
Get the property descriptors for this bean
- getPropertyPath() - 类中的方法 weka.experiment.Experiment
-
Gets the path of properties taken to get to the custom property to iterate over.
- getPruningMethod() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Gets the method used for pruning.
- getPruningStrategy() - 类中的方法 weka.classifiers.trees.BFTree
-
Gets the pruning strategy.
- getPruningType() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get the pruning type
- getQ() - 类中的方法 weka.core.matrix.QRDecomposition
-
Generate and return the (economy-sized) orthogonal factor
- getQuality() - 类中的方法 weka.gui.visualize.JPEGWriter
-
returns the quality the JPEG will be stored in.
- getQuery() - 类中的方法 weka.core.converters.DatabaseLoader
-
Gets the query to execute against the database
- getQuery() - 类中的方法 weka.experiment.InstanceQuery
-
Get the query to execute against the database
- getQuery() - 类中的方法 weka.gui.sql.event.QueryExecuteEvent
-
returns the query that was executed
- getQuery() - 类中的方法 weka.gui.sql.event.ResultChangedEvent
-
returns the query that was executed
- getQuery() - 类中的方法 weka.gui.sql.QueryPanel
-
returns the currently displayed query.
- getQuery() - 类中的方法 weka.gui.sql.ResultSetTable
-
returns the query that produced the table model
- getQuery() - 类中的方法 weka.gui.sql.SqlViewer
-
returns the query from the currently active tab in the ResultPanel, otherwise an empty string.
- getQuery() - 类中的方法 weka.gui.sql.SqlViewerDialog
-
returns the chosen query, if any
- getQueryPanel() - 类中的方法 weka.gui.sql.ResultPanel
-
returns the currently set QueryPanel, can be NULL
- getR() - 类中的方法 weka.core.matrix.QRDecomposition
-
Return the upper triangular factor
- getRaceType() - 类中的方法 weka.attributeSelection.RaceSearch
-
Get the race type
- getRadius() - 类中的方法 weka.core.neighboursearch.balltrees.BallNode
-
Returns the radius of the node's ball.
- getRandom() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the random generator.
- getRandomize() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Gets whether the order of the generated is randomized
- getRandomizeData() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Get if dataset is to be randomized
- getRandomNumberGenerator(long) - 类中的方法 weka.core.Instances
-
Returns a random number generator.
- getRandomOrder() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Get random order flag
- getRandomOrder() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Get random order flag
- getRandomSeed() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
get the seed for the random number generator
- getRandomSeed() - 类中的方法 weka.classifiers.functions.SMO
-
Get the value of randomSeed.
- getRandomSeed() - 类中的方法 weka.classifiers.mi.MISMO
-
Get the value of randomSeed.
- getRandomSeed() - 类中的方法 weka.classifiers.trees.ADTree
-
Gets random seed for a random walk.
- getRandomSeed() - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Returns the seed value of random number generator.
- getRandomSeed() - 类中的方法 weka.filters.supervised.instance.Resample
-
Gets the random number seed.
- getRandomSeed() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Gets the random number seed.
- getRandomSeed() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Gets the random number seed.
- getRandomSeed() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Gets the random number seed.
- getRandomSeed() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Gets the random seed of the random number generator
- getRandomSeed() - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Get the random number generator seed value.
- getRandomSeed() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Gets the random number seed.
- getRandomSeed() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Gets the random number seed.
- getRandomWidthFactor() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Gets the multiplier when generating random codes.
- getRange(int) - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Gets a single Range from the set of available Ranges.
- getRangeCorrection() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Gets the confidence range correction mode used.
- getRanges() - 类中的方法 weka.core.NormalizableDistance
-
Method to get the ranges.
- getRanges() - 类中的方法 weka.core.Range
-
Gets the string representing the selected range of values
- getRanges() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Gets the list of possible Ranges to choose from.
- getRank() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Gets the desired matrix rank (or coverage proportion) for feature-space reduction
- getRawOutput() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Get if raw split evaluator output is to be saved
- getRawOutput() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Get if raw split evaluator output is to be saved
- getRawResultOutput() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Gets the raw output from the classifier
- getRawResultOutput() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Gets the raw output from the classifier
- getRawResultOutput() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Gets the raw output from the classifier
- getRawResultOutput() - 接口中的方法 weka.experiment.SplitEvaluator
-
Returns the raw output for the most recent call to getResult.
- getReachabilityDistance() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Returns the reachabilityDistance for this dataObject
- getReachabilityDistance() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Returns the reachabilityDistance for this dataObject
- getReachabilityDistance() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Returns the reachabilityDistance for this dataObject
- getReadable() - 类中的方法 weka.core.Tag
-
Gets the string description of the Tag.
- getReader(String) - 类中的方法 weka.gui.Loader
-
returns a Reader for the given filename, can be NULL if it fails
- getReader(String, String) - 类中的静态方法 weka.gui.Loader
-
returns a Reader for the given filename and dir, can be NULL if it fails
- getReadIncrementally() - 类中的方法 weka.gui.SetInstancesPanel
-
Gets whether instances are to be read incrementally or not
- getRealEigenvalues() - 类中的方法 weka.core.matrix.EigenvalueDecomposition
-
Return the real parts of the eigenvalues
- getRecall() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Calculate the recall.
- getReducedErrorPruning() - 类中的方法 weka.classifiers.rules.PART
-
Get the value of reducedErrorPruning.
- getReducedErrorPruning() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of reducedErrorPruning.
- getRefer() - 类中的方法 weka.gui.treevisualizer.Node
-
Get the value of refer.
- getRefreshFreq() - 类中的方法 weka.gui.beans.StripChart
-
Get the refresh frequency
- getRegOptimizer() - 类中的方法 weka.classifiers.functions.SMOreg
-
returns the learning algorithm
- getRegressionTree() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Get the value of regressionTree.
- getRegressionTree() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the value of regressionTree.
- getRelabel() - 类中的方法 weka.classifiers.trees.J48graft
-
Get the value of relabelling
- getRelation() - 类中的方法 weka.core.TestInstances
-
returns the current name of the relation
- getRelationalClassFormat() - 类中的方法 weka.core.TestInstances
-
returns the current strcuture of the relational class attribute, can be null
- getRelationalFormat(int) - 类中的方法 weka.core.TestInstances
-
returns the format for the specified relational attribute, can be null
- getRelationForTableName() - 类中的方法 weka.core.converters.DatabaseSaver
-
Gets whether or not the relation name is used as name of the table.
- getRelationName() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the relation name the dataset should have.
- getRelationNameForFilename() - 类中的方法 weka.gui.beans.Saver
-
Get whether the relation name is the primary part of the filename.
- getRemoteHosts() - 类中的方法 weka.experiment.RemoteExperiment
-
Get the list of remote host names
- getRemoveAllMissingCols() - 类中的方法 weka.associations.Apriori
-
Returns whether columns containing all missing values are to be removed
- getRemoveClassColumn() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Get whether the class column is to be removed.
- getRemovedPercentage() - 类中的方法 weka.classifiers.meta.RotationForest
-
Gets the percentage of instances to be removed
- getRemoveFilterClassnames() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
whether the filter classnames in the dataset names are removed by default
- getRemoveFilterName() - 类中的方法 weka.experiment.ResultMatrix
-
returns whether the filter classname is removed from the dataset name
- getRemoveFilterName() - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
returns whether the filter classname is removed from the dataset name.
- getRemoveOldClass() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Get whether the old class attribute is removed.
- getRemoveUnused() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Gets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.
- getRenderingHint(RenderingHints.Key) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- getRenderingHints() - 类中的方法 weka.gui.visualize.PostscriptGraphics
- getRepeatLiterals() - 类中的方法 weka.associations.Tertius
-
Get the value of repeatLiterals.
- getRepetitions() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the number of repetitions to use
- getReplaceMissing() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Gets whether missing values are replace.
- getReplaceMissingValues() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Gets the current setting for using ReplaceMissingValues filter
- getReportFrequency() - 类中的方法 weka.attributeSelection.GeneticSearch
-
get how often repports are generated
- getRepulsion() - 类中的方法 weka.clusterers.CLOPE
-
gets the repulsion
- getReset() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getReset() - 类中的方法 weka.gui.beans.ChartEvent
-
get the value of the reset flag
- getResult() - 类中的方法 weka.core.mathematicalexpression.Parser
-
Returns the result of the evaluation.
- getResult() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Returns the result of the evaluation.
- getResult() - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
the result from the last display of the dialog, the same is returned from
showDialog
. - getResult(double[]) - 类中的方法 weka.core.pmml.BuiltInArithmetic
-
Get the result of applying this function.
- getResult(double[]) - 类中的方法 weka.core.pmml.BuiltInMath
-
Get the result of applying this function.
- getResult(double[]) - 类中的方法 weka.core.pmml.BuiltInString
-
Get the result of applying this function.
- getResult(double[]) - 类中的方法 weka.core.pmml.Constant
-
Get the result of evaluating the expression.
- getResult(double[]) - 类中的方法 weka.core.pmml.DefineFunction
-
Get the result of applying this function.
- getResult(double[]) - 类中的方法 weka.core.pmml.Discretize
-
Get the result of evaluating the expression.
- getResult(double[]) - 类中的方法 weka.core.pmml.Expression
-
Get the result of evaluating the expression.
- getResult(double[]) - 类中的方法 weka.core.pmml.FieldRef
- getResult(double[]) - 类中的方法 weka.core.pmml.Function
-
Get the result of applying this function.
- getResult(double[]) - 类中的方法 weka.core.pmml.NormContinuous
-
Get the result of evaluating the expression.
- getResult(double[]) - 类中的方法 weka.core.pmml.NormDiscrete
-
Get the result of evaluating the expression.
- getResult(Instances, Instances) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Gets the results for the supplied train and test datasets.
- getResult(Instances, Instances) - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Gets the results for the supplied train and test datasets.
- getResult(Instances, Instances) - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Gets the results for the supplied train and test datasets.
- getResult(Instances, Instances) - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Gets the results for the supplied train and test datasets.
- getResult(Instances, Instances) - 接口中的方法 weka.experiment.SplitEvaluator
-
Gets the results for the supplied train and test datasets.
- getResultCategorical(double[]) - 类中的方法 weka.core.pmml.Constant
-
Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.
- getResultCategorical(double[]) - 类中的方法 weka.core.pmml.Discretize
-
Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.
- getResultCategorical(double[]) - 类中的方法 weka.core.pmml.Expression
-
Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.
- getResultCategorical(double[]) - 类中的方法 weka.core.pmml.FieldRef
- getResultCategorical(double[]) - 类中的方法 weka.core.pmml.NormContinuous
-
Always throws an Exception since the result of NormContinuous must be continuous.
- getResultCategorical(double[]) - 类中的方法 weka.core.pmml.NormDiscrete
-
Always throws an Exception since the result of NormDiscrete must be continuous.
- getResultContinuous(double[]) - 类中的方法 weka.core.pmml.Expression
-
Get the result of evaluating the expression for continuous optype.
- getResultFromTable(String, ResultProducer, Object[]) - 类中的方法 weka.experiment.DatabaseUtils
-
Executes a database query to extract a result for the supplied key from the database.
- getResultInverse(double[]) - 类中的方法 weka.core.pmml.NormContinuous
-
Compute the inverse of the normalization (i.e.
- getResultListener() - 类中的方法 weka.experiment.Experiment
-
Gets the result listener where results will be sent.
- getResultMatrix() - 类中的方法 weka.experiment.PairedTTester
-
Gets the instance that produces the output.
- getResultMatrix() - 接口中的方法 weka.experiment.Tester
-
Gets the instance that produces the output.
- getResultMatrix() - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
Gets the currently selected output format result matrix.
- getResultNames() - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets the names of each of the columns produced for a single run.
- getResultNames() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Gets the names of each of the result columns produced for a single run.
- getResultNames() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Gets the names of each of the result columns produced for a single run.
- getResultNames() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets the names of each of the columns produced for a single run.
- getResultNames() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets the names of each of the columns produced for a single run.
- getResultNames() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Gets the names of each of the result columns produced for a single run.
- getResultNames() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets the names of each of the columns produced for a single run.
- getResultNames() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets the names of each of the columns produced for a single run.
- getResultNames() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Gets the names of each of the result columns produced for a single run.
- getResultNames() - 接口中的方法 weka.experiment.ResultProducer
-
Gets the names of each of the result columns produced for a single run.
- getResultNames() - 接口中的方法 weka.experiment.SplitEvaluator
-
Gets the names of each of the result columns produced for a single run.
- getResultProducer() - 类中的方法 weka.experiment.AveragingResultProducer
-
Get the ResultProducer.
- getResultProducer() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Get the ResultProducer.
- getResultProducer() - 类中的方法 weka.experiment.Experiment
-
Get the result producer used for the current experiment.
- getResultProducer() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Get the ResultProducer.
- getResults() - 类中的方法 weka.associations.Tertius
-
returns the results
- getResultSet() - 类中的方法 weka.experiment.DatabaseUtils
-
Gets the results generated by a previous query.
- getResultSet() - 类中的方法 weka.gui.sql.event.QueryExecuteEvent
-
returns the resultset that was produced, can be null in case the query failed
- getResultSet() - 类中的方法 weka.gui.sql.ResultSetHelper
-
the underlying resultset.
- getResultsetKeyColumns() - 类中的方法 weka.experiment.PairedTTester
-
Get the value of ResultsetKeyColumns.
- getResultsetKeyColumns() - 接口中的方法 weka.experiment.Tester
-
Get the value of ResultsetKeyColumns.
- getResultsetName(int) - 类中的方法 weka.experiment.PairedTTester
-
Gets a string descriptive of the specified resultset.
- getResultsetName(int) - 接口中的方法 weka.experiment.Tester
-
Gets a string descriptive of the specified resultset.
- getResultsTableName(ResultProducer) - 类中的方法 weka.experiment.DatabaseUtils
-
Gets the name of the experiment table that stores results from a particular ResultProducer.
- getResultTypes() - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getResultTypes() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Gets the data types of each of the result columns produced for a single run.
- getResultTypes() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Gets the data types of each of the result columns produced for a single run.
- getResultTypes() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getResultTypes() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getResultTypes() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Gets the data types of each of the result columns produced for a single run.
- getResultTypes() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getResultTypes() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets the data types of each of the columns produced for a single run.
- getResultTypes() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Gets the data types of each of the result columns produced for a single run.
- getResultTypes() - 接口中的方法 weka.experiment.ResultProducer
-
Gets the data types of each of the result columns produced for a single run.
- getResultTypes() - 接口中的方法 weka.experiment.SplitEvaluator
-
Gets the data types of each of the result columns produced for a single run.
- getResultVector() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the resultVector
- getResultVector() - 类中的方法 weka.clusterers.OPTICS
-
Returns the resultVector
- getReturnValue() - 类中的方法 weka.gui.DatabaseConnectionDialog
-
Returns which of OK or cancel was clicked from dialog
- getReturnValue() - 类中的方法 weka.gui.sql.SqlViewerDialog
-
returns whether the user clicked OK (JOptionPane.OK_OPTION) or whether he cancelled the dialog (JOptionPane.CANCEL_OPTION)
- getRevision() - 类中的方法 weka.associations.AbstractAssociator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.Apriori
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.AprioriItemSet
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.AssociatorEvaluation
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.CaRuleGeneration
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.CheckAssociator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.FilteredAssociator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.FPGrowth
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.gsp.Element
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.gsp.Sequence
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.ItemSet
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.LabeledItemSet
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.PredictiveApriori
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.PriorEstimation
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.RuleGeneration
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.RuleItem
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.AttributeValueLiteral
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.Body
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.Tertius
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.Head
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.IndividualInstance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.IndividualInstances
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.IndividualLiteral
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.Predicate
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.Rule
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.SimpleLinkedList
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListIterator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ASEvaluation
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ASSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.AttributeSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.BestFirst
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.BestFirst.Link2
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.BestFirst.LinkedList2
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval.hashKey
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.CostSensitiveAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.CostSensitiveSubsetEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.LFSMethods
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.LFSMethods.Link2
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.LFSMethods.LinkedList2
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.Ranker
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.RankSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.blr.GaussianPriorImpl
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.blr.LaplacePriorImpl
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.HNB
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.NaiveBayesSimple
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.NaiveBayesUpdateable
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.ADNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.estimate.SimpleEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.ci.CISearchAlgorithm
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.fixed.FromFile
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.fixed.NaiveBayes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.global.TAN
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.local.TAN
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.search.SearchAlgorithm
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.net.VaryNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.bayes.WAODE
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.BVDecompose
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.CheckClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.CheckSource
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.Classifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.CostMatrix
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.evaluation.CostCurve
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.evaluation.EvaluationUtils
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.Evaluation
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.evaluation.MarginCurve
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.evaluation.NominalPrediction
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.evaluation.NumericPrediction
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.evaluation.ThresholdCurve
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.IsotonicRegression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.neural.LinearUnit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.neural.SigmoidUnit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.SMO.BinarySMO
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.CheckKernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.NormalizedPolyKernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.SMOset
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.IB1
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.kstar.KStarCache
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.kstar.KStarCache.TableEntry
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.kstar.KStarNominalAttribute
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.kstar.KStarNumericAttribute
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.kstar.KStarWrapper
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.LBR
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.Bagging
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.ClassificationViaRegression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.Dagging
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.END
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.Grading
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.RandomCommittee
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.Stacking
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.StackingC
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.meta.Vote
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MDD
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MIBoost
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MIDD
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MILR
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MINND
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.supportVector.MIPolyKernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.mi.supportVector.MIRBFKernel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.misc.HyperPipes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.misc.VFI
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.pmml.consumer.GeneralRegression
- getRevision() - 类中的方法 weka.classifiers.pmml.consumer.NeuralNetwork
- getRevision() - 类中的方法 weka.classifiers.pmml.consumer.Regression
- getRevision() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.DecisionTableHashKey
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.DTNB
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.JRip.Antd
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.JRip
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.JRip.NominalAntd
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.JRip.NumericAntd
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.M5Rules
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.NNge
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.OneR
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.part.C45PruneableDecList
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.PART
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.part.MakeDecList
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.part.PruneableDecList
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.Prism
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.RuleStats
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.rules.ZeroR
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.adtree.PredictionNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.adtree.ReferenceInstances
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.DecisionStump
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.ft.FTInnerNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.ft.FTLeavesNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.ft.FTNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.FT
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.Id3
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.BinC45ModelSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.C45ModelSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.EntropySplitCrit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.GainRatioSplitCrit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.J48
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.InfoGainSplitCrit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.NBTreeClassifierTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.NBTreeModelSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.NoSplit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.PruneableClassifierTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.j48.Stats
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.lmt.ResidualModelSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.m5.Impurity
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.m5.PreConstructedLinearModel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.m5.Values
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.M5P
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.trees.UserClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.classifiers.xml.XMLClassifier
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.AbstractClusterer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.CheckClusterer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.CLOPE
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.ClusterEvaluation
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.Cobweb
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.EM
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.FarthestFirst
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.FilteredClusterer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.OPTICS_Visualizer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.ResultVectorTableModel
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERFileFilter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.EpsilonRange_ListElement
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueueElement
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueueElement
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.HierarchicalClusterer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.OPTICS
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.sIB
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns the revision string.
- getRevision() - 类中的方法 weka.clusterers.XMeans
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.AlgVector
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.AllJavadoc
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Attribute
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.AttributeExpression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.AttributeLocator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.AttributeStats
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.BinarySparseInstance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Capabilities
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.ChebyshevDistance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.CheckGOE
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.CheckOptionHandler
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.CheckScheme.PostProcessor
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.ClassDiscovery
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.ClassDiscovery.StringCompare
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.ClassloaderUtil
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.ContingencyTables
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.ArffLoader.ArffReader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.ArffLoader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.ArffSaver
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.C45Loader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.C45Saver
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.ConverterUtils.DataSink
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.ConverterUtils
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.CSVSaver
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.DatabaseConnection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.DatabaseLoader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.LibSVMLoader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.LibSVMSaver
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.SerializedInstancesSaver
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.SVMLightLoader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.SVMLightSaver
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.XRFFLoader
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.converters.XRFFSaver
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Debug.Clock
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Debug.DBO
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Debug
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Debug.Log
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Debug.Random
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Debug.SimpleLog
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Debug.Timestamp
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.EditDistance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Environment
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.EuclideanDistance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.FastVector.FastVectorEnumeration
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.FastVector
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.FindWithCapabilities
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.GlobalInfoJavadoc
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Instance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.InstanceComparator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Instances
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Jython
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.ListOptions
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.logging.ConsoleLogger
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.logging.FileLogger
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.logging.OutputLogger
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.ManhattanDistance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.MathematicalExpression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.CholeskyDecomposition
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.EigenvalueDecomposition
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.ExponentialFormat
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.FlexibleDecimalFormat
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.FloatingPointFormat
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Matrix
-
已过时。Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.IntVector
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.LinearRegression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.LUDecomposition
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.Maths
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.Matrix
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.QRDecomposition
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.matrix.SingularValueDecomposition
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Memory
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.BallNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.BallSplitter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.BottomUpConstructor
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.CoverTree.CoverTreeNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.kdtrees.KMeansInpiredMethod
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.kdtrees.MedianOfWidestDimension
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Option
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.OptionHandlerJavadoc
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.PropertyPath
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.PropertyPath.Path
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.PropertyPath.PathElement
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.ProtectedProperties
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Queue
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.RandomVariates
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Range
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.RelationalLocator
-
Returns the revision string.
- getRevision() - 接口中的方法 weka.core.RevisionHandler
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.SelectedTag
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.SerializationHelper
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.SerializedObject
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.SingleIndex
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.SparseInstance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.SpecialFunctions
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Statistics
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.stemmers.IteratedLovinsStemmer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.stemmers.LovinsStemmer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.stemmers.NullStemmer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.stemmers.SnowballStemmer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.stemmers.Stemming
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Stopwords
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.StringLocator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.SystemInfo
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Tag
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.TechnicalInformation
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.TechnicalInformationHandlerJavadoc
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Tee
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.TestInstances
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.tokenizers.AlphabeticTokenizer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.tokenizers.WordTokenizer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Trie
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Trie.TrieIterator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Trie.TrieNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Utils
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.Version
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.KOML
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.MethodHandler
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.PropertyHandler
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.SerialUIDChanger
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.XMLBasicSerialization
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.XMLDocument
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.XMLInstances
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.XMLOptions
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.XMLSerialization
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.XMLSerializationMethodHandler
-
Returns the revision string.
- getRevision() - 类中的方法 weka.core.xml.XStream
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns the revision string.
- getRevision() - 类中的方法 weka.datagenerators.Test
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.CheckEstimator.AttrTypes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.CheckEstimator.EstTypes
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.CheckEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.CheckEstimator.PostProcessor
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.DDConditionalEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.DiscreteEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.DKConditionalEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.DNConditionalEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.EstimatorUtils
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.KDConditionalEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.KernelEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.KKConditionalEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.MahalanobisEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.NDConditionalEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.NNConditionalEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.NormalEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.estimators.PoissonEstimator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.CSVResultListener
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.DatabaseResultListener
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.Experiment
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.InstanceQuery
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.InstancesResultListener
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.OutputZipper
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.PairedCorrectedTTester
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.PairedStats
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.PairedStatsCorrected
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.PairedTTester
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.PropertyNode
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.RemoteEngine
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.RemoteExperiment
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.RemoteExperimentSubTask
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.ResultMatrixCSV
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.ResultMatrixGnuPlot
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.ResultMatrixHTML
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.ResultMatrixLatex
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.ResultMatrixPlainText
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.ResultMatrixSignificance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.Stats
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.TaskStatusInfo
-
Returns the revision string.
- getRevision() - 类中的方法 weka.experiment.xml.XMLExperiment
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.AllFilter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.CheckSource
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.Filter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.MultiFilter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Center
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.NumericToBinary
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Obfuscate
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.ReplaceMissingValues
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Standardize
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.TimeSeriesDelta
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.TimeSeriesTranslate
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.NonSparseToSparse
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.SparseToNonSparse
-
Returns the revision string.
- getRevision() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Returns the revision string.
- getRevision() - 类中的方法 weka.gui.beans.FlowRunner
- getRevision() - 类中的方法 weka.gui.sql.DbUtils
-
Returns the revision string.
- getRidge() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Get the value of Ridge.
- getRidge() - 类中的方法 weka.classifiers.functions.Logistic
-
Gets the ridge in the log-likelihood.
- getRidge() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Gets the ridge value.
- getRidge() - 类中的方法 weka.classifiers.mi.MILR
-
Gets the ridge in the log-likelihood.
- getRocAnalysis() - 类中的方法 weka.associations.Tertius
-
Get the value of rocAnalysis.
- getROCArea(Instances) - 类中的静态方法 weka.classifiers.evaluation.ThresholdCurve
-
Calculates the area under the ROC curve as the Wilcoxon-Mann-Whitney statistic.
- getROCString() - 类中的方法 weka.gui.visualize.ThresholdVisualizePanel
-
This extracts the ROC area string
- getRoot() - 类中的方法 weka.core.Trie
-
returns the root node of the trie
- getRoot() - 类中的方法 weka.gui.treevisualizer.Node
-
Get the value of root.
- getRootNode() - 类中的方法 weka.core.xml.XMLDocument
-
returns the current root node.
- getRow() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
the comma-separated list of attribute names that identify a row
- getRow(int) - 类中的方法 weka.core.Matrix
-
已过时。Gets a row of the matrix and returns it as double array.
- getRowCount() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.ResultVectorTableModel
-
Returns the number of rows of this model.
- getRowCount() - 类中的方法 weka.experiment.ResultMatrix
-
returns the number of rows
- getRowCount() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the number of rows in the model
- getRowCount() - 类中的方法 weka.gui.SortedTableModel
-
Returns the number of rows in the model.
- getRowCount() - 类中的方法 weka.gui.sql.ResultSetHelper
-
returns the number of rows in the resultset.
- getRowCount() - 类中的方法 weka.gui.sql.ResultSetTableModel
-
returns the number of rows in the model.
- getRowDimension() - 类中的方法 weka.core.matrix.Matrix
-
Get row dimension.
- getRowHidden(int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the hidden status of the row, if the index is valid, otherwise false
- getRowName(int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the name of the row, if the index is valid, otherwise null.
- getRowNameWidth() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current width for the row names
- getRowOrder() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current order of the rows, null means the default order
- getRowPackedCopy() - 类中的方法 weka.core.matrix.Matrix
-
Make a one-dimensional row packed copy of the internal array.
- getRsource() - 类中的方法 weka.gui.treevisualizer.Edge
-
Get the value of rsource.
- getRtarget() - 类中的方法 weka.gui.treevisualizer.Edge
-
Get the value of rtarget.
- getRuleset() - 类中的方法 weka.classifiers.rules.JRip
-
Get the ruleset generated by Ripper
- getRuleset() - 类中的方法 weka.classifiers.rules.RuleStats
-
Get the ruleset of the stats
- getRulesetSize() - 类中的方法 weka.classifiers.rules.RuleStats
-
Get the size of the ruleset in the stats
- getRulesMustContain() - 类中的方法 weka.associations.FPGrowth
-
Get the comma separated list of items that rules must contain in order to be output.
- getRuleStats(int) - 类中的方法 weka.classifiers.rules.JRip
-
Get the statistics of the ruleset in the given position
- getRunColumn() - 类中的方法 weka.experiment.PairedTTester
-
Get the value of RunColumn.
- getRunColumn() - 接口中的方法 weka.experiment.Tester
-
Get the value of RunColumn.
- getRunLower() - 类中的方法 weka.experiment.Experiment
-
Get the lower run number for the experiment.
- getRunNumber() - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Get the run number.
- getRunNumber() - 类中的方法 weka.gui.beans.TestSetEvent
-
Get the run number that this training set belongs to.
- getRunNumber() - 类中的方法 weka.gui.beans.TrainingSetEvent
-
Get the run number that this training set belongs to.
- getRuns() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- getRuns() - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
Returns the number of runs
- getRuns() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- getRuns() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
- getRuns() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- getRuns() - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
- getRuns() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- getRuns() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
- getRunUpper() - 类中的方法 weka.experiment.Experiment
-
Get the upper run number for the experiment.
- getS() - 类中的方法 weka.core.matrix.SingularValueDecomposition
-
Return the diagonal matrix of singular values
- getSampleSize() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Get the number of instances used for estimating attributes
- getSampleSize() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
gets number of samples
- getSampleSize() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Gets the subsample size.
- getSampleSizePercent() - 类中的方法 weka.classifiers.meta.GridSearch
-
Gets the sample size for the initial grid search.
- getSampleSizePercent() - 类中的方法 weka.filters.supervised.instance.Resample
-
Gets the subsample size as a percentage of the original set.
- getSampleSizePercent() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Gets the subsample size as a percentage of the original set.
- getSaveDialogTitle() - 类中的方法 weka.gui.visualize.PrintableComponent
-
returns the title for the save dialog.
- getSaveDialogTitle() - 接口中的方法 weka.gui.visualize.PrintableHandler
-
returns the title for the save dialog
- getSaveDialogTitle() - 类中的方法 weka.gui.visualize.PrintablePanel
-
returns the title for the save dialog
- getSaveInstanceData() - 类中的方法 weka.classifiers.trees.ADTree
-
Gets whether the tree is to save instance data.
- getSaveInstanceData() - 类中的方法 weka.classifiers.trees.J48
-
Check whether instance data is to be saved.
- getSaveInstanceData() - 类中的方法 weka.classifiers.trees.J48graft
-
Check whether instance data is to be saved.
- getSaveInstanceData() - 类中的方法 weka.clusterers.Cobweb
-
Get the value of saveInstances.
- getSaveInstances() - 类中的方法 weka.classifiers.trees.M5P
-
Get whether instance data is being save.
- getSaver() - 类中的方法 weka.gui.ConverterFileChooser
-
returns the saver that was chosen by the user, can be null in case the user aborted the dialog or the open dialog was shown
- getSaverForExtension(String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the saver to use for this kind of extension, returns null if none can be found.
- getSaverForFile(File) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the saver to use for this kind of file, returns null if none can be found.
- getSaverForFile(String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the saver to use for this kind of file, returns null if none can be found.
- getSaverTemplate() - 类中的方法 weka.gui.beans.Saver
-
Get the saver
- getScale() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Get the scaling factor.
- getScalingEnabled() - 类中的方法 weka.gui.visualize.JComponentWriter
-
whether scaling is enabled or ignored
- getScoreType() - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
get quality measure to be used in searching for networks.
- getSearch() - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Get the current search method
- getSearch() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Gets the search method used
- getSearch() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Gets the current search method
- getSearch() - 类中的方法 weka.classifiers.rules.DTNB
-
Gets the current search method
- getSearch() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Get the name of the search method
- getSearchAlgorithm() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Get the SearchAlgorithm used as the search algorithm
- getSearchBackwards() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Get whether to search backwards
- getSearchPath() - 类中的方法 weka.classifiers.trees.ADTree
-
Gets the method of searching the tree for a new insertion.
- getSearchPercent() - 类中的方法 weka.attributeSelection.RandomSearch
-
get the percentage of the search space to consider
- getSearchString() - 类中的方法 weka.gui.arffviewer.ArffTable
-
returns the search string, can be NULL if no search string is set
- getSearchTermination() - 类中的方法 weka.attributeSelection.BestFirst
-
Get the termination criterion (number of non-improving nodes).
- getSearchTermination() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Get the termination criterion (number of non-improving nodes).
- getSecondValueIndex() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Get the index of the second value used.
- getSecondValueIndex() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Get the index of the second value used.
- getSeed() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Gets the seed for the random number generations.
- getSeed() - 类中的方法 weka.attributeSelection.GeneticSearch
-
get the value of the random number generator's seed
- getSeed() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Get the random number seed
- getSeed() - 类中的方法 weka.attributeSelection.RandomSearch
-
Get the random seed to use
- getSeed() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Get the seed used for randomly sampling instances.
- getSeed() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
get the value of the random number generator's seed
- getSeed() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Seed for cross validation subset size determination.
- getSeed() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Get the random number seed used for cross validation
- getSeed() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Get the seed for randomizing the instances for CV-based hyperparameter selection
- getSeed() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- getSeed() - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
Returns the random seed
- getSeed() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- getSeed() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- getSeed() - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
- getSeed() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- getSeed() - 类中的方法 weka.classifiers.BVDecompose
-
Gets the random number seed
- getSeed() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Gets the random number seed
- getSeed() - 类中的方法 weka.classifiers.evaluation.EvaluationUtils
-
Gets the seed for randomization during cross-validation
- getSeed() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getSeed() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Gets the current seed value for the random number generator
- getSeed() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Get the value of Seed.
- getSeed() - 类中的方法 weka.classifiers.functions.Winnow
-
Get the value of Seed.
- getSeed() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Gets the random number seed.
- getSeed() - 类中的方法 weka.classifiers.RandomizableClassifier
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.classifiers.RandomizableMultipleClassifiersCombiner
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.classifiers.RandomizableSingleClassifierEnhancer
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
returns the current seed value for randomizing the data
- getSeed() - 类中的方法 weka.classifiers.rules.JRip
-
Gets the current seed value to use in randomizing the data
- getSeed() - 类中的方法 weka.classifiers.rules.PART
-
Get the value of Seed.
- getSeed() - 类中的方法 weka.classifiers.rules.Ridor
- getSeed() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of Seed.
- getSeed() - 类中的方法 weka.classifiers.trees.RandomForest
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.classifiers.trees.RandomTree
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.classifiers.trees.REPTree
-
Get the value of Seed.
- getSeed() - 类中的方法 weka.clusterers.RandomizableClusterer
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.clusterers.RandomizableDensityBasedClusterer
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.clusterers.RandomizableSingleClustererEnhancer
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Returns the seed for random number generator.
- getSeed() - 接口中的方法 weka.core.Randomizable
-
Gets the seed for the random number generations
- getSeed() - 类中的方法 weka.core.TestInstances
-
returns the current seed value
- getSeed() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Gets the random number seed.
- getSeed() - 类中的方法 weka.datagenerators.DataGenerator
-
Gets the random number seed.
- getSeed() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Get the current randomization seed
- getSeed() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Gets the random number seed used for shuffling the dataset.
- getSeed() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Returns the current seed value for randomizing the order of the generated data
- getSeed() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Get the seed value for the random number generator.
- getSeed() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Gets the random number seed used for shuffling the dataset.
- getSeed() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Get the currently set seed
- getSeed() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Get the value of the random seed
- getSelectedAttributes() - 类中的方法 weka.gui.AttributeSelectionPanel
-
Gets an array containing the indices of all selected attributes.
- getSelectedBuffer() - 类中的方法 weka.gui.ResultHistoryPanel
-
Gets the buffer associated with the currently selected item in the list.
- getSelectedName() - 类中的方法 weka.gui.ResultHistoryPanel
-
Get the name of the currently selected item in the list
- getSelectedObject() - 类中的方法 weka.gui.ResultHistoryPanel
-
Gets the object associated with the currently selected item in the list.
- getSelectedRange() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Gets the current range selection.
- getSelectedRange() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Get the value of m_SelectedRange.
- getSelectedTag() - 类中的方法 weka.core.SelectedTag
-
Gets the selected Tag.
- getSelection() - 类中的方法 weka.core.Range
-
Gets an array containing all the selected values, in the order that they were selected (or ascending order if range inversion is on)
- getSelectionModel() - 类中的方法 weka.gui.AttributeListPanel
-
Gets the selection model used by the table.
- getSelectionModel() - 类中的方法 weka.gui.AttributeSelectionPanel
-
Gets the selection model used by the table.
- getSelectionModel() - 类中的方法 weka.gui.ResultHistoryPanel
-
Gets the selection model used by the results list.
- getSelectionThreshold() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
- getSeparatingThreshold() - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Gets the separating threshold value.
- getSeparatingThreshold() - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Gets the separating threshold value.
- getSeperator() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Get the seperator between levels.
- getSequentialAttIndex(int) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the boolean value at the specified index in the Sequential Attribute Indexes array
- getSequentialInstanceIndex(int) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the boolean value at the specified index in the Sequential Instance Indexes array
- getSequentialNumAttributes() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the number of attributes in the Sequential array
- getSequentialNumInstances() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns the number of instances in the Sequential array
- getSerializedClassifierFile() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Gets the file pointing to a serialized, trained classifier.
- getSERObject() - 类中的方法 weka.clusterers.OPTICS
-
Returns the internal database
- getSetNumber() - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Get the set number (ie which fold this is)
- getSetNumber() - 类中的方法 weka.gui.beans.BatchClustererEvent
-
Get the set number (ie which fold this is)
- getSetNumber() - 类中的方法 weka.gui.beans.TestSetEvent
-
Get the test set number (eg.
- getSetNumber() - 类中的方法 weka.gui.beans.TrainingSetEvent
-
Get the set number (eg.
- getShape() - 类中的方法 weka.gui.treevisualizer.Node
-
Get the value of shape.
- getShowAttBars() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Gets whether or not attribute bars are being displayed.
- getShowAverage() - 类中的方法 weka.experiment.ResultMatrix
-
returns whether average per column is displayed or not
- getShowAverage() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns whether the Average is shown by default
- getShowAverage() - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
returns whether the average for each column is displayed.
- getShowClassPanel() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Gets whether or not the class panel is being displayed.
- getShowGUI() - 类中的方法 weka.clusterers.OPTICS
-
Returns the flag for showing the OPTICS visualizer GUI.
- getShowStdDev() - 类中的方法 weka.experiment.ResultMatrix
-
returns whether std deviations are displayed or not
- getShowStdDevs() - 类中的方法 weka.experiment.PairedTTester
-
Returns true if standard deviations have been requested.
- getShowStdDevs() - 接口中的方法 weka.experiment.Tester
-
Returns true if standard deviations have been requested.
- getShowStdDevs() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns whether StdDevs are shown by default
- getShowZeroInstancesAsUnknown() - 类中的方法 weka.gui.InstancesSummaryPanel
-
Get whether to show zero instances as unknown (i.e.
- getShrinkage() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Get the shrinkage rate.
- getShrinkage() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Get the value of Shrinkage.
- getShrinking() - 类中的方法 weka.classifiers.functions.LibSVM
-
whether to use the shrinking heuristics
- getShuffle() - 类中的方法 weka.classifiers.rules.Ridor
- getSigma() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Get the value of sigma.
- getSigma() - 类中的方法 weka.classifiers.BVDecompose
-
Get the calculated sigma squared
- getSigma() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Gets the sigma value.
- getSignificance() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the default significance
- getSignificance(int, int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the significance at the given position, if the position is valid, otherwise SIGNIFICANCE_ATIE
- getSignificanceCount(int, int) - 类中的方法 weka.experiment.ResultMatrix
-
counts the occurrences of the given significance type in the given column.
- getSignificanceLevel() - 类中的方法 weka.associations.Apriori
-
Get the value of significanceLevel.
- getSignificanceLevel() - 类中的方法 weka.attributeSelection.RaceSearch
-
Get the significance level
- getSignificanceLevel() - 类中的方法 weka.experiment.PairedTTester
-
Get the value of SignificanceLevel.
- getSignificanceLevel() - 接口中的方法 weka.experiment.Tester
-
Get the value of SignificanceLevel.
- getSignificanceWidth() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current width for the significance
- getSilent() - 类中的方法 weka.core.Check
-
Get whether silent mode is turned on
- getSilent() - 类中的方法 weka.core.Javadoc
-
whether output in the console is suppressed
- getSilent() - 类中的方法 weka.estimators.CheckEstimator
-
Get whether silent mode is turned on
- getSimpleStats(int) - 类中的方法 weka.classifiers.rules.RuleStats
-
Get the simple stats of one rule, including 6 parameters: 0: coverage; 1:uncoverage; 2: true positive; 3: true negatives; 4: false positives; 5: false negatives
- getSIndex() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Get the index of the shape selected for creating splits.
- getSingleIndex() - 类中的方法 weka.core.SingleIndex
-
Gets the string representing the selected range of values
- getSingleModeFlag() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Return if single mode is set for the given data generator mode depends on option setting and or generator type.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Return if single mode is set for the given data generator mode depends on option setting and or generator type.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Return if single mode is set for the given data generator mode depends on option setting and or generator type.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Return if single mode is set for the given data generator mode depends on option setting and or generator type.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the single mode flag.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Return if single mode is set for the given data generator mode depends on option setting and or generator type.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Return if single mode is set for the given data generator mode depends on option setting and or generator type.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Gets the single mode flag.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Gets the single mode flag.
- getSingleModeFlag() - 类中的方法 weka.datagenerators.DataGenerator
-
Return if single mode is set for the given data generator mode depends on option setting and or generator type.
- getSingleton() - 类中的静态方法 weka.core.logging.Logger
-
Returns the singleton instance of the logger.
- getSingleton() - 类中的静态方法 weka.gui.beans.KnowledgeFlowApp
-
Return the singleton instance of the KnowledgeFlow
- getSingleton() - 类中的静态方法 weka.gui.GUIChooser
-
Get the singleton instance of the GUIChooser
- getSingleton() - 类中的静态方法 weka.gui.Main
-
Return the singleton instance of the Main GUI.
- getSingularValues() - 类中的方法 weka.core.matrix.SingularValueDecomposition
-
Return the one-dimensional array of singular values
- getSize() - 类中的方法 weka.core.Debug.Log
-
returns the size of the files
- getSizePer() - 类中的方法 weka.classifiers.trees.BFTree
-
Get training set size.
- getSizePer() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Get training set size.
- getSkipIdentical() - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Gets whether if identical instances are skipped from the neighbourhood.
- getSlope() - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Returns the slope of the function.
- getSmoothing() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Get whether or not smoothing has been turned on
- getSmoothingParameter() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Gets the smoothing value to be used to avoid zero WordGivenClass probabilities.
- getSort() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Gets whether the labels are sorted or not.
- getSortColumn() - 类中的方法 weka.experiment.PairedTTester
-
Returns the column to sort on, -1 means the default sorting.
- getSortColumn() - 接口中的方法 weka.experiment.Tester
-
Returns the column to sort on, -1 means the default sorting.
- getSortColumnName() - 类中的方法 weka.experiment.PairedTTester
-
Returns the name of the column to sort on.
- getSortColumnName() - 接口中的方法 weka.experiment.Tester
-
Returns the name of the column to sort on.
- getSorting() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the default sorting (empty string means none)
- getSource() - 类中的方法 weka.gui.beans.BeanConnection
-
returns the source BeanInstance for this connection
- getSource() - 类中的方法 weka.gui.treevisualizer.Edge
-
Get the value of source.
- getSourceCode() - 类中的方法 weka.classifiers.CheckSource
-
Gets the class to test.
- getSourceCode() - 类中的方法 weka.filters.CheckSource
-
Gets the class to test.
- getSparseData() - 类中的方法 weka.experiment.InstanceQuery
-
Gets whether data is to be returned as a set of sparse instances
- getSplitByDataSet() - 类中的方法 weka.experiment.RemoteExperiment
-
Returns true if sub experiments are to be created on the basis of data set..
- getSplitDim() - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNode
-
Gets the splitting dimension.
- getSplitEvaluator() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Get the SplitEvaluator.
- getSplitEvaluator() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Get the SplitEvaluator.
- getSplitOnResiduals() - 类中的方法 weka.classifiers.trees.LMT
-
Get the value of splitOnResiduals.
- getSplitPoint() - 类中的方法 weka.classifiers.rules.JRip.NumericAntd
-
Get split point of this numeric antecedent
- getSplitPoint() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Get the split point used for numeric selection
- getSplitValue() - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNode
-
Gets the splitting value.
- getSquaredError() - 类中的方法 weka.clusterers.SimpleKMeans
-
Gets the squared error for all clusters
- getStamp() - 类中的方法 weka.core.Debug.Timestamp
-
returns the associated date/time
- getStandardDeviation(Instance) - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Gives the variance of the prediction at the given instance
- getStart() - 类中的方法 weka.core.Debug.Clock
-
returns the start time
- getStartMessage() - 类中的方法 weka.gui.beans.Loader
-
Gets a string that describes the start action.
- getStartMessage() - 接口中的方法 weka.gui.beans.Startable
-
Gets a string that describes the start action.
- getStartPoint() - 类中的方法 weka.attributeSelection.RankSearch
-
Get the point at which to start evaluating the ranking
- getStartSequentially() - 类中的方法 weka.gui.beans.FlowRunner
-
Gets whether Startable beans will be launched sequentially or all in parallel.
- getStartSet() - 类中的方法 weka.attributeSelection.BestFirst
-
Returns a list of attributes (and or attribute ranges) as a String
- getStartSet() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns a list of attributes (and or attribute ranges) as a String
- getStartSet() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns a list of attributes (and or attribute ranges) as a String
- getStartSet() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns a list of attributes (and or attribute ranges) as a String
- getStartSet() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns a list of attributes (and or attribute ranges) as a String
- getStartSet() - 类中的方法 weka.attributeSelection.Ranker
-
Returns a list of attributes (and or attribute ranges) as a String
- getStartSet() - 接口中的方法 weka.attributeSelection.StartSetHandler
-
Returns a list of attributes (and or attribute ranges) as a String
- getStaticIcon() - 类中的方法 weka.gui.beans.BeanVisual
-
Returns the static icon
- getStats() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns a string representation of the statistics.
- getStats() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns a string representation of the statistics.
- getStatus() - 类中的方法 weka.gui.beans.IncrementalClassifierEvent
-
Get the status
- getStatus() - 类中的方法 weka.gui.beans.InstanceEvent
-
Get the status
- getStatusFrequency() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Get how often progress is reported to the status bar.
- getStatusMessage() - 类中的方法 weka.experiment.TaskStatusInfo
-
Get the status message.
- getStatusTable() - 类中的方法 weka.gui.beans.LogPanel
-
The JTable used for the status messages (in case clients want to attach listeners etc.)
- getStdDev() - 类中的方法 weka.estimators.KernelEstimator
-
Return the standard deviation of this kernel estimator.
- getStdDev() - 类中的方法 weka.estimators.NormalEstimator
-
Return the value of the standard deviation of this normal estimator.
- getStdDev(int, int) - 类中的方法 weka.experiment.ResultMatrix
-
returns the std deviation at the given position, if the position is valid, otherwise 0
- getStdDevCoordsPerPoint() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the standard deviation of coords per point.
- getStdDevIntNodesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the standard deviation of internal nodes visited.
- getStdDevLeavesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the standard deviation of leaves visited.
- getStdDevPointsVisited() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the standard deviation of points visited.
- getStdDevPrec() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current standard deviation precision
- getStdDevPrec() - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
Gets the precision used for printing the std.
- getStdDevPrecision() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the default precision for the stddevs
- getStddevValue() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
- getStdDevWidth() - 类中的方法 weka.experiment.ResultMatrix
-
returns the current width for the std dev
- getStemmer() - 类中的方法 weka.core.stemmers.SnowballStemmer
-
returns the name of the current stemmer, null if none is set.
- getStemmer() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the current stemming algorithm, null if none is used.
- getStepSize() - 类中的方法 weka.attributeSelection.RankSearch
-
Get the number of attributes to add from the rankining in each iteration
- getStepSize() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Get the value of StepSize.
- getStop() - 类中的方法 weka.core.Debug.Clock
-
returns the stop time or, if still running, the current time
- getStopwords() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
returns the file used for obtaining the stopwords, if the file represents a directory then the default ones are used.
- getString() - 类中的方法 weka.core.Trie.TrieNode
-
returns the full string up to the root
- getString(int[]) - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Returns the list of indices as a string.
- getString(int[]) - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Returns the list of indices as a string.
- getString(String) - 类中的静态方法 weka.associations.gsp.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.associations.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.arffviewer.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.beans.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.beans.xml.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.boundaryvisualizer.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.experiment.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.explorer.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.graphvisualizer.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.hierarchyvisualizer.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.sql.event.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.sql.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.streams.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.treevisualizer.Messages
-
getString.
- getString(String) - 类中的静态方法 weka.gui.visualize.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.associations.gsp.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.associations.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.arffviewer.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.beans.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.beans.xml.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.boundaryvisualizer.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.experiment.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.explorer.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.graphvisualizer.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.hierarchyvisualizer.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.sql.event.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.sql.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.streams.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.treevisualizer.Messages
-
getString.
- getString(String, Locale) - 类中的静态方法 weka.gui.visualize.Messages
-
getString.
- getStringAttributes() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the current attribute range to be forced to type string.
- getStringSelection() - 类中的方法 weka.gui.arffviewer.ArffTable
-
returns the selected content in a StringSelection that can be copied to the clipboard and used in Excel, if nothing is selected the whole table is copied to the clipboard
- getStroke() - 类中的方法 weka.gui.visualize.PostscriptGraphics
- getStructure() - 类中的方法 weka.core.converters.AbstractLoader
- getStructure() - 类中的方法 weka.core.converters.ArffLoader.ArffReader
-
Returns the header format
- getStructure() - 类中的方法 weka.core.converters.ArffLoader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.core.converters.C45Loader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
returns the structure of the data.
- getStructure() - 类中的方法 weka.core.converters.CSVLoader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.core.converters.DatabaseLoader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.core.converters.LibSVMLoader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 接口中的方法 weka.core.converters.Loader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.core.converters.SVMLightLoader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.core.converters.XRFFLoader
-
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
- getStructure() - 类中的方法 weka.gui.beans.IncrementalClassifierEvent
-
Get the instances structure (may be null if this is not a NEW_BATCH event)
- getStructure() - 类中的方法 weka.gui.beans.InstanceEvent
-
Get the instances structure (may be null if this is not a FORMAT_AVAILABLE event)
- getStructure(int) - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
returns the structure of the data, with the defined class index.
- getStructure(String) - 类中的方法 weka.gui.beans.ClassAssigner
-
Get the structure of the output encapsulated in the named event.
- getStructure(String) - 类中的方法 weka.gui.beans.ClassValuePicker
- getStructure(String) - 类中的方法 weka.gui.beans.Loader
-
Get the structure of the output encapsulated in the named event.
- getStructure(String) - 接口中的方法 weka.gui.beans.StructureProducer
-
Get the structure of the output encapsulated in the named event.
- getSubFlow() - 类中的方法 weka.gui.beans.MetaBean
- getSubmenuTitle() - 接口中的方法 weka.gui.MainMenuExtension
-
Returns the name of the submenu.
- getSubsequenceLength() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the length of the subsequence
- getSubsetEvaluator() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Get the subset evaluator to use
- getSubsetSizeEvaluator() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Get the subset evaluator used for subset size determination.
- getSubSpaceSize() - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Gets the size of each subSpace, as a percentage of the training set size.
- getSubtreeRaising() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of subtreeRaising.
- getSubtreeRaising() - 类中的方法 weka.classifiers.trees.J48graft
-
Get the value of subtreeRaising.
- getSuccess() - 类中的方法 weka.core.CheckGOE
-
returns the success of the tests
- getSuccess() - 类中的方法 weka.core.CheckOptionHandler
-
returns the success of the tests
- getSuitableTargets(EventSetDescriptor) - 类中的方法 weka.gui.beans.MetaBean
-
Return a list of input beans capable of receiving the supplied event
- getSummary() - 类中的方法 weka.gui.SetInstancesPanel
-
Gets the instances summary panel associated with this panel
- getSumOfCounts() - 类中的方法 weka.estimators.DiscreteEstimator
-
Get the sum of all the counts
- getSumOfWeights() - 类中的方法 weka.estimators.NormalEstimator
-
Return the sum of the weights for this normal estimator.
- getSupportedCursorScrollType() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns the type of scrolling that the cursor supports, -1 if not supported or not connected.
- getSVMType() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Gets type of SVM
- getSVMType() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets type of SVM
- getSymbols() - 类中的方法 weka.core.mathematicalexpression.Parser
-
Returns the current variable - value relation in use.
- getSymbols() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Returns the current variable - value relation in use.
- getSystemInfo() - 类中的方法 weka.core.SystemInfo
-
returns a copy of the system info.
- getSystemLookAndFeel() - 类中的静态方法 weka.gui.LookAndFeel
-
returns the system LnF classname
- getSystemWide() - 类中的静态方法 weka.core.Environment
-
Get the singleton system-wide (visible to every class in the running VM) set of environment variables.
- getTabbedPane() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns the tabbedpane instance
- getTabbedPane() - 类中的方法 weka.gui.explorer.Explorer
-
returns the tabbed pane of the Explorer
- getTable() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns the table component
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - 类中的方法 weka.gui.arffviewer.ArffTableCellRenderer
-
Returns the default table cell renderer.
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - 类中的方法 weka.gui.sql.ResultSetTableCellRenderer
-
Returns the default table cell renderer.
- getTableModel() - 类中的方法 weka.gui.AttributeSelectionPanel
-
Get the table model in use (or null if no instances have been set yet).
- getTableName() - 类中的方法 weka.core.converters.DatabaseSaver
-
Gets the table's name.
- getTabs() - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
returns an array with the classnames of all the additional panels to display as tabs in the Explorer.
- getTabTitle() - 类中的方法 weka.gui.explorer.AssociationsPanel
-
Returns the title for the tab in the Explorer
- getTabTitle() - 类中的方法 weka.gui.explorer.AttributeSelectionPanel
-
Returns the title for the tab in the Explorer
- getTabTitle() - 类中的方法 weka.gui.explorer.ClassifierPanel
-
Returns the title for the tab in the Explorer
- getTabTitle() - 类中的方法 weka.gui.explorer.ClustererPanel
-
Returns the title for the tab in the Explorer
- getTabTitle() - 接口中的方法 weka.gui.explorer.Explorer.ExplorerPanel
-
Returns the title for the tab in the Explorer
- getTabTitle() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Returns the title for the tab in the Explorer
- getTabTitle() - 类中的方法 weka.gui.explorer.VisualizePanel
-
Returns the title for the tab in the Explorer
- getTabTitleToolTip() - 类中的方法 weka.gui.explorer.AssociationsPanel
-
Returns the tooltip for the tab in the Explorer
- getTabTitleToolTip() - 类中的方法 weka.gui.explorer.AttributeSelectionPanel
-
Returns the tooltip for the tab in the Explorer
- getTabTitleToolTip() - 类中的方法 weka.gui.explorer.ClassifierPanel
-
Returns the tooltip for the tab in the Explorer
- getTabTitleToolTip() - 类中的方法 weka.gui.explorer.ClustererPanel
-
Returns the tooltip for the tab in the Explorer
- getTabTitleToolTip() - 接口中的方法 weka.gui.explorer.Explorer.ExplorerPanel
-
Returns the tooltip for the tab in the Explorer
- getTabTitleToolTip() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Returns the tooltip for the tab in the Explorer
- getTabTitleToolTip() - 类中的方法 weka.gui.explorer.VisualizePanel
-
Returns the tooltip for the tab in the Explorer
- getTabuList() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
- getTabuList() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
- getTags() - 类中的方法 weka.core.SelectedTag
-
Gets the set of all valid Tags.
- getTags() - 类中的方法 weka.gui.CostMatrixEditor
-
Some objects can return tags, but a cost matrix cannot.
- getTags() - 类中的方法 weka.gui.GenericArrayEditor
-
Returns null as we don't support getting values as tags.
- getTags() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns null as we don't support getting values as tags.
- getTags() - 类中的方法 weka.gui.SelectedTagEditor
-
Gets the list of tags that can be selected from.
- getTags() - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Some objects can return tags, but a date format cannot.
- getTarget() - 类中的方法 weka.gui.beans.BeanConnection
-
Returns the target BeanInstance for this connection
- getTarget() - 类中的方法 weka.gui.treevisualizer.Edge
-
Get the value of target.
- getTargetClass() - 类中的方法 weka.classifiers.bayes.DMNBtext.DNBBinary
-
Gets the Target Class
- getTargetMetaData() - 类中的方法 weka.core.pmml.MiningSchema
-
Get the Target meta data.
- getTaskResult() - 类中的方法 weka.experiment.TaskStatusInfo
-
Get the returnable result of this task.
- getTaskStatus() - 类中的方法 weka.experiment.RemoteExperimentSubTask
- getTaskStatus() - 接口中的方法 weka.experiment.Task
-
Clients should be able to call this method at any time to obtain information on a current task.
- getTaskStatus() - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Return status information for this sub task
- getTechnicalInformation() - 类中的方法 weka.associations.Apriori
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.associations.FPGrowth
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns TechnicalInformation about the paper related to the algorithm.
- getTechnicalInformation() - 类中的方法 weka.associations.PredictiveApriori
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.associations.Tertius
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.RankSearch
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.HNB
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.NaiveBayesSimple
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.NaiveBayesUpdateable
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.ADNode
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.search.global.TAN
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.net.search.local.TAN
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.bayes.WAODE
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.BVDecompose
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.SMO
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.lazy.IB1
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.lazy.LBR
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.Bagging
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.ClassificationViaRegression
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.Dagging
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.END
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.Grading
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.Stacking
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.StackingC
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.meta.Vote
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MDD
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MIBoost
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MIDD
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MINND
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.misc.VFI
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.rules.DTNB
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.rules.JRip
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.rules.M5Rules
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.rules.NNge
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.rules.OneR
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.rules.PART
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.rules.Prism
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.FT
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.Id3
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.J48
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.LMT
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.classifiers.trees.UserClassifier
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.clusterers.CLOPE
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.clusterers.Cobweb
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.clusterers.DBSCAN
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.clusterers.FarthestFirst
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.clusterers.OPTICS
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.clusterers.sIB
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.clusterers.XMeans
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.ChebyshevDistance
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.EuclideanDistance
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.ManhattanDistance
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.balltrees.BottomUpConstructor
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.kdtrees.KMeansInpiredMethod
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.kdtrees.MedianOfWidestDimension
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.Optimization
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.core.stemmers.LovinsStemmer
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 接口中的方法 weka.core.TechnicalInformationHandler
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.experiment.PairedCorrectedTTester
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTechnicalInformation() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
- getTempDir() - 类中的静态方法 weka.core.Debug
-
returns the system temp directory
- getTester() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the display name of the preferred Tester algorithm
- getTestEvaluator() - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Gets whether the evaluator is being tested or the search method.
- getTestOrTrain() - 类中的方法 weka.gui.beans.BatchClustererEvent
-
Get whether the set of instances is a test or a training set
- getTestPredictions(Classifier, Instances) - 类中的方法 weka.classifiers.evaluation.EvaluationUtils
-
Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.
- getTestSet() - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Get the test set
- getTestSet() - 类中的方法 weka.gui.beans.BatchClustererEvent
-
Get the training/test set
- getTestSet() - 类中的方法 weka.gui.beans.TestSetEvent
-
Get the test set instances
- getText() - 类中的方法 weka.gui.beans.BeanVisual
-
Get the visual's label
- getText() - 类中的方法 weka.gui.beans.TextEvent
-
Describe
getText
method here. - getTextTitle() - 类中的方法 weka.gui.beans.TextEvent
-
Describe
getTextTitle
method here. - getTFTransform() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
- getThreshold() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
- getThreshold() - 类中的方法 weka.attributeSelection.RaceSearch
-
Get the threshold
- getThreshold() - 接口中的方法 weka.attributeSelection.RankedOutputSearch
-
Gets the threshold by which attributes can be discarded.
- getThreshold() - 类中的方法 weka.attributeSelection.Ranker
-
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
- getThreshold() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Get the treshold
- getThreshold() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Get the value of the threshold
- getThreshold() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Return the threshold being used.
- getThreshold() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Gets the threshold for olsc estimator
- getThreshold() - 类中的方法 weka.classifiers.functions.Winnow
-
Get the value of Threshold.
- getThreshold() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Gets the threshold for the max error when predicting a numeric class.
- getThresholdInstance(Instances, double) - 类中的静态方法 weka.classifiers.evaluation.ThresholdCurve
-
Gets the index of the instance with the closest threshold value to the desired target
- getTimestamp() - 类中的静态方法 weka.experiment.CrossValidationResultProducer
-
Gets a Double representing the current date and time.
- getTimestamp() - 类中的静态方法 weka.experiment.RandomSplitResultProducer
-
Gets a Double representing the current date and time.
- getTitle() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns the title for the Tab, i.e.
- getToken(StreamTokenizer) - 类中的静态方法 weka.core.converters.ConverterUtils
-
Gets token.
- getTokenizer() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the current tokenizer algorithm.
- getTolerance() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Get the tolerance value
- getTolerance() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
returns the current tolerance
- getToleranceParameter() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Get the value of T used with SMO
- getToleranceParameter() - 类中的方法 weka.classifiers.functions.SMO
-
Get the value of tolerance parameter.
- getToleranceParameter() - 类中的方法 weka.classifiers.mi.MISMO
-
Get the value of tolerance parameter.
- getToolTipText() - 类中的方法 weka.experiment.PairedCorrectedTTester
-
returns a string that is displayed as tooltip on the "perform test" button in the experimenter
- getToolTipText() - 类中的方法 weka.experiment.PairedTTester
-
returns a string that is displayed as tooltip on the "perform test" button in the experimenter
- getToolTipText() - 接口中的方法 weka.experiment.Tester
-
returns a string that is displayed as tooltip on the "perform test" button in the experimenter
- getToolTipText() - 类中的方法 weka.gui.GenericObjectEditor.GOETreeNode
-
Get the tool tip for this node
- getToolTipText(MouseEvent) - 类中的方法 weka.gui.AttributeVisualizationPanel
-
Returns "<nominal value> [<nominal value count>]" if displaying a bar plot and mouse is on some bar.
- getToolTipText(PrintableComponent) - 类中的静态方法 weka.gui.visualize.PrintableComponent
-
Returns a tooltip only if the user wants it.
- getTop() - 类中的方法 weka.gui.treevisualizer.Node
-
Get the value of top.
- getTotalCoordsPerPoint() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the total sum of coords per point.
- getTotalCount(Node, int) - 类中的静态方法 weka.gui.treevisualizer.Node
-
Recursively finds the total number of nodes there are.
- getTotalGCount(Node, int) - 类中的静态方法 weka.gui.treevisualizer.Node
-
Recursively finds the total number of groups of siblings there are.
- getTotalHeight(Node, int) - 类中的静态方法 weka.gui.treevisualizer.Node
-
Recursively finds the total number of levels there are.
- getTotalIntNodesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the total number of internal nodes visited.
- getTotalLeavesVisited() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Returns the total number of leaves visited.
- getTotalPointsVisited() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Returns the total number of points visited.
- getTotalSupport() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get the total support for this rule (premise + consequence).
- getTotalTransactions() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get the total number of transactions in the data.
- getToYear() - 类中的静态方法 weka.core.Copyright
-
returns the end year of the copyright (i.e., current year)
- getTPRate() - 类中的方法 weka.associations.tertius.Rule
-
Get the rate of True Positive instances of this rule.
- getTrainingSet() - 类中的方法 weka.gui.beans.TrainingSetEvent
-
Get the training instances
- getTrainingTime() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getTrainIterations() - 类中的方法 weka.classifiers.BVDecompose
-
Gets the maximum number of boost iterations
- getTrainPercent() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Get the value of TrainPercent.
- getTrainPercent() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Get the percentage of the data that will be in the training portion of the split
- getTrainPercentage() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
returns the training percentage in case of splits
- getTrainPoolSize() - 类中的方法 weka.classifiers.BVDecompose
-
Get the number of instances in the training pool.
- getTrainSet() - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Get the train set
- getTrainSize() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the training size
- getTrainTestPredictions(Classifier, Instances, Instances) - 类中的方法 weka.classifiers.evaluation.EvaluationUtils
-
Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set.
- getTransactionsMustContain() - 类中的方法 weka.associations.FPGrowth
-
Gets the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.
- getTransform() - 类中的方法 weka.gui.visualize.PostscriptGraphics
- getTransformAllValues() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Gets if all nominal values are turned into new attributes, not only if there are more than 2.
- getTransformAllValues() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Gets if all nominal values are turned into new attributes, not only if there are more than 2.
- getTransformationDictionary() - 类中的方法 weka.core.pmml.MiningSchema
-
Get the transformation dictionary .
- getTransformBackToOriginal() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Gets whether the data is to be transformed back to the original space.
- getTransformMethod() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Get the method used in transformation.
- getTranslation() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Get the translation.
- getTraversal() - 类中的方法 weka.classifiers.meta.GridSearch
-
Gets the type of traversal for the grid.
- getTrimingThreshold() - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Gets the triming thresholding value.
- getTrimingThreshold() - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Gets the triming thresholding value.
- getTrueNegative() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Gets the number of negative instances predicted as negative
- getTruePositive() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Gets the number of positive instances predicted as positive
- getTruePositiveRate() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Calculate the true positive rate.
- getTStart() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- getTStart() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- getTwoClassStats(int) - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Gets the performance with respect to one of the classes as a TwoClassStats object.
- getType() - 类中的方法 weka.associations.tertius.IndividualLiteral
- getType() - 类中的方法 weka.associations.tertius.LiteralSet
-
Give the type of properties in this set (individual or part properties).
- getType() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Get the type
- getType() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Get the type
- getType() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- getType() - 类中的方法 weka.core.AttributeLocator
-
returns the type of attribute that is located
- getType() - 类中的方法 weka.core.TechnicalInformation
-
returns the type of this technical information
- getType() - 类中的方法 weka.gui.sql.event.ConnectionEvent
-
returns the type of this event, CONNECT or DISCONNECT
- getType(int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns the TYPE of the attribute at the given position
- getType(int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the TYPE of the attribute at the given position
- getType(int, int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns the TYPE of the attribute at the given position
- getType(int, int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the TYPE of the attribute at the given position
- getType(String) - 类中的静态方法 weka.core.RevisionUtils
-
Determines the type of a (sanitized) revision string.
- getType(RevisionHandler) - 类中的静态方法 weka.core.RevisionUtils
-
Determines the type of a (sanitized) revision string returned by the RevisionHandler.
- getU() - 类中的方法 weka.core.Matrix
-
已过时。Returns the U part of the matrix.
- getU() - 类中的方法 weka.core.matrix.LUDecomposition
-
Return upper triangular factor
- getU() - 类中的方法 weka.core.matrix.SingularValueDecomposition
-
Return the left singular vectors
- getUID(Class) - 类中的静态方法 weka.core.SerializationHelper
-
reads or creates the serialVersionUID for the given class.
- getUID(String) - 类中的静态方法 weka.core.SerializationHelper
-
reads or creates the serialVersionUID for the given class.
- getUnpruned() - 类中的方法 weka.classifiers.rules.PART
-
Get the value of unpruned.
- getUnpruned() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of unpruned.
- getUnpruned() - 类中的方法 weka.classifiers.trees.J48graft
-
Get the value of unpruned.
- getUnpruned() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Get whether unpruned tree/rules are being generated
- getUnpruned() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Get whether unpruned tree/rules are being generated
- getUpdateCount() - 类中的方法 weka.core.converters.DatabaseConnection
-
Dewtermines if the current query retrieves a result set or updates a table
- getUpdateIncrementalClassifier() - 类中的方法 weka.gui.beans.Classifier
-
Get whether an incremental classifier will be updated on the incoming instance stream.
- getUpper() - 类中的方法 weka.gui.experiment.RunNumberPanel
-
Gets the current upper run number.
- getUpperBoundMinSupport() - 类中的方法 weka.associations.Apriori
-
Get the value of upperBoundMinSupport.
- getUpperBoundMinSupport() - 类中的方法 weka.associations.FPGrowth
-
Get the value of upperBoundMinSupport.
- getUpperCase() - 类中的方法 weka.core.converters.DatabaseConnection
-
Check if the property checkUpperCaseNames in the DatabaseUtils file is set to true or false.
- getUpperNumericBound() - 类中的方法 weka.core.Attribute
-
Returns the upper bound of a numeric attribute.
- getUpperSize() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Get the value of UpperSize.
- getUrl() - 接口中的方法 weka.core.converters.DatabaseConverter
- getUrl() - 类中的方法 weka.core.converters.DatabaseLoader
-
Gets the URL
- getUrl() - 类中的方法 weka.core.converters.DatabaseSaver
-
Gets the database URL.
- getURL() - 类中的静态方法 weka.core.Copyright
-
returns the URL of the owner
- getURL() - 类中的方法 weka.gui.DatabaseConnectionDialog
-
Returns URL from dialog
- getURL() - 类中的方法 weka.gui.sql.ConnectionPanel
-
returns the current URL.
- getURL() - 类中的方法 weka.gui.sql.event.ResultChangedEvent
-
returns the database URL that produced the table model
- getURL() - 类中的方法 weka.gui.sql.ResultSetTable
-
returns the database URL that produced the table model
- getURL() - 类中的方法 weka.gui.sql.SqlViewer
-
returns the database URL from the currently active tab in the ResultPanel, otherwise an empty string.
- getURL() - 类中的方法 weka.gui.sql.SqlViewerDialog
-
returns the chosen URL, if any
- getURL(String) - 类中的方法 weka.gui.Loader
-
returns a URL for the given filename, can be NULL if it fails
- getURL(String, String) - 类中的静态方法 weka.gui.Loader
-
returns a URL for the given filename, can be NULL if it fails
- getURLFileLoaders() - 类中的静态方法 weka.core.converters.ConverterUtils
-
returns a vector with the classnames of all the URL file loaders.
- getURLLoaderForExtension(String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the URL loader to use for this kind of extension, returns null if none can be found.
- getURLLoaderForFile(File) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the URL loader to use for this kind of file, returns null if none can be found.
- getURLLoaderForFile(String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
tries to determine the URL loader to use for this kind of file, returns null if none can be found.
- getUsageType() - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Get the usage type of this field.
- getUseADTree() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Method declaration
- getUseAIC() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Get the value of useAIC.
- getUseAIC() - 类中的方法 weka.classifiers.trees.FT
-
Get the value of useAIC.
- getUseAIC() - 类中的方法 weka.classifiers.trees.LMT
-
Get the value of useAIC.
- getUseAIC() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Get the value of useAIC.
- getUseArcReversal() - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
get use the arc reversal operation
- getUseArcReversal() - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
get use the arc reversal operation
- getUseBetterEncoding() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Gets whether better encoding is to be used for MDL.
- getUseClassification() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
whether classification or regression is used
- getUseCpuTime() - 类中的方法 weka.core.Debug.Clock
-
returns whether the use of CPU is time is enabled/disabled (regardless whether the system supports it or not)
- getUseCrossOver() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- getUseCrossOver() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- getUseCrossValidation() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Get the value of useCrossValidation.
- getUseCustomDimensions() - 类中的方法 weka.gui.visualize.JComponentWriter
-
whether custom dimensions are to used for the size of the image
- getUsedAttributes() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Returns an array of the indices of the attributes used in the logistic model.
- getUseEqualFrequency() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Get the value of UseEqualFrequency.
- getUseEqualFrequency() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Get the value of UseEqualFrequency.
- getUseEqualFrequency() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Get the value of UseEqualFrequency.
- getUseErrorRate() - 类中的方法 weka.classifiers.trees.BFTree
-
Get if use error rate in internal cross-validation.
- getUseGini() - 类中的方法 weka.classifiers.trees.BFTree
-
Get if use Gini index as splitting criterion.
- getUseGUI() - 类中的方法 weka.core.Memory
-
whether to display a dialog in case of a problem (= TRUE) or just print on stderr (= FALSE)
- getUseIBk() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Gets whether IBk is being used instead of the majority class
- getUseKDTree() - 类中的方法 weka.clusterers.XMeans
-
Gets whether the KDTree is used or not.
- getUseKernelEstimator() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Gets if kernel estimator is being used.
- getUseKononenko() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Gets whether Kononenko's MDL criterion is to be used.
- getUseLaplace() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Gets if laplace correction is being used.
- getUseLaplace() - 类中的方法 weka.classifiers.trees.J48
-
Get the value of useLaplace.
- getUseLaplace() - 类中的方法 weka.classifiers.trees.J48graft
-
Get the value of useLaplace.
- getUseLeastValues() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Gets whether to use values with least or most instances
- getUseLowerOrder() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Gets whether lower-order terms are used.
- getUseMEstimates() - 类中的方法 weka.classifiers.bayes.AODE
-
Gets if m-estimaces is being used.
- getUseMissing() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Gets the flag if missing values are treated as extra values.
- getUseMutation() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- getUseMutation() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- getUseNormalization() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns whether normalization is used.
- getUseOneSE() - 类中的方法 weka.classifiers.trees.BFTree
-
Get if use the 1SE rule to choose final model.
- getUseOneSE() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Get if use the 1SE rule to choose final model.
- getUseORForMustContainList() - 类中的方法 weka.associations.FPGrowth
-
Gets whether OR is to be used rather than AND when considering must contain lists.
- getUsePairwiseCoupling() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Gets whether to use pairwise coupling with 1-vs-1 classification to improve probability estimates.
- getUseProb() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
- getUsePropertyIterator() - 类中的方法 weka.experiment.Experiment
-
Gets whether the custom property iterator should be used.
- getUsePrune() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Get if use minimal cost-complexity pruning.
- getUsePruning() - 类中的方法 weka.classifiers.rules.JRip
-
Gets whether pruning is performed
- getUser() - 接口中的方法 weka.core.converters.DatabaseConverter
- getUser() - 类中的方法 weka.core.converters.DatabaseLoader
-
Gets the user name
- getUser() - 类中的方法 weka.core.converters.DatabaseSaver
-
Gets the database user.
- getUser() - 类中的方法 weka.gui.sql.ConnectionPanel
-
returns the current User.
- getUser() - 类中的方法 weka.gui.sql.event.ResultChangedEvent
-
returns the user that produced the table model
- getUser() - 类中的方法 weka.gui.sql.ResultSetTable
-
returns the user that produced the table model
- getUser() - 类中的方法 weka.gui.sql.SqlViewer
-
returns the user from the currently active tab in the ResultPanel, otherwise an empty string.
- getUser() - 类中的方法 weka.gui.sql.SqlViewerDialog
-
returns the chosen user, if any
- getUseRelativePath() - 类中的方法 weka.core.converters.AbstractFileLoader
-
Gets whether relative paths are to be used
- getUseRelativePath() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Gets whether relative paths are to be used
- getUseRelativePath() - 接口中的方法 weka.core.converters.FileSourcedConverter
-
Gets whether relative paths are to be used
- getUseRelativePath() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Get whether to use relative paths for the directory.
- getUseRelativePaths() - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
whether relative paths are used by default
- getUseResampling() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Get whether resampling is turned on
- getUseResampling() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Get whether resampling is turned on
- getUseResampling() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get whether resampling is turned on
- getUsername() - 类中的方法 weka.experiment.DatabaseUtils
-
Get the database username.
- getUsername() - 类中的方法 weka.gui.DatabaseConnectionDialog
-
Returns Username from dialog
- getUserOptions() - 类中的方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
returns the options the user supplied for the kernel
- getUserOptions() - 类中的方法 weka.core.CheckOptionHandler
-
Gets the current user-supplied options (creates a copy)
- getUseStars() - 类中的方法 weka.core.Javadoc
-
whether the Javadoc is prefixed with "*"
- getUseStoplist() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets whether if the words on the stoplist are to be ignored (The stoplist is in weka.core.StopWords).
- getUseSupervisedDiscretization() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Get whether supervised discretization is to be used.
- getUseTournamentSelection() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- getUseTournamentSelection() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- getUseTraining() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Get if training data is to be used instead of hold out/test data
- getUseTree() - 类中的方法 weka.classifiers.trees.m5.Rule
-
get whether an m5 tree is being used rather than rules
- getUseUnsmoothed() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Get whether or not smoothing is being used
- getV() - 类中的方法 weka.core.matrix.EigenvalueDecomposition
-
Return the eigenvector matrix
- getV() - 类中的方法 weka.core.matrix.SingularValueDecomposition
-
Return the right singular vectors
- getValidating() - 类中的方法 weka.core.xml.XMLDocument
-
returns whether a validating parser is used.
- getValidating() - 类中的方法 weka.core.xml.XMLOptions
-
returns whether a validating parser is used.
- getValidationChunkSize() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Get the validation chunk size
- getValidationSetSize() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getValidationThreshold() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- getValue() - 类中的方法 weka.classifiers.trees.adtree.PredictionNode
-
Gets the prediction value of the node.
- getValue() - 类中的方法 weka.core.pmml.FieldMetaInfo.Value
- getValue() - 类中的方法 weka.gui.CostMatrixEditor
-
Gets the cost matrix that is being edited.
- getValue() - 类中的方法 weka.gui.GenericArrayEditor
-
Gets the current object array.
- getValue() - 类中的方法 weka.gui.GenericObjectEditor
-
Gets the current Object.
- getValue() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Get the value of current node
- getValue() - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Gets the date format that is being edited.
- getValue() - 类中的方法 weka.gui.SortedTableModel.SortContainer
-
Returns the value to sort on.
- getValue(Object, String) - 类中的静态方法 weka.core.PropertyPath
-
returns the value specified by the given path from the object
- getValue(Object, PropertyPath.Path) - 类中的静态方法 weka.core.PropertyPath
-
returns the value specified by the given path from the object
- getValue(Instance, int) - 类中的静态方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Returns either a String object for nominal attributes or a Double for numeric ones.
- getValue(TechnicalInformation.Field) - 类中的方法 weka.core.TechnicalInformation
-
returns the value associated with the given field, or empty if field is not currently stored.
- getValueAt(int, int) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.ResultVectorTableModel
-
Returns the value for the JTable for a given position.
- getValueAt(int, int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns the value for the cell at columnindex and rowIndex
- getValueAt(int, int) - 类中的方法 weka.gui.SortedTableModel
-
Returns the value for the cell at columnIndex and rowIndex.
- getValueAt(int, int) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
returns the value for the cell at columnindex and rowIndex.
- getValueIndex() - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
Get the value index for this item.
- getValueIndices() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Get the indices of the indicator values.
- getValueName(int, int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
returns value of a node
- getValueRange() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Get the range containing the indicator values.
- getValues() - 类中的方法 weka.classifiers.meta.GridSearch
-
returns the parameter pair that was found to work best
- getValues() - 类中的方法 weka.core.pmml.TargetMetaInfo
-
Get the values (discrete case only) for this Target.
- getValues() - 类中的方法 weka.gui.visualize.VisualizePanelEvent
- getValues(int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
returns array of values of a node
- getValues(String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
returns array of values of a node
- getValuesList() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
returns the range for each attribute as string
- getValuesOutput() - 类中的方法 weka.associations.Tertius
-
Get the value of valuesOutput.
- getVarbValues() - 类中的方法 weka.core.Optimization
-
Get the variable values.
- getVariableNames() - 类中的方法 weka.core.Environment
-
Get the names of the variables (keys) stored in the internal map.
- getVariableValue(String) - 类中的方法 weka.core.Environment
-
Get the value for a particular variable.
- getVariance() - 类中的方法 weka.classifiers.BVDecompose
-
Get the calculated variance
- getVarianceCovered() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Gets the proportion of total variance to account for when retaining principal components
- getVarianceCovered() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Gets the proportion of total variance to account for when retaining principal components.
- getVectorOfAttrTypes() - 类中的方法 weka.estimators.CheckEstimator.AttrTypes
- getVerbose() - 类中的方法 weka.associations.Apriori
-
Gets whether algorithm is run in verbose mode
- getVerbose() - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
get whether or not output is verbose
- getVerbose() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Get whether output is to be verbose
- getVerbose() - 类中的方法 weka.attributeSelection.RandomSearch
-
get whether or not output is verbose
- getVerbose() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Get whether output is to be verbose
- getVerbose() - 类中的方法 weka.classifiers.meta.Dagging
-
Gets the verbose state
- getVersion() - 类中的方法 weka.core.xml.XMLSerialization
-
returns the WEKA version with which the serialized object was created
- getVisible() - 类中的方法 weka.gui.treevisualizer.Node
-
Get the value of visible.
- getVisibleColCount() - 类中的方法 weka.experiment.ResultMatrix
-
returns the number of visible columns
- getVisibleRowCount() - 类中的方法 weka.experiment.ResultMatrix
-
returns the number of visible rows
- getVisual() - 类中的方法 weka.gui.beans.AbstractDataSink
-
Get the visual being used by this data source.
- getVisual() - 类中的方法 weka.gui.beans.AbstractDataSource
-
Get the visual being used by this data source.
- getVisual() - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Get the visual
- getVisual() - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Get the visual for this bean
- getVisual() - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Get the visual for this bean
- getVisual() - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Get the visual for this bean
- getVisual() - 类中的方法 weka.gui.beans.Associator
-
Gets the visual appearance of this wrapper bean
- getVisual() - 类中的方法 weka.gui.beans.ClassAssigner
- getVisual() - 类中的方法 weka.gui.beans.Classifier
-
Gets the visual appearance of this wrapper bean
- getVisual() - 类中的方法 weka.gui.beans.ClassValuePicker
- getVisual() - 类中的方法 weka.gui.beans.Clusterer
-
Gets the visual appearance of this wrapper bean
- getVisual() - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- getVisual() - 类中的方法 weka.gui.beans.DataVisualizer
-
Return the visual appearance of this bean
- getVisual() - 类中的方法 weka.gui.beans.Filter
-
Get the visual appearance of this bean
- getVisual() - 类中的方法 weka.gui.beans.GraphViewer
-
Get the visual appearance of this bean
- getVisual() - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Gets the visual appearance of this wrapper bean
- getVisual() - 类中的方法 weka.gui.beans.MetaBean
-
Gets the visual appearance of this wrapper bean
- getVisual() - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Return the visual appearance of this bean
- getVisual() - 类中的方法 weka.gui.beans.PredictionAppender
-
Get the visual being used by this data source.
- getVisual() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Get the visual being used by this data source.
- getVisual() - 类中的方法 weka.gui.beans.StripChart
-
Get the visual appearance of this bean
- getVisual() - 类中的方法 weka.gui.beans.TextViewer
-
Get the visual appearance of this bean
- getVisual() - 接口中的方法 weka.gui.beans.Visible
-
Get the visual representation
- getVisualizeMenuItem(String, String) - 接口中的方法 weka.gui.visualize.plugins.GraphVisualizePlugin
-
Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the graph in XML BIF format.
- getVisualizeMenuItem(String, String) - 接口中的方法 weka.gui.visualize.plugins.TreeVisualizePlugin
-
Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the tree in GraphViz's dotty format.
- getVisualizeMenuItem(FastVector, Attribute) - 接口中的方法 weka.gui.visualize.plugins.VisualizePlugin
-
Get a JMenu or JMenuItem which contain action listeners that perform the visualization, using some but not necessarily all of the data.
- getVisualizeMenuItem(Instances) - 接口中的方法 weka.gui.visualize.plugins.ErrorVisualizePlugin
-
Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.
- getVoteFlag() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Gets the vote flag.
- getWBias() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the calculated bias according to the Webb definition
- getWeight() - 类中的方法 weka.classifiers.bayes.AODE
-
Gets the weight used in m-estimate
- getWeightByConfidence() - 类中的方法 weka.classifiers.misc.VFI
-
Get whether feature intervals are being weighted by confidence
- getWeightByDistance() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Get whether nearest neighbours are being weighted by distance
- getWeightingKernel() - 类中的方法 weka.classifiers.lazy.LWL
-
Gets the kernel weighting method to use.
- getWeightMethod() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns the current weighting method for instances.
- getWeightMethod() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Returns the current weighting method for instances.
- getWeights() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Gets the parameters C of class i to weight[i]*C (default 1).
- getWeights() - 类中的方法 weka.classifiers.functions.LibSVM
-
Gets the parameters C of class i to weight[i]*C, for C-SVC (default 1).
- getWeights() - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
call this function to get the weights array.
- getWeights() - 类中的方法 weka.estimators.KernelEstimator
-
Return the weights of the kernels.
- getWeights() - 接口中的方法 weka.gui.boundaryvisualizer.DataGenerator
-
Get weights
- getWeights() - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
- getWeightThreshold() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Get the degree of weight thresholding
- getWeightThreshold() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Get the degree of weight thresholding
- getWeightTrimBeta() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Get the value of weightTrimBeta.
- getWeightTrimBeta() - 类中的方法 weka.classifiers.trees.FT
-
Get the value of weightTrimBeta.
- getWeightTrimBeta() - 类中的方法 weka.classifiers.trees.LMT
-
Get the value of weightTrimBeta.
- getWeightTrimBeta() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Get the value of weightTrimBeta.
- getWholeDataErr() - 类中的方法 weka.classifiers.rules.Ridor
- getWidth() - 类中的方法 weka.gui.beans.BeanInstance
-
Gets the width of this bean
- getWindow(Class) - 类中的方法 weka.gui.Main
-
returns the first instance of the given window class, null if none can be found.
- getWindow(String) - 类中的方法 weka.gui.Main
-
returns the first window with the given title, null if none can be found.
- getWindowList() - 类中的方法 weka.gui.Main
-
returns all currently open frames.
- getWindowSize() - 类中的方法 weka.classifiers.lazy.IBk
-
Gets the maximum number of instances allowed in the training pool.
- getWithPrefix(String) - 类中的方法 weka.core.Trie
-
returns all stored strings that match the given prefix
- getWords() - 类中的方法 weka.core.CheckScheme
-
returns the words used for assembling strings in a comma-separated list.
- getWords() - 类中的方法 weka.core.TestInstances
-
returns the words used for assembling strings in a comma-separated list.
- getWordSeparators() - 类中的方法 weka.core.CheckScheme
-
returns the word separators (chars) to use for assembling strings.
- getWordSeparators() - 类中的方法 weka.core.TestInstances
-
returns the word separators (chars) to use for assembling strings.
- getWordsToKeep() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Gets the number of words (per class if there is a class attribute assigned) to attempt to keep.
- getWrappedAlgorithm() - 类中的方法 weka.gui.beans.Associator
-
Returns the wrapped associator
- getWrappedAlgorithm() - 类中的方法 weka.gui.beans.Classifier
-
Returns the wrapped classifier
- getWrappedAlgorithm() - 类中的方法 weka.gui.beans.Clusterer
-
Returns the wrapped clusterer
- getWrappedAlgorithm() - 类中的方法 weka.gui.beans.Filter
-
Get the filter wrapped by this bean
- getWrappedAlgorithm() - 类中的方法 weka.gui.beans.Loader
-
Get the loader
- getWrappedAlgorithm() - 类中的方法 weka.gui.beans.Saver
-
Get the saver
- getWrappedAlgorithm() - 接口中的方法 weka.gui.beans.WekaWrapper
-
Get the algorithm
- getWriteMode() - 类中的方法 weka.core.converters.AbstractSaver
-
Gets the write mode.
- getWriteMode() - 接口中的方法 weka.core.converters.Saver
-
Gets the write mode
- getWriteOPTICSresults() - 类中的方法 weka.clusterers.OPTICS
-
Returns the flag for writing actions
- getWriter() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Gets the writer
- getWriter(String) - 类中的方法 weka.gui.visualize.PrintableComponent
-
returns the JComponentWriter associated with the given name, is
null
if not found. - getWriter(String) - 接口中的方法 weka.gui.visualize.PrintableHandler
-
returns the JComponentWriter associated with the given name, is
null
if not found - getWriter(String) - 类中的方法 weka.gui.visualize.PrintablePanel
-
returns the JComponentWriter associated with the given name, is
null
if not found - getWriters() - 类中的方法 weka.gui.visualize.PrintableComponent
-
returns a Hashtable with the current available JComponentWriters in the save dialog.
- getWriters() - 接口中的方法 weka.gui.visualize.PrintableHandler
-
returns a Hashtable with the current available JComponentWriters in the save dialog.
- getWriters() - 类中的方法 weka.gui.visualize.PrintablePanel
-
returns a Hashtable with the current available JComponentWriters in the save dialog.
- getWVariance() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Get the calculated variance according to the Webb definition
- getX() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- getX() - 类中的方法 weka.gui.beans.BeanInstance
-
Gets the x coordinate of this bean
- getXBase() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the value of the base for X.
- getXExpression() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the expression for the X value.
- getXindex() - 类中的方法 weka.gui.visualize.PlotData2D
-
Get the currently set x index of the data
- getXIndex() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Get the index of the attribute on the x axis
- getXLabelFreq() - 类中的方法 weka.gui.beans.StripChart
-
Get the frequency by which x axis values are printed
- getXMax() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the value of the Maximum of X.
- getXMin() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the value of the minimum of X.
- getXMLDocument() - 类中的方法 weka.core.xml.XMLOptions
-
returns the handler of the XML document.
- getXProperty() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the X property to test (normally the filter).
- getXScale() - 类中的方法 weka.gui.visualize.JComponentWriter
-
returns the scale factor for the x-axis
- getXScale() - 类中的方法 weka.gui.visualize.PrintableComponent
-
returns the scale factor for the x-axis.
- getXScale() - 接口中的方法 weka.gui.visualize.PrintableHandler
-
returns the scale factor for the x-axis
- getXScale() - 类中的方法 weka.gui.visualize.PrintablePanel
-
returns the scale factor for the x-axis
- getXStep() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the value of the step size for X.
- getY() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- getY() - 类中的方法 weka.gui.beans.BeanInstance
-
Gets the y coordinate of this bean
- getYBase() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the value of the base for Y.
- getYExpression() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the expression for the Y value.
- getYindex() - 类中的方法 weka.gui.visualize.PlotData2D
-
Get the currently set y index of the data
- getYIndex() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Get the index of the attribute on the y axis
- getYMax() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the value of the Maximum of Y.
- getYMin() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the value of the minimum of Y.
- getYProperty() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the Y property (normally the classifier).
- getYScale() - 类中的方法 weka.gui.visualize.JComponentWriter
-
returns the scale factor for the y-axis
- getYScale() - 类中的方法 weka.gui.visualize.PrintableComponent
-
returns the scale factor for the y-axis.
- getYScale() - 接口中的方法 weka.gui.visualize.PrintableHandler
-
returns the scale factor for the y-axis
- getYScale() - 类中的方法 weka.gui.visualize.PrintablePanel
-
returns the scale factor for the y-axis
- getYStep() - 类中的方法 weka.classifiers.meta.GridSearch
-
Get the value of the step size for Y.
- globalBlendTipText() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns the tip text for this property
- globalInfo() - 类中的方法 weka.associations.Apriori
-
Returns a string describing this associator
- globalInfo() - 类中的方法 weka.associations.FilteredAssociator
-
Returns a string describing this Associator
- globalInfo() - 类中的方法 weka.associations.FPGrowth
-
Returns a string describing this associator
- globalInfo() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns global information about the algorithm.
- globalInfo() - 类中的方法 weka.associations.PredictiveApriori
-
Returns a string describing this associator
- globalInfo() - 类中的方法 weka.associations.Tertius
-
Returns a string describing this associator.
- globalInfo() - 类中的方法 weka.attributeSelection.BestFirst
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
- globalInfo() - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
- globalInfo() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
- globalInfo() - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns a string describing this attribute transformer
- globalInfo() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns a string describing this attribute transformer
- globalInfo() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.Ranker
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.RankSearch
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
- globalInfo() - 类中的方法 weka.classifiers.bayes.BayesNet
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.HNB
-
Returns a string describing this classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.NaiveBayesSimple
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.NaiveBayesUpdateable
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
This will return a string describing the class.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.estimate.SimpleEstimator
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.ci.CISearchAlgorithm
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
-
This will return a string describing the search algorithm.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.fixed.FromFile
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.fixed.NaiveBayes
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
This will return a string describing the search algorithm.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
This will return a string describing the search algorithm.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
This will return a string describing the search algorithm.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.global.TAN
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
This will return a string describing the search algorithm.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
This will return a string describing the search algorithm.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
This will return a string describing the search algorithm.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
This will return a string describing the search algorithm.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.net.search.local.TAN
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.bayes.WAODE
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.BVDecompose
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.IsotonicRegression
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.SMO
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns a string describing the kernel
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.NormalizedPolyKernel
-
Returns a string describing the kernel
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Returns a string describing the kernel
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Returns a string describing the kernel
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Returns a string describing the kernel
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Returns a string describing the kernel
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Returns a string describing the object
- globalInfo() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns a string describing the kernel
- globalInfo() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.lazy.IB1
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns a string describing classifier.
- globalInfo() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.lazy.LBR
- globalInfo() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns a string describing classifier.
- globalInfo() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.classifiers.meta.Bagging
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.ClassificationViaRegression
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
- globalInfo() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.Dagging
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.END
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.Grading
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
- globalInfo() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
- globalInfo() - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
- globalInfo() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
- globalInfo() - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
- globalInfo() - 类中的方法 weka.classifiers.meta.RandomCommittee
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.Stacking
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.StackingC
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.meta.ThresholdSelector
- globalInfo() - 类中的方法 weka.classifiers.meta.Vote
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.MDD
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.MIBoost
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.MIDD
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.MILR
-
Returns the tip text for this property
- globalInfo() - 类中的方法 weka.classifiers.mi.MINND
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.classifiers.misc.HyperPipes
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.misc.VFI
-
Returns a string describing this search method
- globalInfo() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.DTNB
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.JRip
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.M5Rules
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.NNge
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.OneR
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.PART
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.Prism
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.rules.ZeroR
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.DecisionStump
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.FT
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.Id3
-
Returns a string describing the classifier.
- globalInfo() - 类中的方法 weka.classifiers.trees.J48
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.LMT
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
returns information about the classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Return a description suitable for displaying in the explorer/experimenter.
- globalInfo() - 类中的方法 weka.classifiers.trees.UserClassifier
-
This will return a string describing the classifier.
- globalInfo() - 类中的方法 weka.clusterers.CLOPE
-
Returns a string describing this DataMining-Algorithm
- globalInfo() - 类中的方法 weka.clusterers.Cobweb
-
Returns a string describing this clusterer
- globalInfo() - 类中的方法 weka.clusterers.DBSCAN
-
Returns a string describing this DataMining-Algorithm
- globalInfo() - 类中的方法 weka.clusterers.EM
-
Returns a string describing this clusterer
- globalInfo() - 类中的方法 weka.clusterers.FarthestFirst
-
Returns a string describing this clusterer
- globalInfo() - 类中的方法 weka.clusterers.FilteredClusterer
-
Returns a string describing this clusterer.
- globalInfo() - 类中的方法 weka.clusterers.HierarchicalClusterer
-
This will return a string describing the clusterer.
- globalInfo() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns a string describing classifier
- globalInfo() - 类中的方法 weka.clusterers.OPTICS
-
Returns a string describing this DataMining-Algorithm
- globalInfo() - 类中的方法 weka.clusterers.sIB
-
Returns a string describing this clusterer
- globalInfo() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns a string describing this clusterer
- globalInfo() - 类中的方法 weka.clusterers.XMeans
-
Returns a string describing this clusterer.
- globalInfo() - 类中的方法 weka.core.ChebyshevDistance
-
Returns a string describing this object.
- globalInfo() - 类中的方法 weka.core.converters.ArffLoader
-
Returns a string describing this Loader
- globalInfo() - 类中的方法 weka.core.converters.ArffSaver
-
Returns a string describing this Saver
- globalInfo() - 类中的方法 weka.core.converters.C45Loader
-
Returns a string describing this attribute evaluator
- globalInfo() - 类中的方法 weka.core.converters.C45Saver
-
Returns a string describing this Saver
- globalInfo() - 类中的方法 weka.core.converters.CSVLoader
-
Returns a string describing this attribute evaluator.
- globalInfo() - 类中的方法 weka.core.converters.CSVSaver
-
Returns a string describing this Saver
- globalInfo() - 类中的方法 weka.core.converters.DatabaseLoader
-
Returns a string describing this Loader
- globalInfo() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns a string describing this Saver.
- globalInfo() - 类中的方法 weka.core.converters.LibSVMLoader
-
Returns a string describing this Loader.
- globalInfo() - 类中的方法 weka.core.converters.LibSVMSaver
-
Returns a string describing this Saver
- globalInfo() - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Returns a string describing this object
- globalInfo() - 类中的方法 weka.core.converters.SerializedInstancesSaver
-
Returns a string describing this Saver.
- globalInfo() - 类中的方法 weka.core.converters.SVMLightLoader
-
Returns a string describing this Loader.
- globalInfo() - 类中的方法 weka.core.converters.SVMLightSaver
-
Returns a string describing this Saver.
- globalInfo() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Returns a string describing this loader
- globalInfo() - 类中的方法 weka.core.converters.XRFFLoader
-
Returns a string describing this Loader
- globalInfo() - 类中的方法 weka.core.converters.XRFFSaver
-
Returns a string describing this Saver
- globalInfo() - 类中的方法 weka.core.EditDistance
-
Returns a string describing this object.
- globalInfo() - 类中的方法 weka.core.EuclideanDistance
-
Returns a string describing this object.
- globalInfo() - 类中的方法 weka.core.ManhattanDistance
-
Returns a string describing this object.
- globalInfo() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.balltrees.BottomUpConstructor
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren
-
Returns a string describing this object.
- globalInfo() - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.kdtrees.KMeansInpiredMethod
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.kdtrees.MedianOfWidestDimension
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - 类中的方法 weka.core.NormalizableDistance
-
Returns a string describing this object.
- globalInfo() - 类中的方法 weka.core.stemmers.IteratedLovinsStemmer
-
Returns a string describing the stemmer
- globalInfo() - 类中的方法 weka.core.stemmers.LovinsStemmer
-
Returns a string describing the stemmer
- globalInfo() - 类中的方法 weka.core.stemmers.NullStemmer
-
Returns a string describing the stemmer
- globalInfo() - 类中的方法 weka.core.stemmers.SnowballStemmer
-
Returns a string describing the stemmer.
- globalInfo() - 类中的方法 weka.core.tokenizers.AlphabeticTokenizer
-
Returns a string describing the stemmer
- globalInfo() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Returns a string describing the stemmer
- globalInfo() - 类中的方法 weka.core.tokenizers.Tokenizer
-
Returns a string describing the stemmer
- globalInfo() - 类中的方法 weka.core.tokenizers.WordTokenizer
-
Returns a string describing the stemmer
- globalInfo() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.ClusterDefinition
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns a string describing this data generator.
- globalInfo() - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns a string describing this result producer
- globalInfo() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Returns a string describing this split evaluator
- globalInfo() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Returns a string describing this split evaluator
- globalInfo() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns a string describing this result producer
- globalInfo() - 类中的方法 weka.experiment.CSVResultListener
-
Returns a string describing this result listener
- globalInfo() - 类中的方法 weka.experiment.DatabaseResultListener
-
Returns a string describing this result listener
- globalInfo() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Returns a string describing this result producer
- globalInfo() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Returns a string describing this split evaluator
- globalInfo() - 类中的方法 weka.experiment.InstancesResultListener
-
Returns a string describing this result listener
- globalInfo() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns a string describing this result producer
- globalInfo() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns a string describing this result producer
- globalInfo() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Returns a string describing this split evaluator
- globalInfo() - 类中的方法 weka.filters.AllFilter
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.MultiFilter
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.SimpleFilter
-
Returns a string describing this classifier.
- globalInfo() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns a string describing this classifier.
- globalInfo() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns a string describing this classifier.
- globalInfo() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Center
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
Returns a string describing this classifier.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.NumericToBinary
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Obfuscate
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.ReplaceMissingValues
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Standardize
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.TimeSeriesDelta
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.TimeSeriesTranslate
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Returns a string describing this classifier.
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.NonSparseToSparse
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Returns a string describing this classifier
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.SparseToNonSparse
-
Returns a string describing this filter
- globalInfo() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Returns a string describing this filter.
- globalInfo() - 类中的方法 weka.gui.beans.Associator
-
Global info (if it exists) for the wrapped classifier
- globalInfo() - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.ClassAssigner
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.Classifier
-
Global info (if it exists) for the wrapped classifier
- globalInfo() - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.ClassValuePicker
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.Clusterer
-
Global info (if it exists) for the wrapped classifier
- globalInfo() - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.DataVisualizer
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.Filter
-
Global info (if it exists) for the wrapped filter
- globalInfo() - 类中的方法 weka.gui.beans.GraphViewer
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.Loader
-
Global info (if it exists) for the wrapped loader
- globalInfo() - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.PredictionAppender
-
Global description of this bean
- globalInfo() - 类中的方法 weka.gui.beans.Saver
-
Global info (if it exists) for the wrapped loader
- globalInfo() - 类中的方法 weka.gui.beans.ScatterPlotMatrix
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Global info for this bean.
- globalInfo() - 类中的方法 weka.gui.beans.StripChart
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.TestSetMaker
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.TextViewer
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.TrainingSetMaker
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Global info for this bean
- globalInfo() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Returns a string describing this tool
- GLOBALINFO_ENDTAG - 类中的静态变量 weka.core.GlobalInfoJavadoc
-
the end comment tag for inserting the generated Javadoc
- GLOBALINFO_METHOD - 类中的静态变量 weka.core.GlobalInfoJavadoc
-
the globalInfo method name
- GLOBALINFO_STARTTAG - 类中的静态变量 weka.core.GlobalInfoJavadoc
-
the start comment tag for inserting the generated Javadoc
- GlobalInfoJavadoc - weka.core中的类
-
Generates Javadoc comments from the class's globalInfo method.
- GlobalInfoJavadoc() - 类的构造器 weka.core.GlobalInfoJavadoc
-
default constructor
- GlobalScoreSearchAlgorithm - weka.classifiers.bayes.net.search.global中的类
-
This Bayes Network learning algorithm uses cross validation to estimate classification accuracy.
- GlobalScoreSearchAlgorithm() - 类的构造器 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
- goDown(String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Go to a certain node of the tree down from the current node according to the specified relative path.
- GOEPanel() - 类的构造器 weka.gui.GenericObjectEditor.GOEPanel
-
Creates the GUI editor component.
- GOETreeNode() - 类的构造器 weka.gui.GenericObjectEditor.GOETreeNode
-
Creates a tree node that has no parent and no children, but which allows children.
- GOETreeNode(Object) - 类的构造器 weka.gui.GenericObjectEditor.GOETreeNode
-
Creates a tree node with no parent, no children, but which allows children, and initializes it with the specified user object.
- GOETreeNode(Object, boolean) - 类的构造器 weka.gui.GenericObjectEditor.GOETreeNode
-
Creates a tree node with no parent, no children, initialized with the specified user object, and that allows children only if specified.
- goTo(String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Go to a certain node of the tree according to the specified path Note that the path must be absolute path from the root.
- goToChild(int) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Go to one child node from the current position in the tree according to the given position
- goToChild(String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Go to one child node from the current position in the tree according to the given value
If the child node with the given value cannot be found it returns false, true otherwise. - goToParent() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Go to the parent from the current position in the tree If the current position is the root, it stays there and does not move
- goToRoot() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Go to the root of the tree
- gr(double, double) - 类中的静态方法 weka.core.Utils
-
Tests if a is greater than b.
- Grading - weka.classifiers.meta中的类
-
Implements Grading.
- Grading() - 类的构造器 weka.classifiers.meta.Grading
- GraftSplit - weka.classifiers.trees.j48中的类
-
Class implementing a split for nodes added to a tree during grafting.
- GraftSplit(int, double, int, double, double) - 类的构造器 weka.classifiers.trees.j48.GraftSplit
-
constructor
- GraftSplit(int, double, int, double, double[][]) - 类的构造器 weka.classifiers.trees.j48.GraftSplit
-
constructor
- graph() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns a BayesNet graph in XMLBIF ver 0.3 format.
- graph() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns graph describing the classifier (if possible).
- graph() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Returns graph describing the classifier (if possible).
- graph() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns graph describing the classifier (if possible).
- graph() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Returns graph describing the classifier (if possible).
- graph() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Returns graph describing the classifier (if possible).
- graph() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.FT
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.J48
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.j48.NBTreeClassifierTree
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.LMT
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.M5P
-
Return a dot style String describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns graph describing the tree.
- graph() - 类中的方法 weka.classifiers.trees.REPTree
-
Outputs the decision tree as a graph
- graph() - 类中的方法 weka.classifiers.trees.UserClassifier
- graph() - 类中的方法 weka.clusterers.Cobweb
-
Generates the graph string of the Cobweb tree
- graph() - 类中的方法 weka.clusterers.HierarchicalClusterer
- graph() - 接口中的方法 weka.core.Drawable
-
Returns a string that describes a graph representing the object.
- graph(StringBuffer) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Assign a unique identifier to each node in the tree and then calls graphTree
- graph(FPGrowth.FPTreeRoot) - 类中的方法 weka.associations.FPGrowth
-
Assemble a dot graph representation of the FP-tree.
- GraphConstants - weka.gui.graphvisualizer中的接口
-
GraphConstants.java
- GraphEdge - weka.gui.graphvisualizer中的类
-
This class represents an edge in the graph
- GraphEdge(int, int, int) - 类的构造器 weka.gui.graphvisualizer.GraphEdge
- GraphEdge(int, int, int, String, String) - 类的构造器 weka.gui.graphvisualizer.GraphEdge
- GraphEvent - weka.gui.beans中的类
-
Event for graphs
- GraphEvent(Object, String, String, int) - 类的构造器 weka.gui.beans.GraphEvent
-
Creates a new
GraphEvent
instance. - GraphListener - weka.gui.beans中的接口
-
Describe interface
TextListener
here. - GraphNode - weka.gui.graphvisualizer中的类
-
This class represents a node in the Graph.
- GraphNode(String, String) - 类的构造器 weka.gui.graphvisualizer.GraphNode
-
Constructor
- GraphNode(String, String, int) - 类的构造器 weka.gui.graphvisualizer.GraphNode
-
Constructor
- GraphPanel - weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI中的类
-
GraphPanel.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht
Date: Sep 16, 2004
Time: 10:28:19 AM
$ Revision 1.4 $ - GraphPanel(FastVector, int, boolean, boolean) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
- graphType() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.FT
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.J48
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.M5P
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.classifiers.trees.UserClassifier
-
Returns the type of graph this classifier represents.
- graphType() - 类中的方法 weka.clusterers.Cobweb
-
Returns the type of graphs this class represents
- graphType() - 类中的方法 weka.clusterers.HierarchicalClusterer
- graphType() - 接口中的方法 weka.core.Drawable
-
Returns the type of graph representing the object.
- GraphViewer - weka.gui.beans中的类
-
A bean encapsulating weka.gui.treevisualize.TreeVisualizer
- GraphViewer() - 类的构造器 weka.gui.beans.GraphViewer
- GraphViewerBeanInfo - weka.gui.beans中的类
-
Bean info class for the graph viewer
- GraphViewerBeanInfo() - 类的构造器 weka.gui.beans.GraphViewerBeanInfo
- GraphVisualizePlugin - weka.gui.visualize.plugins中的接口
-
Interface implemented by classes loaded dynamically to visualize graphs in the explorer.
- GraphVisualizer - weka.gui.graphvisualizer中的类
-
This class displays the graph we want to visualize.
- GraphVisualizer() - 类的构造器 weka.gui.graphvisualizer.GraphVisualizer
-
Constructor
Sets up the gui and initializes all the other previously uninitialized variables. - GreedyStepwise - weka.attributeSelection中的类
-
GreedyStepwise :
Performs a greedy forward or backward search through the space of attribute subsets. - GreedyStepwise() - 类的构造器 weka.attributeSelection.GreedyStepwise
-
Constructor
- GRID - 类中的静态变量 weka.datagenerators.clusterers.BIRCHCluster
-
Constant set for choice of pattern.
- gridIsExtendableTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- GridSearch - weka.classifiers.meta中的类
-
Performs a grid search of parameter pairs for the a classifier (Y-axis, default is LinearRegression with the "Ridge" parameter) and the PLSFilter (X-axis, "# of Components") and chooses the best pair found for the actual predicting.
The initial grid is worked on with 2-fold CV to determine the values of the parameter pairs for the selected type of evaluation (e.g., accuracy). - GridSearch() - 类的构造器 weka.classifiers.meta.GridSearch
-
the default constructor
- grOrEq(double, double) - 类中的静态方法 weka.core.Utils
-
Tests if a is greater or equal to b.
- grouping(boolean) - 类中的方法 weka.core.matrix.FlexibleDecimalFormat
- grow(Instances) - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Build one rule using the growing data
- grow(Instances) - 类中的方法 weka.classifiers.rules.Rule
-
Build this rule
- GT - 接口中的静态变量 weka.core.mathematicalexpression.sym
- GT - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- GUI - weka.classifiers.bayes.net中的类
-
GUI interface to Bayesian Networks.
- GUI() - 类的构造器 weka.classifiers.bayes.net.GUI
-
Constructor
Sets up the gui and initializes all the other previously uninitialized variables. - GUI_MDI - 类中的静态变量 weka.gui.Main
-
displays the GUI as MDI.
- GUI_SDI - 类中的静态变量 weka.gui.Main
-
displays the GUI as SDI.
- GUIChooser - weka.gui中的类
-
The main class for the Weka GUIChooser.
- GUIChooser() - 类的构造器 weka.gui.GUIChooser
-
Creates the experiment environment gui with no initial experiment
- GUIChooser.ChildFrameSDI - weka.gui中的类
-
Specialized JFrame class.
- GUIEDITORS_PROPERTY_FILE - 类中的静态变量 weka.gui.GenericObjectEditor
-
the properties files containing the class/editor mappings.
- GUITipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
H
- h(double) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Computes the value of h(x) given the mixture.
- h(double) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Computes the value of h(x) given the mixture.
- h(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Computes the value of h(x) given the mixture, where x is a vector.
- h(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Computes the value of h(x) given the mixture, where x is a vector.
- h1(int, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Constructs single Householder transformation for a column
- h2(int, int, double, PaceMatrix, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Performs single Householder transformation on one column of a matrix
- handles(Capabilities.Capability) - 类中的方法 weka.core.Capabilities
-
returns true if the classifier handler has the specified capability
- handles(Capabilities.Capability) - 类中的方法 weka.core.FindWithCapabilities
-
returns true if the given capability can be handled.
- hasAdditional() - 类中的方法 weka.core.TechnicalInformation
-
returns true if there are further technical informations stored in this
- hasAntds() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Whether this rule has antecedents, i.e.
- hasAntds() - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Whether this rule has antecedents, i.e.
- hasAntds() - 类中的方法 weka.classifiers.rules.Rule
-
Whether this rule has antecedents, i.e.
- hasClasspathProblems() - 类中的方法 weka.core.CheckScheme
-
returns TRUE if the classifier returned a "not in classpath" Exception
- hasClasspathProblems() - 类中的方法 weka.estimators.CheckEstimator
-
returns TRUE if the estimator returned a "not in classpath" Exception
- hasDependencies() - 类中的方法 weka.core.Capabilities
-
Checks whether there are any dependencies at all
- hasDependency(Capabilities.Capability) - 类中的方法 weka.core.Capabilities
-
returns true if the classifier handler has a dependency for the specified capability
- hasFalseHead() - 类中的方法 weka.associations.tertius.Rule
-
Test if the head of the rule is false.
- hash - 类中的变量 weka.classifiers.lazy.kstar.KStarCache.TableEntry
-
attribute value hash code
- hashCode() - 类中的方法 weka.associations.FPGrowth.BinaryItem
- hashCode() - 类中的方法 weka.associations.ItemSet
-
Produces a hash code for a item set.
- hashCode() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval.hashKey
-
Calculates a hash code
- hashCode() - 类中的方法 weka.classifiers.rules.DecisionTableHashKey
-
Calculates a hash code
- hashCode() - 类中的方法 weka.core.SerializedObject
-
Returns a hashcode for this object.
- hashCode() - 类中的方法 weka.core.Trie
-
Returns the hash code value for this collection.
- hashKey(double[]) - 类的构造器 weka.attributeSelection.ConsistencySubsetEval.hashKey
-
Constructor for a hashKey
- hashKey(Instance, int) - 类的构造器 weka.attributeSelection.ConsistencySubsetEval.hashKey
-
Constructor for a hashKey
- hasIncomingBatchInstances() - 类中的方法 weka.gui.beans.Classifier
-
Returns true if this classifier has an incoming connection that is a batch set of instances
- hasIncomingBatchInstances() - 类中的方法 weka.gui.beans.Clusterer
-
Returns true if this clusterer has an incoming connection that is a batch set of instances
- hasIncomingStreamInstances() - 类中的方法 weka.gui.beans.Classifier
-
Returns true if this classifier has an incoming connection that is an instance stream
- hasIndex() - 类中的方法 weka.core.PropertyPath.PathElement
-
returns whether the property is an index-based one
- hasInterface(Class, Class) - 类中的静态方法 weka.core.ClassDiscovery
-
Checks whether the given class implements the given interface.
- hasInterface(String, String) - 类中的静态方法 weka.core.ClassDiscovery
-
Checks whether the given class implements the given interface.
- hasMaxCounterInstances() - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if all the intances are counter-instances.
- hasMaxRows() - 类中的方法 weka.gui.sql.ResultSetHelper
-
whether a limit on the rows to retrieve was set.
- hasMissingValue() - 类中的方法 weka.core.Instance
-
Tests whether an instance has a missing value.
- hasModels() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns true if the logistic regression model at this node has changed compared to the one at the parent node.
- hasModels() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns true if the logistic regression model at this node has changed compared to the one at the parent node.
- hasMoreElements() - 类中的方法 weka.core.FastVector.FastVectorEnumeration
-
Tests if there are any more elements to enumerate.
- hasMoreElements() - 类中的方法 weka.core.tokenizers.AlphabeticTokenizer
-
returns whether there are more elements still
- hasMoreElements() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
returns true if there's more elements available
- hasMoreElements() - 类中的方法 weka.core.tokenizers.Tokenizer
-
Tests if this enumeration contains more elements.
- hasMoreElements() - 类中的方法 weka.core.tokenizers.WordTokenizer
-
Tests if this enumeration contains more elements.
- hasMoreElements(Instances) - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
returns whether there are more Instance objects in the data.
- hasMoreIterations() - 类中的方法 weka.experiment.Experiment
-
Returns true if there are more iterations to carry out in the experiment.
- hasNext() - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListIterator
- hasNext() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue
-
Tests, if the queue has some more elements left
- hasNext() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue
-
Tests, if the queue has some more elements left
- hasNext() - 类中的方法 weka.core.Trie.TrieIterator
-
Returns true if the iteration has more elements.
- hasPrevious() - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
- hasResult() - 类中的方法 weka.gui.sql.event.QueryExecuteEvent
-
whether a ResultSet was produced, e.g.
- hasTargetMetaData() - 类中的方法 weka.core.pmml.MiningSchema
-
Returns true if there is Target meta data.
- hasTrueBody() - 类中的方法 weka.associations.tertius.Rule
-
Test if the body of the rule is true.
- hasUID(Class) - 类中的静态方法 weka.core.SerializationHelper
-
checks whether the given class contains a serialVersionUID.
- hasUID(String) - 类中的静态方法 weka.core.SerializationHelper
-
checks whether the given class contains a serialVersionUID.
- hasZeropoint() - 类中的方法 weka.core.Attribute
-
Returns whether the attribute has a zeropoint and may be added meaningfully.
- HDRankTipText() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns the tip text for this property
- Head - weka.associations.tertius中的类
-
Class representing the head of a rule.
- Head() - 类的构造器 weka.associations.tertius.Head
-
Constructor without storing the counter-instances.
- Head(Instances) - 类的构造器 weka.associations.tertius.Head
-
Constructor storing the counter-instances.
- headContains(Literal) - 类中的方法 weka.associations.tertius.Rule
-
Test if the head of the rule contains a literal.
- header(int) - 类中的方法 weka.experiment.PairedTTester
-
Creates a "header" string describing the current resultsets.
- header(int) - 接口中的方法 weka.experiment.Tester
-
Creates a "header" string describing the current resultsets.
- headerKeys() - 类中的方法 weka.experiment.ResultMatrix
-
returns an enumeration of the header keys
- HEIGHT - 类中的静态变量 weka.gui.arffviewer.ArffViewerMainPanel
-
default height
- HEIGHT - 类中的静态变量 weka.gui.sql.SqlViewer
-
the height property in the history file.
- heuristicStopTipText() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the tip text for this property
- heuristicTipText() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the tip text for this property
- heuristicTipText() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns the tip text for this property
- hf(double) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Computes the value of h(x) / f(x) given the mixture.
- hf(double) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Computes the value of h(x) / f(x) given the mixture.
- hiddenLayersTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- HierarchicalBCEngine - weka.gui.graphvisualizer中的类
-
This class lays out the vertices of a graph in a hierarchy of vertical levels, with a number of nodes in each level.
- HierarchicalBCEngine() - 类的构造器 weka.gui.graphvisualizer.HierarchicalBCEngine
-
SimpleConstructor If we want to instantiate the class first, and if information for nodes and edges is not available.
- HierarchicalBCEngine(FastVector, FastVector, int, int) - 类的构造器 weka.gui.graphvisualizer.HierarchicalBCEngine
-
Constructor - takes in FastVectors of nodes and edges, and the initial width and height of a node
- HierarchicalBCEngine(FastVector, FastVector, int, int, boolean) - 类的构造器 weka.gui.graphvisualizer.HierarchicalBCEngine
-
Constructor - takes in FastVectors of nodes and edges, the initial width and height of a node, and a boolean value to indicate if the edges should be concentrated.
- HierarchicalClusterer - weka.clusterers中的类
-
Hierarchical clustering class.
- HierarchicalClusterer() - 类的构造器 weka.clusterers.HierarchicalClusterer
- HierarchyPropertyParser - weka.gui中的类
-
This class implements a parser to read properties that have a hierarchy(i.e.
- HierarchyPropertyParser() - 类的构造器 weka.gui.HierarchyPropertyParser
-
Default constructor
- HierarchyPropertyParser(String, String) - 类的构造器 weka.gui.HierarchyPropertyParser
-
Constructor that builds a tree from the given property with the given delimitor
- HierarchyVisualizer - weka.gui.hierarchyvisualizer中的类
- HierarchyVisualizer(String) - 类的构造器 weka.gui.hierarchyvisualizer.HierarchyVisualizer
- HillClimber - weka.classifiers.bayes.net.search.global中的类
-
This Bayes Network learning algorithm uses a hill climbing algorithm adding, deleting and reversing arcs.
- HillClimber - weka.classifiers.bayes.net.search.local中的类
-
This Bayes Network learning algorithm uses a hill climbing algorithm adding, deleting and reversing arcs.
- HillClimber() - 类的构造器 weka.classifiers.bayes.net.search.global.HillClimber
- HillClimber() - 类的构造器 weka.classifiers.bayes.net.search.local.HillClimber
- HISTORY_NAME - 类中的静态变量 weka.gui.sql.ConnectionPanel
-
the name of the history.
- HISTORY_NAME - 类中的静态变量 weka.gui.sql.QueryPanel
-
the name of the history.
- historyChanged(HistoryChangedEvent) - 接口中的方法 weka.gui.sql.event.HistoryChangedListener
-
This method gets called when a history is modified.
- historyChanged(HistoryChangedEvent) - 类中的方法 weka.gui.sql.SqlViewer
-
This method gets called when a history is modified.
- HistoryChangedEvent - weka.gui.sql.event中的类
-
An event that is generated when a history is modified.
- HistoryChangedEvent(Object, String, DefaultListModel) - 类的构造器 weka.gui.sql.event.HistoryChangedEvent
-
constructs the event
- HistoryChangedListener - weka.gui.sql.event中的接口
-
A listener for changes in a history.
- hit(Rectangle, Shape, boolean) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- HLINE - 类中的静态变量 weka.gui.visualize.VisualizePanelEvent
- HNB - weka.classifiers.bayes中的类
-
Contructs Hidden Naive Bayes classification model with high classification accuracy and AUC.
For more information refer to:
H. - HNB() - 类的构造器 weka.classifiers.bayes.HNB
- holdOutFileTipText() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Returns the tip text for this property
- HoldOutSubsetEvaluator - weka.attributeSelection中的类
-
Abstract attribute subset evaluator capable of evaluating subsets with respect to a data set that is distinct from that used to initialize/ train the subset evaluator.
- HoldOutSubsetEvaluator() - 类的构造器 weka.attributeSelection.HoldOutSubsetEvaluator
- hornClausesTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- HostListPanel - weka.gui.experiment中的类
-
This panel controls setting a list of hosts for a RemoteExperiment to use.
- HostListPanel() - 类的构造器 weka.gui.experiment.HostListPanel
-
Create the host list panel initially disabled.
- HostListPanel(RemoteExperiment) - 类的构造器 weka.gui.experiment.HostListPanel
-
Creates the host list panel with the given experiment.
- HOWPUBLISHED - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
How something strange has been published.
- HTTP - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
A link to a postscript file.
- HyperparameterRange - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
CV Hyperparameter Range
- hyperparameterRangeTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- Hyperparameters - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Array to store Hyperparameter values for each feature.
- HyperparameterSelection - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Hyperparameter selection method
- hyperparameterSelectionTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- HyperparameterValue - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Best hyperparameter for test phase
- hyperparameterValueTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- HyperPipes - weka.classifiers.misc中的类
-
Class implementing a HyperPipe classifier.
- HyperPipes() - 类的构造器 weka.classifiers.misc.HyperPipes
- hypot(double, double) - 类中的静态方法 weka.core.matrix.Maths
-
sqrt(a^2 + b^2) without under/overflow.
I
- I0 - 类中的静态变量 weka.classifiers.functions.supportVector.RegSMOImproved
- I0a - 类中的静态变量 weka.classifiers.functions.supportVector.RegSMOImproved
- I0b - 类中的静态变量 weka.classifiers.functions.supportVector.RegSMOImproved
- I1 - 类中的静态变量 weka.classifiers.functions.supportVector.RegSMOImproved
- I2 - 类中的静态变量 weka.classifiers.functions.supportVector.RegSMOImproved
- I3 - 类中的静态变量 weka.classifiers.functions.supportVector.RegSMOImproved
- IB1 - weka.classifiers.lazy中的类
-
Nearest-neighbour classifier.
- IB1() - 类的构造器 weka.classifiers.lazy.IB1
- IBk - weka.classifiers.lazy中的类
-
K-nearest neighbours classifier.
- IBk() - 类的构造器 weka.classifiers.lazy.IBk
-
IB1 classifer.
- IBk(int) - 类的构造器 weka.classifiers.lazy.IBk
-
IBk classifier.
- ICON_PATH - 类中的静态变量 weka.gui.beans.BeanVisual
- ICSSearchAlgorithm - weka.classifiers.bayes.net.search.ci中的类
-
This Bayes Network learning algorithm uses conditional independence tests to find a skeleton, finds V-nodes and applies a set of rules to find the directions of the remaining arrows.
- ICSSearchAlgorithm() - 类的构造器 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
- Id3 - weka.classifiers.trees中的类
-
Class for constructing an unpruned decision tree based on the ID3 algorithm.
- Id3() - 类的构造器 weka.classifiers.trees.Id3
- identity(int, int) - 类中的静态方法 weka.core.matrix.Matrix
-
Generate identity matrix
- IDFTransformTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- IDIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Returns the tip text for this property
- IDLE - 类中的静态变量 weka.gui.beans.BeanInstance
- IFELSE - 接口中的静态变量 weka.core.mathematicalexpression.sym
- ignoreClassTipText() - 类中的方法 weka.filters.unsupervised.attribute.PotentialClassIgnorer
-
Returns the tip text for this property
- ignored() - 类中的方法 weka.core.xml.PropertyHandler
-
returns an enumeration of the stored display names and classes of properties to ignore.
NOTE: String and Class Objects are mixed in this enumeration, depending whether it is a global property to ignore or just one for a certain class! - ignoredAttributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Returns the tip text for this property
- ignoredAttributeIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Returns the tip text for this property
- ignoreRangeTipText() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Returns the tip text for this property
- IMAGES - 类中的静态变量 weka.gui.ComponentHelper
-
the default directories for images
- IMPLICIT - 类中的静态变量 weka.associations.Tertius
-
Way of handling missing values: max counterinstances
- ImproveSolutions() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Improve the solutions previously combined by adding the attributes that improve that solution
- Impurity - weka.classifiers.trees.m5中的类
-
Class for handling the impurity values when spliting the instances
- Impurity(int, int, Instances, int) - 类的构造器 weka.classifiers.trees.m5.Impurity
-
Constructs an Impurity object containing the impurity values of partitioning the instances using an attribute
- INBOOK - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
A part of a book, which may be a chapter (or section or whatever) and/or a range of pages.
- includeClassTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- INCOLLECTION - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
A part of a book having its own title.
- incompleteBeta(double, double, double) - 类中的静态方法 weka.core.Statistics
-
Returns the Incomplete Beta Function evaluated from zero to xx.
- incompleteBetaFraction1(double, double, double) - 类中的静态方法 weka.core.Statistics
-
Continued fraction expansion #1 for incomplete beta integral.
- incompleteBetaFraction2(double, double, double) - 类中的静态方法 weka.core.Statistics
-
Continued fraction expansion #2 for incomplete beta integral.
- incompleteGamma(double, double) - 类中的静态方法 weka.core.Statistics
-
Returns the Incomplete Gamma function.
- incompleteGammaComplement(double, double) - 类中的静态方法 weka.core.Statistics
-
Returns the Complemented Incomplete Gamma function.
- incorrect() - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Gets the number of incorrect classifications (that is, for which an incorrect prediction was made).
- incorrect() - 类中的方法 weka.classifiers.Evaluation
-
Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).
- incrCoordCount() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Increments the coordinate count (number of coordinates/attributes looked at).
- increaseFrequency() - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
Increment the frequency of this item.
- increaseFrequency(int) - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
Increase the frequency of this item.
- incremental(double, int) - 类中的方法 weka.classifiers.trees.m5.Impurity
-
Incrementally computes the impurirty values
- INCREMENTAL - 接口中的静态变量 weka.core.converters.Loader
- INCREMENTAL - 接口中的静态变量 weka.core.converters.Saver
- IncrementalClassifierEvaluator - weka.gui.beans中的类
-
Bean that evaluates incremental classifiers
- IncrementalClassifierEvaluator() - 类的构造器 weka.gui.beans.IncrementalClassifierEvaluator
- IncrementalClassifierEvaluatorBeanInfo - weka.gui.beans中的类
-
Bean info class for the incremental classifier evaluator bean
- IncrementalClassifierEvaluatorBeanInfo() - 类的构造器 weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo
- IncrementalClassifierEvaluatorCustomizer - weka.gui.beans中的类
-
GUI Customizer for the incremental classifier evaluator bean
- IncrementalClassifierEvaluatorCustomizer() - 类的构造器 weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
- IncrementalClassifierEvent - weka.gui.beans中的类
-
Class encapsulating an incrementally built classifier and current instance
- IncrementalClassifierEvent(Object) - 类的构造器 weka.gui.beans.IncrementalClassifierEvent
- IncrementalClassifierEvent(Object, Classifier, Instance, int) - 类的构造器 weka.gui.beans.IncrementalClassifierEvent
-
Creates a new
IncrementalClassifierEvent
instance. - IncrementalClassifierEvent(Object, Classifier, Instances) - 类的构造器 weka.gui.beans.IncrementalClassifierEvent
-
Creates a new incremental classifier event that encapsulates header information and classifier.
- IncrementalClassifierListener - weka.gui.beans中的接口
-
Interface to something that can process a IncrementalClassifierEvent
- IncrementalConverter - weka.core.converters中的接口
-
Marker interface for a loader/saver that can retrieve instances incrementally
- IncrementalEstimator - weka.estimators中的接口
-
Interface for an incremental probability estimators.
- incrIntNodeCount() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Increments the internal node count.
- incrLeafCount() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Increments the leaf count.
- incrPointCount() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Increments the point count (number of datapoints looked at).
- index() - 类中的方法 weka.core.Attribute
-
Returns the index of this attribute.
- index(int) - 类中的方法 weka.core.Instance
-
Returns the index of the attribute stored at the given position.
- index(int) - 类中的方法 weka.core.SparseInstance
-
Returns the index of the attribute stored at the given position.
- INDEX_BEANCONNECTIONS - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the index in the Vector, where the BeanConnections are stored (Instances and Connections are stored in a Vector and then serialized)
- INDEX_BEANINSTANCES - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the index in the Vector, where the BeanInstances are stored (Instances and Connections are stored in a Vector and then serialized)
- Indexes(int, int, boolean, int) - 类的构造器 weka.classifiers.lazy.LBR.Indexes
-
constructor
- Indexes(LBR.Indexes) - 类的构造器 weka.classifiers.lazy.LBR.Indexes
-
constructor
- indexOf(Object) - 类中的方法 weka.core.FastVector
-
Searches for the first occurence of the given argument, testing for equality using the equals method.
- indexOf(Object) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Searches for the first occurrence of elem.
- indexOf(Object, int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Searches for the first occurrence of elem, beginning the search at index.
- indexOf(Literal) - 类中的方法 weka.associations.tertius.Predicate
- indexOfMax() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the index of the maximum.
- indexOfValue(String) - 类中的方法 weka.core.Attribute
-
Returns the index of a given attribute value.
- indexToString(int) - 类中的静态方法 weka.core.SingleIndex
-
Creates a string representation of the given index.
- indicesToRangeList(int[]) - 类中的静态方法 weka.core.Range
-
Creates a string representation of the indices in the supplied array.
- INDIVIDUAL_PROPERTY - 类中的静态变量 weka.associations.tertius.IndividualLiteral
- IndividualInstance - weka.associations.tertius中的类
- IndividualInstance(IndividualInstance) - 类的构造器 weka.associations.tertius.IndividualInstance
- IndividualInstance(Instance, Instances) - 类的构造器 weka.associations.tertius.IndividualInstance
- IndividualInstances - weka.associations.tertius中的类
- IndividualInstances(Instances, Instances) - 类的构造器 weka.associations.tertius.IndividualInstances
- IndividualLiteral - weka.associations.tertius中的类
- IndividualLiteral(Predicate, String, int, int, int, int) - 类的构造器 weka.associations.tertius.IndividualLiteral
- individualPredictions(Instance) - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Returns the individual predictions of the base classifiers for an instance.
- info(int[]) - 类中的静态方法 weka.core.Utils
-
Computes entropy for an array of integers.
- INFO - enum class 中的枚举常量 weka.core.logging.Logger.Level
-
FINE level.
- INFO - 类中的静态变量 weka.core.Debug
-
the log level Info
- infoGain() - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Returns (C4.5-type) information gain for the generated split.
- infoGain() - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns (C4.5-type) information gain for the generated split.
- InfoGainAttributeEval - weka.attributeSelection中的类
-
InfoGainAttributeEval :
Evaluates the worth of an attribute by measuring the information gain with respect to the class.
InfoGain(Class,Attribute) = H(Class) - H(Class | Attribute). - InfoGainAttributeEval() - 类的构造器 weka.attributeSelection.InfoGainAttributeEval
-
Constructor
- InfoGainSplitCrit - weka.classifiers.trees.j48中的类
-
Class for computing the information gain for a given distribution.
- InfoGainSplitCrit() - 类的构造器 weka.classifiers.trees.j48.InfoGainSplitCrit
- InfoPanel - weka.gui.sql中的类
-
A simple panel for displaying information, e.g.
- InfoPanel(JFrame) - 类的构造器 weka.gui.sql.InfoPanel
-
creates the panel
- InfoPanelCellRenderer - weka.gui.sql中的类
-
A specialized renderer that takes care of JLabels in a JList.
- InfoPanelCellRenderer() - 类的构造器 weka.gui.sql.InfoPanelCellRenderer
-
the constructor
- Init(int, int) - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
Init defines a minimal Bayes net with no arcs
- initAsNaiveBayesTipText() - 类中的方法 weka.classifiers.bayes.net.search.SearchAlgorithm
- initClassifier(Instances) - 类中的方法 weka.classifiers.bayes.DMNBtext.DNBBinary
- initClassifier(Instances) - 接口中的方法 weka.classifiers.IterativeClassifier
-
Inits an iterative classifier.
- initClassifier(Instances) - 类中的方法 weka.classifiers.trees.ADTree
-
Sets up the tree ready to be trained, using two-class optimized method.
- initClassifier(Instances) - 类中的方法 weka.classifiers.trees.LADTree
-
Sets up the tree ready to be trained.
- initCPTs() - 类中的方法 weka.classifiers.bayes.BayesNet
-
initializes the conditional probabilities
- initCPTs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
initCPTs reserves space for CPTs and set all counts to zero
- initCPTs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
initCPTs reserves space for CPTs and set all counts to zero
- initCPTs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
initCPTs reserves space for CPTs and set all counts to zero
- initCPTs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.estimate.SimpleEstimator
-
initCPTs reserves space for CPTs and set all counts to zero
- initDebugVectorsInput() - 类中的方法 weka.clusterers.XMeans
-
Initialises the debug vector input.
- initFileClassIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns the tip text for this property
- initFileTipText() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns the tip text for this property
- initFilter(Instances) - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
initializes the filter with the given dataset, i.e., the kernel gets built.
- INITIAL_STEP - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- initialAnchorRandomTipText() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Returns the tip text for this property.
- initialize() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
(1)Initialize m_Beta[j] to 0.
- initialize() - 类中的方法 weka.classifiers.CostMatrix
-
Initializes the matrix
- initialize() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Sets all counts to zero.
- initialize() - 类中的方法 weka.experiment.Experiment
-
Prepares an experiment for running, initializing current iterator settings.
- initialize() - 类中的方法 weka.experiment.RemoteExperiment
-
Prepares a remote experiment for running, creates sub experiments
- initialize() - 类中的方法 weka.gui.visualize.BMPWriter
-
further initialization
- initialize() - 类中的方法 weka.gui.visualize.JPEGWriter
-
further initialization.
- initialize() - 类中的方法 weka.gui.visualize.PNGWriter
-
further initialization
- initialize(int, int, int) - 类中的方法 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Resets the object of split information
- initialize(int, int, int) - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Resets the object of split information
- initializeDown(boolean) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
- initializeRanges() - 类中的方法 weka.core.NormalizableDistance
-
Initializes the ranges using all instances of the dataset.
- initializeRanges(int) - 类中的方法 weka.core.Debug.DBO
-
Initialize ranges, upper limit must be set
- initializeRanges(int[]) - 类中的方法 weka.core.NormalizableDistance
-
Initializes the ranges of a subset of the instances of this dataset.
- initializeRanges(int[], int, int) - 类中的方法 weka.core.NormalizableDistance
-
Initializes the ranges of a subset of the instances of this dataset.
- initializeRangesEmpty(int, double[][]) - 类中的方法 weka.core.NormalizableDistance
-
Used to initialize the ranges.
- initializeUp() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
- initInternalFields() - 类中的方法 weka.gui.visualize.MatrixPanel
-
Initializes internal data fields, i.e.
- InitPopulation(int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Creating space for introducing the population
- initStructure() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Init structure initializes the structure to an empty graph or a Naive Bayes graph (depending on the -N flag).
- innerProduct(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the inner product of two DoubleVectors
- INPROCEEDINGS - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
An article in a conference proceedings.
- input(Instance) - 类中的方法 weka.filters.AllFilter
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.Filter
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.SimpleBatchFilter
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.SimpleStreamFilter
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.supervised.instance.Resample
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Center
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.NumericToBinary
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Obfuscate
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.ReplaceMissingValues
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.Standardize
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.NonSparseToSparse
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.SparseToNonSparse
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Input an instance for filtering.
- input(Instance) - 类中的方法 weka.gui.streams.InstanceCounter
- input(Instance) - 类中的方法 weka.gui.streams.InstanceJoiner
- input(Instance) - 类中的方法 weka.gui.streams.InstanceSavePanel
- input(Instance) - 类中的方法 weka.gui.streams.InstanceTable
- input(Instance) - 类中的方法 weka.gui.streams.InstanceViewer
- INPUT - 类中的静态变量 weka.classifiers.functions.neural.NeuralConnection
-
This unit is an input unit.
- inputCenterFileTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- inputFormat(Instances) - 类中的方法 weka.gui.streams.InstanceCounter
- inputFormat(Instances) - 类中的方法 weka.gui.streams.InstanceJoiner
-
Sets the format of the input instances.
- inputFormat(Instances) - 类中的方法 weka.gui.streams.InstanceSavePanel
- inputFormat(Instances) - 类中的方法 weka.gui.streams.InstanceTable
- inputFormat(Instances) - 类中的方法 weka.gui.streams.InstanceViewer
- InputHyperparameterValues - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Set of values to be used as hyperparameter values during Cross-Validation.
- inputOrderTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- inputs(Vector) - 类中的静态方法 weka.gui.beans.BeanConnection
-
Returns a vector of BeanInstances that can be considered as inputs (or the left-hand side of a sub-flow)
- inputsContains(BeanInstance) - 类中的方法 weka.gui.beans.MetaBean
- inRanges(Instance, double[][]) - 类中的方法 weka.core.NormalizableDistance
-
Test if an instance is within the given ranges.
- insert(double, double, double) - 类中的方法 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Inserts a new entry in the hashtable using the specified key.
- insert(int) - 类中的方法 weka.classifiers.functions.supportVector.SMOset
-
Inserts an element into the set.
- insert(DataObject) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Inserts a new dataObject into the database
- insert(DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Inserts a new dataObject into the database
- insertAttributeAt(int) - 类中的方法 weka.core.Instance
-
Inserts an attribute at the given position (0 to numAttributes()).
- insertAttributeAt(Attribute, int) - 类中的方法 weka.core.Instances
-
Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.
- insertElementAt(Object, int) - 类中的方法 weka.core.FastVector
-
Inserts an element at the given position.
- insertElementAt(Object, int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Inserts the specified object as a component in this list at the specified index.
- installLinearModels() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Traverses the tree and installs linear models at each node.
- installSmoothedModels() - 类中的方法 weka.classifiers.trees.m5.RuleNode
- instance(int) - 类中的方法 weka.core.Instances
-
Returns the instance at the given position.
- Instance - weka.core中的类
-
Class for handling an instance.
- Instance(double, double[]) - 类的构造器 weka.core.Instance
-
Constructor that inititalizes instance variable with given values.
- Instance(int) - 类的构造器 weka.core.Instance
-
Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.
- Instance(Instance) - 类的构造器 weka.core.Instance
-
Constructor that copies the attribute values and the weight from the given instance.
- INSTANCE_AVAILABLE - 类中的静态变量 weka.gui.beans.InstanceEvent
- INSTANCE_AVAILABLE - 类中的静态变量 weka.gui.streams.InstanceEvent
-
Specifies that an instance is available
- InstanceComparator - weka.core中的类
-
A comparator for the Instance class.
- InstanceComparator() - 类的构造器 weka.core.InstanceComparator
-
initializes the comparator and includes the class in the comparison
- InstanceComparator(boolean) - 类的构造器 weka.core.InstanceComparator
-
initializes the comparator
- InstanceCounter - weka.gui.streams中的类
-
A bean that counts instances streamed to it.
- InstanceCounter() - 类的构造器 weka.gui.streams.InstanceCounter
- InstanceEvent - weka.gui.beans中的类
-
Event that encapsulates a single instance or header information only
- InstanceEvent - weka.gui.streams中的类
-
An event encapsulating an instance stream event.
- InstanceEvent(Object) - 类的构造器 weka.gui.beans.InstanceEvent
- InstanceEvent(Object, int) - 类的构造器 weka.gui.streams.InstanceEvent
-
Constructs an InstanceEvent with the specified source object and event type
- InstanceEvent(Object, Instance, int) - 类的构造器 weka.gui.beans.InstanceEvent
-
Creates a new
InstanceEvent
instance that encapsulates a single instance only. - InstanceEvent(Object, Instances) - 类的构造器 weka.gui.beans.InstanceEvent
-
Creates a new
InstanceEvent
instance which encapsulates header information only. - InstanceJoiner - weka.gui.streams中的类
-
A bean that joins two streams of instances into one.
- InstanceJoiner() - 类的构造器 weka.gui.streams.InstanceJoiner
-
Setup the initial states of the member variables
- InstanceListener - weka.gui.beans中的接口
-
Interface to something that can accept instance events
- InstanceListener - weka.gui.streams中的接口
-
An interface for objects interested in listening to streams of instances.
- InstanceLoader - weka.gui.streams中的类
-
A bean that produces a stream of instances from a file.
- InstanceLoader() - 类的构造器 weka.gui.streams.InstanceLoader
- instanceProduced(InstanceEvent) - 类中的方法 weka.gui.streams.InstanceCounter
- instanceProduced(InstanceEvent) - 类中的方法 weka.gui.streams.InstanceJoiner
- instanceProduced(InstanceEvent) - 接口中的方法 weka.gui.streams.InstanceListener
- instanceProduced(InstanceEvent) - 类中的方法 weka.gui.streams.InstanceSavePanel
- instanceProduced(InstanceEvent) - 类中的方法 weka.gui.streams.InstanceTable
- instanceProduced(InstanceEvent) - 类中的方法 weka.gui.streams.InstanceViewer
- InstanceProducer - weka.gui.streams中的接口
-
An interface for objects capable of producing streams of instances.
- InstanceQuery - weka.experiment中的类
-
Convert the results of a database query into instances.
- InstanceQuery() - 类的构造器 weka.experiment.InstanceQuery
-
Sets up the database drivers
- instanceRangeTipText() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Returns the tip text for this property
- Instances - weka.core中的类
-
Class for handling an ordered set of weighted instances.
- Instances(Reader) - 类的构造器 weka.core.Instances
-
Reads an ARFF file from a reader, and assigns a weight of one to each instance.
- Instances(Reader, int) - 类的构造器 weka.core.Instances
-
已过时。instead of using this method in conjunction with the
readInstance(Reader)
method, one should use theArffLoader
orDataSource
class instead. - Instances(String, FastVector, int) - 类的构造器 weka.core.Instances
-
Creates an empty set of instances.
- Instances(Instances) - 类的构造器 weka.core.Instances
-
Constructor copying all instances and references to the header information from the given set of instances.
- Instances(Instances, int) - 类的构造器 weka.core.Instances
-
Constructor creating an empty set of instances.
- Instances(Instances, int, int) - 类的构造器 weka.core.Instances
-
Creates a new set of instances by copying a subset of another set.
- InstanceSavePanel - weka.gui.streams中的类
-
A bean that saves a stream of instances to a file.
- InstanceSavePanel() - 类的构造器 weka.gui.streams.InstanceSavePanel
- instancesDownBranch(int, Instances) - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Gets the subset of instances that apply to a particluar branch of the split.
- instancesDownBranch(int, Instances) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Gets the subset of instances that apply to a particluar branch of the split.
- instancesDownBranch(int, Instances) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Gets the subset of instances that apply to a particluar branch of the split.
- instancesIndicesTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Returns the tip text for this property
- InstancesResultListener - weka.experiment中的类
-
Outputs the received results in arff format to a Writer.
- InstancesResultListener() - 类的构造器 weka.experiment.InstancesResultListener
-
Sets temporary file.
- InstancesSummaryPanel - weka.gui中的类
-
This panel just displays relation name, number of instances, and number of attributes.
- InstancesSummaryPanel() - 类的构造器 weka.gui.InstancesSummaryPanel
-
Creates the instances panel with no initial instances.
- InstanceStreamToBatchMaker - weka.gui.beans中的类
-
Bean that converts an instance stream into a (batch) data set.
- InstanceStreamToBatchMaker() - 类的构造器 weka.gui.beans.InstanceStreamToBatchMaker
- InstanceStreamToBatchMakerBeanInfo - weka.gui.beans中的类
-
BeanInfo class for the InstanceStreamToBatchMaker bean
- InstanceStreamToBatchMakerBeanInfo() - 类的构造器 weka.gui.beans.InstanceStreamToBatchMakerBeanInfo
- InstanceTable - weka.gui.streams中的类
-
A bean that takes a stream of instances and displays in a table.
- InstanceTable() - 类的构造器 weka.gui.streams.InstanceTable
- instanceToSchema(Instance, MiningSchema) - 类中的方法 weka.core.pmml.MappingInfo
-
Convert an
Instance
to an array of values that matches the format of the mining schema. - InstanceViewer - weka.gui.streams中的类
-
This is a very simple instance viewer - just displays the dataset as text output as it would be written to a file.
- InstanceViewer() - 类的构造器 weka.gui.streams.InstanceViewer
- INSTITUTION - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The sponsoring institution of a technical report.
- intCount - 类中的变量 weka.core.AttributeStats
-
The number of int-like values
- INTEGER - 类中的静态变量 weka.datagenerators.clusterers.SubspaceCluster
-
cluster subtype: integer
- INTEGER - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for INTEGER used for reading experiment results.
- intercept() - 类中的方法 weka.classifiers.trees.m5.PreConstructedLinearModel
-
Return the intercept
- internalCacheSizeTipText() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the tip text for this property
- internalsTipText() - 类中的方法 weka.classifiers.bayes.WAODE
-
Returns the tip text for this property
- InterquartileRange - weka.filters.unsupervised.attribute中的类
-
A filter for detecting outliers and extreme values based on interquartile ranges.
- InterquartileRange() - 类的构造器 weka.filters.unsupervised.attribute.InterquartileRange
- intersectSubsets(ScatterSearchV1.Subset, ScatterSearchV1.Subset) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Intersects two subsets
- IntervalEstimator - weka.classifiers中的接口
-
Interface for classifiers that can output confidence intervals
- IntVector - weka.core.matrix中的类
-
A vector specialized on integers.
- IntVector() - 类的构造器 weka.core.matrix.IntVector
-
Constructs a null vector.
- IntVector(int) - 类的构造器 weka.core.matrix.IntVector
-
Constructs an n-vector of zeros.
- IntVector(int[]) - 类的构造器 weka.core.matrix.IntVector
-
Constructs a vector given an int array
- IntVector(int, int) - 类的构造器 weka.core.matrix.IntVector
-
Constructs an n-vector of a constant
- INVALID - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Value.Property
- inverse() - 类中的方法 weka.core.matrix.Matrix
-
Matrix inverse or pseudoinverse
- inverseIterator() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- invertSelectionTipText() - 类中的方法 weka.core.NormalizableDistance
-
Returns the tip text for this property.
- invertSelectionTipText() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns the tip text for this property.
- invertSelectionTipText() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the tip text for this property
- invertSelectionTipText() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Returns the tip text for this property
- invertTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns the tip text for this property
- invoke(Object, String, Class[], Object[]) - 类中的静态方法 weka.core.Jython
-
executes the specified method and returns the result, if any
- invoke(String, Class[], Object[]) - 类中的方法 weka.core.Jython
-
executes the specified method on the current interpreter and returns the result, if any
- invokeMain(String, String[]) - 类中的静态方法 weka.gui.SplashWindow
-
Invokes the main method of the provided class name.
- invokeMethod(String, String, String[]) - 类中的静态方法 weka.gui.SplashWindow
-
Invokes the named method of the provided class name.
- is(String) - 类中的方法 weka.core.Stopwords
-
Returns true if the given string is a stop word.
- IS - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- isALeaf() - 类中的方法 weka.core.neighboursearch.balltrees.BallNode
-
Returns true if the node is a leaf node (if both its left and right child are null).
- isALeaf() - 类中的方法 weka.core.neighboursearch.CoverTree.CoverTreeNode
-
Returns whether if the node is a leaf or not.
- isALeaf() - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNode
-
Checks if node is a leaf.
- isAllowed(Class, String) - 类中的方法 weka.core.xml.PropertyHandler
-
returns whether the given property (display name) is allowed for the given class.
- isAllowed(Object, String) - 类中的方法 weka.core.xml.PropertyHandler
-
returns whether the given property (display name) is allowed for the given object .
- isArff(String) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSource
-
returns whether the extension of the location is likely to be of ARFF format, i.e., ending in ".arff" or ".arff.gz" (case-insensitive).
- isAttribute() - enum class中的方法 weka.core.Capabilities.Capability
-
returns true if the capability is an attribute
- isAttributeCapability() - enum class中的方法 weka.core.Capabilities.Capability
-
returns true if the capability is an attribute capability
- isAveragable() - 类中的方法 weka.core.Attribute
-
Returns whether the attribute can be averaged meaningfully.
- ISBN - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The International Standard Book Number (10 digits).
- ISBN13 - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The International Standard Book Number (13 digits).
- isBoolean(int) - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Returns true if attribute is boolean
- isBusy() - 类中的方法 weka.gui.beans.Associator
-
Returns true if.
- isBusy() - 接口中的方法 weka.gui.beans.BeanCommon
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.ClassAssigner
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.Classifier
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.ClassValuePicker
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.Clusterer
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.Filter
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.Loader
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.MetaBean
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.PredictionAppender
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.Saver
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.StripChart
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.TestSetMaker
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.TextViewer
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.TrainingSetMaker
-
Returns true if.
- isBusy() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Returns true if.
- isCellEditable(int, int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns true if the cell at rowindex and columnindexis editable
- isCellEditable(int, int) - 类中的方法 weka.gui.SortedTableModel
-
Returns true if the cell at rowIndex and columnIndex is editable.
- isCellEditable(int, int) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
returns true if the cell at rowindex and columnindexis editable.
- isChanged() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
return true when current state differs from the state the network was last saved
- isChanged() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns whether the content of the panel was changed
- isChanged() - 类中的方法 weka.gui.ViewerDialog
-
returns whether the data has been changed
- isClass() - 类中的方法 weka.associations.tertius.Predicate
- isClass() - enum class中的方法 weka.core.Capabilities.Capability
-
returns true if the capability is a class
- isClassCapability() - enum class中的方法 weka.core.Capabilities.Capability
-
returns true if the capability is a other capability
- isClassname(String) - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
tests whether the given partial string is the name of a class with classpath - it basically tests, whether the string consists only of alphanumeric literals, underscores and dots.
- isConnected() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns true if a database connection is active.
- isConnected() - 类中的方法 weka.gui.sql.event.ConnectionEvent
-
returns whether the connection is still open.
- isContainedBy(Instance) - 类中的方法 weka.associations.gsp.Element
-
Checks if an Element is contained by a given Instance.
- isContinuous() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
checks, whether cluster sub type is continuous
- isCoreFileLoader(String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
checks whether the given class is one of the hardcoded core file loaders.
- isCoreFileSaver(String) - 类中的静态方法 weka.core.converters.ConverterUtils
-
checks whether the given class is one of the hardcoded core file savers.
- isCover(Instance) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Whether the instance covered by this rule
- isCpuTime() - 类中的方法 weka.core.Debug.Clock
-
whether the measurement is based on the msecs returned from the System class or on the more accurate CPU time.
- isCursorScrollable() - 类中的方法 weka.experiment.DatabaseUtils
-
Checks whether cursors are scrollable in general, false otherwise (also if not connected).
- isCursorScrollSensitive() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns whether the cursors only support forward movement or are scroll sensitive (with ResultSet.CONCUR_READ_ONLY concurrency).
- isDate() - 类中的方法 weka.core.Attribute
-
Tests if the attribute is a date type.
- isDebug() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns true if debug is turned on.
- isEmpty() - 类中的方法 weka.associations.gsp.Element
-
Checks if the Element contains any events.
- isEmpty() - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if this set is empty.
- isEmpty() - 类中的方法 weka.associations.tertius.Rule
-
Test if this rule is empty.
- isEmpty() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- isEmpty() - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Returns true if it is empty.
- isEmpty() - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Check if the matrix is empty
- isEmpty() - 类中的方法 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Tests if this hashtable maps no keys to values.
- isEmpty() - 类中的方法 weka.core.matrix.DoubleVector
-
Checks if it is an empty vector
- isEmpty() - 类中的方法 weka.core.matrix.IntVector
-
Returns true if the vector is empty
- isEmpty() - 类中的方法 weka.core.Trie
-
Returns true if this collection contains no elements.
- isEnabled() - 类中的方法 weka.core.Memory
-
returns whether the memory management is enabled
- isEnabled(Capabilities.Capability) - 类中的方法 weka.core.FindWithCapabilities
-
whether the given capability is enabled.
- isEnabledNot(Capabilities.Capability) - 类中的方法 weka.core.FindWithCapabilities
-
whether the given "not to have" capability is enabled.
- isEqual(ScatterSearchV1.Subset) - 类中的方法 weka.attributeSelection.ScatterSearchV1.Subset
- isFirstBatchDone() - 类中的方法 weka.filters.Filter
-
Returns true if the first batch of instances got processed.
- isFullRank() - 类中的方法 weka.core.matrix.QRDecomposition
-
Is the matrix full rank?
- isGaussian() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
checks, whether cluster type is gaussian
- isHidden() - 类中的方法 weka.gui.beans.BeanConnection
-
Returns true if this connection is invisible
- isHierachic(String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Whether the given string has a hierachy structure with the seperators
- isIgnored(Class, String) - 类中的方法 weka.core.xml.PropertyHandler
-
checks whether the given display name of a certain class is an ignored property.
- isIgnored(Object, String) - 类中的方法 weka.core.xml.PropertyHandler
-
checks whether the given display name of a given object is an ignored property.
- isIgnored(String) - 类中的方法 weka.core.xml.PropertyHandler
-
checks whether the given display name is an ignored property
- isIncludedIn(Rule) - 类中的方法 weka.associations.tertius.Body
-
Test if this Body is included in a rule.
- isIncludedIn(Rule) - 类中的方法 weka.associations.tertius.Head
-
Test if this Head is included in a rule.
- isIncludedIn(Rule) - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if this LiteralSet is included in a rule.
- isIncremental() - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
returns whether the loader is an incremental one.
- isInitialAnchorRandom() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Gets whether if the initial anchor is chosen randomly.
- isInRange(double) - 类中的方法 weka.core.Attribute
-
Determines whether a value lies within the bounds of the attribute.
- isInRange(int) - 类中的方法 weka.core.Range
-
Gets whether the supplied cardinal number is included in the current range.
- isInteger() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
checks, whether cluster sub type is integer
- isKeyword(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Checks whether the given string is a reserved keyword.
- isKOML(String) - 类中的静态方法 weka.core.xml.SerialUIDChanger
-
checks whether the given filename ends with ".koml"
- isLeaf() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Return true if this node is a leaf
- isLeafReached() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Whether the current position is a leaf
- isMissing(int) - 类中的方法 weka.core.Instance
-
Tests if a specific value is "missing".
- isMissing(int) - 类中的方法 weka.core.SparseInstance
-
Tests if a specific value is "missing".
- isMissing(Attribute) - 类中的方法 weka.core.Instance
-
Tests if a specific value is "missing".
- ISMISSING - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- isMissingAt(int, int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
checks whether the value at the given position is missing
- isMissingAt(int, int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
checks whether the value at the given position is missing
- isMissingSparse(int) - 类中的方法 weka.core.Instance
-
Tests if a specific value is "missing".
- isMissingValue(double) - 类中的静态方法 weka.core.Instance
-
Tests if the given value codes "missing".
- isMonitoring() - 类中的方法 weka.gui.MemoryUsagePanel
-
Returns whether the thread is still running.
- isNewBatch() - 类中的方法 weka.filters.Filter
-
Returns true if the a new batch was started, either a new instance of the filter was created or the batchFinished() method got called.
- isNewer(Object) - 类中的方法 weka.core.Version
-
checks whether this version is newer than the one from the given version string
- isNominal() - 类中的方法 weka.core.Attribute
-
Test if the attribute is nominal.
- isNominal() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns true if selection attribute is nominal.
- isNominal() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns true if selection attribute is nominal.
- isNominal(int) - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Returns true if attribute is nominal
- isNonsingular() - 类中的方法 weka.core.matrix.LUDecomposition
-
Is the matrix nonsingular?
- isNormalizeData() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns true if the data is to be normalized first
- isNotificationEnabled() - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns whether the notification of changes is enabled
- isNotificationEnabled() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns whether the notification of changes is enabled
- isNullAt(int, int) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
checks whether the value of the cell is NULL.
- isNumeric() - 类中的方法 weka.core.Attribute
-
Tests if the attribute is numeric.
- isNumeric() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns true if selection attribute is numeric.
- isNumericAt(int) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
returns whether the column at the given index is numeric.
- isOlder(Object) - 类中的方法 weka.core.Version
-
checks whether this version is older than the one from the given version string
- isOpticsOutputs() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
-
Returns the flag for writing actions
- isOtherCapability() - enum class中的方法 weka.core.Capabilities.Capability
-
returns true if the capability is a class capability
- IsotonicRegression - weka.classifiers.functions中的类
-
Learns an isotonic regression model.
- IsotonicRegression() - 类的构造器 weka.classifiers.functions.IsotonicRegression
- isOutOfMemory() - 类中的方法 weka.core.Memory
-
checks if there's still enough memory left by checking whether there is still a 50MB margin between getUsed() and getMax().
- isOutputFormatDefined() - 类中的方法 weka.filters.Filter
-
Returns whether the output format is ready to be collected
- isOutputFormatDefined() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Returns whether the output format is ready to be collected
- isPaintable() - 类中的方法 weka.gui.CostMatrixEditor
-
Indicates whether the object can be represented graphically.
- isPaintable() - 类中的方法 weka.gui.FileEditor
-
Returns true since this editor is paintable.
- isPaintable() - 类中的方法 weka.gui.GenericArrayEditor
-
Returns true to indicate that we can paint a representation of the string array.
- isPaintable() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns true to indicate that we can paint a representation of the Object.
- isPaintable() - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Indicates whether the object can be represented graphically.
- isPanelSelected() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
checks whether a panel is currently selected
- isPresent() - 类中的静态方法 weka.classifiers.functions.LibLINEAR
-
returns whether the liblinear classes are present or not, i.e.
- isPresent() - 类中的静态方法 weka.classifiers.functions.LibSVM
-
returns whether the libsvm classes are present or not, i.e.
- isPresent() - 类中的静态方法 weka.core.Jython
-
returns whether the Jython classes are present or not, i.e.
- isPresent() - 类中的静态方法 weka.core.stemmers.SnowballStemmer
-
returns whether Snowball is present or not, i.e.
- isPresent() - 类中的静态方法 weka.core.xml.KOML
-
returns whether KOML is present or not, i.e.
- isPresent() - 类中的静态方法 weka.core.xml.XStream
-
returns whether XStream is present or not, i.e.
- isProcessed() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Gives information about the status of a dataObject
- isProcessed() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Gives information about the status of a dataObject
- isProcessed() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Gives information about the status of a dataObject
- isRandom() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
checks, whether cluster type is random
- isReadOnly() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns whether the model is read-only
- isReadOnly() - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns whether the model is read-only
- isReadOnly() - 类中的方法 weka.gui.arffviewer.ArffTable
-
returns whether the model is read-only
- isReadOnly() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns whether the model is read-only
- isRegular() - 类中的方法 weka.core.Attribute
-
Returns whether the attribute values are equally spaced.
- isRelationValued() - 类中的方法 weka.core.Attribute
-
Tests if the attribute is relation valued.
- isResultRequired(ResultProducer, Object[]) - 类中的方法 weka.experiment.AveragingResultProducer
-
Determines whether the results for a specified key must be generated.
- isResultRequired(ResultProducer, Object[]) - 类中的方法 weka.experiment.CSVResultListener
-
Always says a result is required.
- isResultRequired(ResultProducer, Object[]) - 类中的方法 weka.experiment.DatabaseResultListener
-
Always says a result is required.
- isResultRequired(ResultProducer, Object[]) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Determines whether the results for a specified key must be generated.
- isResultRequired(ResultProducer, Object[]) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Determines whether the results for a specified key must be generated.
- isResultRequired(ResultProducer, Object[]) - 接口中的方法 weka.experiment.ResultListener
-
Determines whether the results for a specified key must be generated.
- isRootReached() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Whether the current position is the root
- isRunning() - 类中的方法 weka.core.Debug.Clock
-
whether the time is still being clocked
- isSaved() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
indicate the network state was saved
- isSequentialAttIndexValid() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns whether or not the Sequential Attribute Index requires rebuilding due to a change
- isSequentialInstanceIndexValid() - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Returns whether or not the Sequential Instance Index requires rebuilding due to a change
- isSerializable(Class) - 类中的静态方法 weka.core.SerializationHelper
-
checks whether a class is serializable.
- isSerializable(String) - 类中的静态方法 weka.core.SerializationHelper
-
checks whether a class is serializable.
- isShowCoreDistances() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Returns the flag for showCoreDistances
- isShowReachabilityDistances() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Returns the flag for showReachabilityDistances
- ISSN - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The International Standard Serial Number.
- isSorted() - 类中的方法 weka.gui.SortedTableModel
-
returns whether the table was sorted
- isSPD() - 类中的方法 weka.core.matrix.CholeskyDecomposition
-
Is the matrix symmetric and positive definite?
- isSquare() - 类中的方法 weka.core.matrix.Matrix
-
returns whether the matrix is a square matrix or not.
- isStopword(String) - 类中的静态方法 weka.core.Stopwords
-
Returns true if the given string is a stop word.
- isStreamableFilter() - 类中的方法 weka.filters.MultiFilter
-
tests whether all the enclosed filters are streamable
- isString() - 类中的方法 weka.core.Attribute
-
Tests if the attribute is a string.
- isStructureOnly() - 类中的方法 weka.gui.beans.DataSetEvent
-
Returns true if the encapsulated instances contain just header information
- isStructureOnly() - 类中的方法 weka.gui.beans.TestSetEvent
-
Returns true if the encapsulated instances contain just header information
- isStructureOnly() - 类中的方法 weka.gui.beans.TrainingSetEvent
-
Returns true if the encapsulated instances contain just header information
- isSubclass(Class, Class) - 类中的静态方法 weka.core.ClassDiscovery
-
Checks whether the "otherclass" is a subclass of the given "superclass".
- isSubclass(String, String) - 类中的静态方法 weka.core.ClassDiscovery
-
Checks whether the "otherclass" is a subclass of the given "superclass".
- isSymmetric() - 类中的方法 weka.core.Matrix
-
已过时。Returns true if the matrix is symmetric.
- isSymmetric() - 类中的方法 weka.core.matrix.Matrix
-
Returns true if the matrix is symmetric.
- isUndoEnabled() - 接口中的方法 weka.core.Undoable
-
returns whether undo support is enabled
- isUndoEnabled() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
returns whether undo support is enabled
- isUndoEnabled() - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
returns whether undo support is enabled
- isUndoEnabled() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
returns whether undo support is enabled
- isUniform() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
checks, whether cluster type is uniform
- isUseK2Prior() - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
Returns whether K2 prior is used
- isUseK2Prior() - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
- isUseVariant1() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Whether variant 1 is used
- itemAt(int) - 类中的方法 weka.associations.ItemSet
-
Gest the index of the value of the specified attribute
- items() - 类中的方法 weka.associations.ItemSet
-
Gest the item set as an int array
- ItemSet - weka.associations中的类
-
Class for storing a set of items.
- ItemSet(int) - 类的构造器 weka.associations.ItemSet
-
Constructor
- ItemSet(int[]) - 类的构造器 weka.associations.ItemSet
-
Contsructor
- ItemSet(int, int[]) - 类的构造器 weka.associations.ItemSet
-
Constructor
- itemStateChanged(ItemEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Performs the action associated with the ItemEvent.
- IteratedLovinsStemmer - weka.core.stemmers中的类
-
An iterated version of the Lovins stemmer.
- IteratedLovinsStemmer() - 类的构造器 weka.core.stemmers.IteratedLovinsStemmer
- IteratedSingleClassifierEnhancer - weka.classifiers中的类
-
Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.
- IteratedSingleClassifierEnhancer() - 类的构造器 weka.classifiers.IteratedSingleClassifierEnhancer
- iterationCounter - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Iteration counter
- IterativeClassifier - weka.classifiers中的接口
-
Interface for classifiers that can induce models of growing complexity one step at a time.
- iterator() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- iterator() - 类中的方法 weka.core.Trie
-
Returns an iterator over the elements in this collection.
J
- J48 - weka.classifiers.trees中的类
-
Class for generating a pruned or unpruned C4.5 decision tree.
- J48() - 类的构造器 weka.classifiers.trees.J48
- J48graft - weka.classifiers.trees中的类
-
Class for generating a grafted (pruned or unpruned) C4.5 decision tree.
- J48graft() - 类的构造器 weka.classifiers.trees.J48graft
- Javadoc - weka.core中的类
-
Abstract superclass for classes that generate Javadoc comments and replace the content between certain comment tags.
- Javadoc() - 类的构造器 weka.core.Javadoc
- JComponentWriter - weka.gui.visualize中的类
-
This class takes any JComponent and outputs it to a file.
- JComponentWriter() - 类的构造器 weka.gui.visualize.JComponentWriter
-
initializes the object
- JComponentWriter(JComponent) - 类的构造器 weka.gui.visualize.JComponentWriter
-
initializes the object with the given Component
- JComponentWriter(JComponent, File) - 类的构造器 weka.gui.visualize.JComponentWriter
-
initializes the object with the given Component and filename
- JListHelper - weka.gui中的类
-
A helper class for JList GUI elements with DefaultListModel or derived models.
- JListHelper() - 类的构造器 weka.gui.JListHelper
- joinOptions(String[]) - 类中的静态方法 weka.core.Utils
-
Joins all the options in an option array into a single string, as might be used on the command line.
- joinSubsets(ScatterSearchV1.Subset, ScatterSearchV1.Subset) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Join two subsets
- JOURNAL - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
A journal name.
- JPEGWriter - weka.gui.visualize中的类
-
This class takes any JComponent and outputs it to a JPEG-file.
- JPEGWriter() - 类的构造器 weka.gui.visualize.JPEGWriter
-
initializes the object.
- JPEGWriter(JComponent) - 类的构造器 weka.gui.visualize.JPEGWriter
-
initializes the object with the given Component.
- JPEGWriter(JComponent, File) - 类的构造器 weka.gui.visualize.JPEGWriter
-
initializes the object with the given Component and filename.
- JRip - weka.classifiers.rules中的类
-
This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W.
- JRip() - 类的构造器 weka.classifiers.rules.JRip
- JRip.Antd - weka.classifiers.rules中的类
-
The single antecedent in the rule, which is composed of an attribute and the corresponding value.
- JRip.NominalAntd - weka.classifiers.rules中的类
-
The antecedent with nominal attribute
- JRip.NumericAntd - weka.classifiers.rules中的类
-
The antecedent with numeric attribute
- JRip.RipperRule - weka.classifiers.rules中的类
-
This class implements a single rule that predicts specified class.
- JTableHelper - weka.gui中的类
-
A helper class for JTable, e.g.
- JTableHelper(JTable) - 类的构造器 weka.gui.JTableHelper
-
initializes the object
- JTreePopupMenu(JTree) - 类的构造器 weka.gui.GenericObjectEditor.JTreePopupMenu
-
Constructs a new popup menu.
- Jython - weka.core中的类
-
A helper class for Jython.
- Jython() - 类的构造器 weka.core.Jython
-
default constructor, tries to instantiate a Python Interpreter
- JythonObject - weka.core中的接口
-
An indicator interface for Jython objects.
- JythonSerializableObject - weka.core中的接口
-
An indicator interface for serializable Jython objects.
K
- k_nextNeighbourQuery(int, double, DataObject) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Emits the k next-neighbours and performs an epsilon-range-query at the parallel.
- k_nextNeighbourQuery(int, double, DataObject) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Emits the k next-neighbours and performs an epsilon-range-query at the parallel.
- K2 - weka.classifiers.bayes.net.search.global中的类
-
This Bayes Network learning algorithm uses a hill climbing algorithm restricted by an order on the variables.
For more information see:
G.F. - K2 - weka.classifiers.bayes.net.search.local中的类
-
This Bayes Network learning algorithm uses a hill climbing algorithm restricted by an order on the variables.
For more information see:
G.F. - K2() - 类的构造器 weka.classifiers.bayes.net.search.global.K2
- K2() - 类的构造器 weka.classifiers.bayes.net.search.local.K2
- kappa() - 类中的方法 weka.classifiers.Evaluation
-
Returns value of kappa statistic if class is nominal.
- KBInformation() - 类中的方法 weka.classifiers.Evaluation
-
Return the total Kononenko & Bratko Information score in bits
- KBMeanInformation() - 类中的方法 weka.classifiers.Evaluation
-
Return the Kononenko & Bratko Information score in bits per instance.
- KBRelativeInformation() - 类中的方法 weka.classifiers.Evaluation
-
Return the Kononenko & Bratko Relative Information score
- KDConditionalEstimator - weka.estimators中的类
-
Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate kernel estimators for each discrete conditioning value).
- KDConditionalEstimator(int, double) - 类的构造器 weka.estimators.KDConditionalEstimator
-
Constructor
- KDDataGenerator - weka.gui.boundaryvisualizer中的类
-
KDDataGenerator.
- KDDataGenerator() - 类的构造器 weka.gui.boundaryvisualizer.KDDataGenerator
- KDTree - weka.core.neighboursearch中的类
-
Class implementing the KDTree search algorithm for nearest neighbour search.
The connection to dataset is only a reference. - KDTree() - 类的构造器 weka.core.neighboursearch.KDTree
-
Creates a new instance of KDTree.
- KDTree(Instances) - 类的构造器 weka.core.neighboursearch.KDTree
-
Creates a new instance of KDTree.
- KDTreeNode - weka.core.neighboursearch.kdtrees中的类
-
A class representing a KDTree node.
- KDTreeNode() - 类的构造器 weka.core.neighboursearch.kdtrees.KDTreeNode
-
Constructor.
- KDTreeNode(int, int, int, double[][]) - 类的构造器 weka.core.neighboursearch.kdtrees.KDTreeNode
-
Constructor.
- KDTreeNode(int, int, int, double[][], double[][]) - 类的构造器 weka.core.neighboursearch.kdtrees.KDTreeNode
- KDTreeNodeSplitter - weka.core.neighboursearch.kdtrees中的类
-
Class that splits up a KDTreeNode.
- KDTreeNodeSplitter() - 类的构造器 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
default constructor.
- KDTreeNodeSplitter(int[], Instances, EuclideanDistance) - 类的构造器 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Creates a new instance of KDTreeNodeSplitter.
- KDTreeTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- Kernel - weka.classifiers.functions.supportVector中的类
-
Abstract kernel.
- Kernel() - 类的构造器 weka.classifiers.functions.supportVector.Kernel
- KernelEstimator - weka.estimators中的类
-
Simple kernel density estimator.
- KernelEstimator(double) - 类的构造器 weka.estimators.KernelEstimator
-
Constructor that takes a precision argument.
- KernelEvaluation - weka.classifiers.functions.supportVector中的类
-
Class for evaluating Kernels.
- KernelEvaluation() - 类的构造器 weka.classifiers.functions.supportVector.KernelEvaluation
-
default constructor
- kernelFactorExpressionTipText() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns the tip text for this property
- KernelFilter - weka.filters.unsupervised.attribute中的类
-
Converts the given set of predictor variables into a kernel matrix.
- KernelFilter() - 类的构造器 weka.filters.unsupervised.attribute.KernelFilter
- kernelMatrixFileTipText() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Returns the tip text for this property
- kernelTipText() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Returns the tip text for this property
- kernelTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- kernelTipText() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns the tip text for this property
- kernelTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- kernelTipText() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns the tip text for this property
- kernelTipText() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns the tip text for this property
- KERNELTYPE_LINEAR - 类中的静态变量 weka.classifiers.functions.LibSVM
-
kernel type linear: u'*v
- KERNELTYPE_POLYNOMIAL - 类中的静态变量 weka.classifiers.functions.LibSVM
-
kernel type polynomial: (gamma*u'*v + coef0)^degree
- KERNELTYPE_RBF - 类中的静态变量 weka.classifiers.functions.LibSVM
-
kernel type radial basis function: exp(-gamma*|u-v|^2)
- KERNELTYPE_SIGMOID - 类中的静态变量 weka.classifiers.functions.LibSVM
-
kernel type sigmoid: tanh(gamma*u'*v + coef0)
- kernelTypeTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- key - 类中的变量 weka.classifiers.lazy.kstar.KStarCache.TableEntry
-
attribute value
- KEY - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
Used for alphabetizing, cross referencing, and creating a label when the ``author'' information is missing.
- keyFieldNameTipText() - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns the tip text for this property
- keyIterator() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Returns an iterator over all the keys
- keyIterator() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Returns an iterator over all the keys
- keys() - 类中的方法 weka.core.xml.MethodHandler
-
returns an enumeration over all currently stored custom methods, i.e.
- keysTipText() - 类中的方法 weka.core.converters.DatabaseLoader
-
the tip text for this property
- KEYWORDS - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
Key words used for searching or possibly for annotation.
- kFoldCV(BayesNet, int) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
kFoldCV uses k-fold cross validation to measure the accuracy of a Bayes network classifier.
- KKConditionalEstimator - weka.estimators中的类
-
Conditional probability estimator for a numeric domain conditional upon a numeric domain.
- KKConditionalEstimator(double) - 类的构造器 weka.estimators.KKConditionalEstimator
-
Constructor
- KMeansInpiredMethod - weka.core.neighboursearch.kdtrees中的类
-
The class that splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.
For more information see also:
Ashraf Masood Kibriya (2007). - KMeansInpiredMethod() - 类的构造器 weka.core.neighboursearch.kdtrees.KMeansInpiredMethod
- kNearestNeighbours(Instance, int) - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns k nearest instances in the current neighbourhood to the supplied instance.
- kNearestNeighbours(Instance, int) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns k-NNs of a given target instance, from among the previously supplied training instances (supplied through setInstances method) P.S.: May return more than k-NNs if more one instances have the same distance to the target as the kth NN.
- kNearestNeighbours(Instance, int) - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the k nearest neighbours of the supplied instance.
- kNearestNeighbours(Instance, int) - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Returns k nearest instances in the current neighbourhood to the supplied instance.
- kNearestNeighbours(Instance, int) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns k nearest instances in the current neighbourhood to the supplied instance.
- KNNTipText() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the tip text for this property.
- KNNTipText() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns the tip text for this property.
- KnowledgeFlow - weka.gui.beans中的类
-
Startup class for the KnowledgeFlow.
- KnowledgeFlow() - 类的构造器 weka.gui.beans.KnowledgeFlow
- KnowledgeFlowApp - weka.gui.beans中的类
-
Main GUI class for the KnowledgeFlow.
- KnowledgeFlowApp(boolean) - 类的构造器 weka.gui.beans.KnowledgeFlowApp
-
Creates a new
KnowledgeFlowApp
instance. - KOML - weka.core.xml中的类
-
This class is a helper class for XML serialization using KOML .
- KOML() - 类的构造器 weka.core.xml.KOML
- komlToBinary(String, String) - 类中的静态方法 weka.core.xml.SerialUIDChanger
-
converts a KOML file into a binary one
- KOMLV - 类中的静态变量 weka.gui.beans.SerializedModelSaver
- KStar - weka.classifiers.lazy中的类
-
K* is an instance-based classifier, that is the class of a test instance is based upon the class of those training instances similar to it, as determined by some similarity function.
- KStar() - 类的构造器 weka.classifiers.lazy.KStar
- KStarCache - weka.classifiers.lazy.kstar中的类
-
A class representing the caching system used to keep track of each attribute value and its corresponding scale factor or stop parameter.
- KStarCache() - 类的构造器 weka.classifiers.lazy.kstar.KStarCache
- KStarCache.CacheTable - weka.classifiers.lazy.kstar中的类
-
A custom hashtable class to support the caching system.
- KStarCache.TableEntry - weka.classifiers.lazy.kstar中的类
-
Hashtable collision list.
- KStarConstants - weka.classifiers.lazy.kstar中的接口
- KStarNominalAttribute - weka.classifiers.lazy.kstar中的类
-
A custom class which provides the environment for computing the transformation probability of a specified test instance nominal attribute to a specified train instance nominal attribute.
- KStarNominalAttribute(Instance, Instance, int, Instances, int[][], KStarCache) - 类的构造器 weka.classifiers.lazy.kstar.KStarNominalAttribute
-
Constructor
- KStarNumericAttribute - weka.classifiers.lazy.kstar中的类
-
A custom class which provides the environment for computing the transformation probability of a specified test instance numeric attribute to a specified train instance numeric attribute.
- KStarNumericAttribute(Instance, Instance, int, Instances, int[][], KStarCache) - 类的构造器 weka.classifiers.lazy.kstar.KStarNumericAttribute
-
Constructor
- KStarWrapper - weka.classifiers.lazy.kstar中的类
- KStarWrapper() - 类的构造器 weka.classifiers.lazy.kstar.KStarWrapper
- kthSmallestValue(double[], int) - 类中的静态方法 weka.core.Utils
-
Returns the kth-smallest value in the array
- kthSmallestValue(int[], int) - 类中的静态方法 weka.core.Utils
-
Returns the kth-smallest value in the array.
- kthSmallestValue(int, int) - 类中的方法 weka.core.Instances
-
Returns the kth-smallest attribute value of a numeric attribute.
- kthSmallestValue(Attribute, int) - 类中的方法 weka.core.Instances
-
Returns the kth-smallest attribute value of a numeric attribute.
- kullback(double[], double[], double[], double[], int) - 类中的方法 weka.classifiers.mi.MINND
-
This function calculates the Kullback Leibler distance between two normal distributions.
- KValueTipText() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns the tip text for this property
L
- LabeledItemSet - weka.associations中的类
-
Class for storing a set of items together with a class label.
- LabeledItemSet(int, int) - 类的构造器 weka.associations.LabeledItemSet
-
Constructor
- labelsTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Returns the tip text for this property
- LADTree - weka.classifiers.trees中的类
-
Class for generating a multi-class alternating decision tree using the LogitBoost strategy.
- LADTree() - 类的构造器 weka.classifiers.trees.LADTree
- LAGDHillClimber - weka.classifiers.bayes.net.search.local中的类
-
This Bayes Network learning algorithm uses a Look Ahead Hill Climbing algorithm called LAGD Hill Climbing.
- LAGDHillClimber() - 类的构造器 weka.classifiers.bayes.net.search.local.LAGDHillClimber
- lambdaTipText() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns the tip text for this property
- lambdaTipText() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the tip text for this property
- LANGUAGE - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The language the document is in.
- LaplaceEstimate(double, double, double) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns the probability estimate, using laplace correction
- laplaceForSubsetOfInterest() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- LaplacePriorImpl - weka.classifiers.bayes.blr中的类
-
Implementation of the Gaussian Prior update function based on modified CLG Algorithm (CLG-Lasso) with a certain Trust Region Update based on Laplace Priors.
- LaplacePriorImpl() - 类的构造器 weka.classifiers.bayes.blr.LaplacePriorImpl
- laplaceProb(int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns relative frequency of class over all bags with Laplace correction.
- laplaceProb(int, int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns relative frequency of class for given bag.
- laplaceUpdate(int, double) - 类中的方法 weka.classifiers.bayes.blr.LaplacePriorImpl
-
This is the CLG-lasso update function described in the
- LAPLACIAN - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
- last() - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Returns the last element in the stack.
- LAST - 类中的静态变量 weka.filters.unsupervised.attribute.ClassAssigner
-
use the last attribute as class.
- lastActionMsg() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
get message representing the last action performed on the network
- lastElement() - 类中的方法 weka.core.FastVector
-
Returns the last element of the vector.
- lastElement() - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Returns the last component of the list.
- lastIndexOf(Object) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Returns the index of the last occurrence of elem.
- lastIndexOf(Object, int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Searches backwards for elem, starting from the specified index, and returns an index to it.
- lastInstance() - 类中的方法 weka.core.Instances
-
Returns the last instance in the set.
- LatentSemanticAnalysis - weka.attributeSelection中的类
-
Performs latent semantic analysis and transformation of the data.
- LatentSemanticAnalysis() - 类的构造器 weka.attributeSelection.LatentSemanticAnalysis
- launchNext(int, int) - 类中的方法 weka.experiment.RemoteExperiment
-
Launch a sub experiment on a remote host
- layoutCompleted(LayoutCompleteEvent) - 类中的方法 weka.classifiers.bayes.net.GUI
-
This method is an implementation for LayoutCompleteEventListener class.
- layoutCompleted(LayoutCompleteEvent) - 类中的方法 weka.gui.graphvisualizer.GraphVisualizer
-
This method is an implementation for LayoutCompleteEventListener class.
- layoutCompleted(LayoutCompleteEvent) - 接口中的方法 weka.gui.graphvisualizer.LayoutCompleteEventListener
- LayoutCompleteEvent - weka.gui.graphvisualizer中的类
-
This is an event which is fired by a LayoutEngine once a LayoutEngine finishes laying out the graph, so that the Visualizer can repaint the screen to show the changes.
- LayoutCompleteEvent(Object) - 类的构造器 weka.gui.graphvisualizer.LayoutCompleteEvent
- LayoutCompleteEventListener - weka.gui.graphvisualizer中的接口
-
This interface should be implemented by any class which needs to receive LayoutCompleteEvents from the LayoutEngine.
- LayoutEngine - weka.gui.graphvisualizer中的接口
-
This interface class has been added to facilitate the addition of other layout engines to this package.
- layoutGraph() - 类中的方法 weka.gui.graphvisualizer.GraphVisualizer
-
This method lays out the graph by calling the LayoutEngine's layoutGraph() method.
- layoutGraph() - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
This method does a complete layout of the graph which includes removing cycles, assigning levels to nodes, reducing edge crossings and laying out the vertices horizontally for better visibility.
- layoutGraph() - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
This method lays out the graph for better visualization
- layoutGraph(FastVector, FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
set positions of all nodes
- LBR - weka.classifiers.lazy中的类
-
Lazy Bayesian Rules Classifier.
- LBR() - 类的构造器 weka.classifiers.lazy.LBR
- LBR.Indexes - weka.classifiers.lazy中的类
-
Class for handling instances and the associated attributes.
- LCCN - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The Library of Congress Call Number.
- LE - 接口中的静态变量 weka.core.mathematicalexpression.sym
- LE - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- LearningRateResultProducer - weka.experiment中的类
-
Tells a sub-ResultProducer to reproduce the current run for varying sized subsamples of the dataset.
- LearningRateResultProducer() - 类的构造器 weka.experiment.LearningRateResultProducer
- learningRateTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- leastExplainingColumn(PaceMatrix, IntVector, int, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns the index of the column that has the smallest (squared) response, when the column is moved to become the (ks-1)-th column.
- LeastMedSq - weka.classifiers.functions中的类
-
Implements a least median sqaured linear regression utilising the existing weka LinearRegression class to form predictions.
- LeastMedSq() - 类的构造器 weka.classifiers.functions.LeastMedSq
- leaveOneOut(LBR.Indexes, int[][][], int[], boolean[]) - 类中的方法 weka.classifiers.lazy.LBR
-
Leave-one-out strategy.
- leaveOneOutCV(BayesNet) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
LeaveOneOutCV returns the accuracy calculated using Leave One Out cross validation.
- LED24 - weka.datagenerators.classifiers.classification中的类
-
This generator produces data for a display with 7 LEDs.
- LED24() - 类的构造器 weka.datagenerators.classifiers.classification.LED24
-
initializes the generator with default values
- LEFT_PARENTHESES - 类中的变量 weka.experiment.ResultMatrix
-
the left parentheses for enumerating cols/rows
- leftNode() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the left child of this node
- leftSide(Instances) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Prints left side of condition.
- leftSide(Instances) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Prints left side of condition..
- leftSide(Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Prints left side of condition satisfied by instances.
- leftSide(Instances) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
Prints left side of condition satisfied by instances.
- leftSide(Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Does nothing because no condition has to be satisfied.
- leftSide(Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Prints left side of condition..
- leftSide(Instances) - 类中的方法 weka.classifiers.trees.j48.NoSplit
-
Does nothing because no condition has to be satisfied.
- leftSide(Instances) - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Returns name of splitting attribute (left side of condition).
- legend() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns the legend of the tree, describing how results are to be interpreted.
- legend() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns the legend of the tree, describing how results are to be interpreted.
- LegendPanel - weka.gui.visualize中的类
-
This panel displays legends for a list of plots.
- LegendPanel() - 类的构造器 weka.gui.visualize.LegendPanel
-
Constructor
- length - 类中的变量 weka.core.neighboursearch.covertrees.Stack
-
The number of elements in the stack.
- LEVERAGE - enum class 中的枚举常量 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
- leverageForRule(AprioriItemSet, AprioriItemSet, int, int) - 类中的方法 weka.associations.AprioriItemSet
-
Outputs the leverage for a rule.
- LFSMethods - weka.attributeSelection中的类
- LFSMethods() - 类的构造器 weka.attributeSelection.LFSMethods
-
empty constructor methods are not static because of access to inner class Link2 and LinkedList2
- LFSMethods.Link2 - weka.attributeSelection中的类
-
Class for a node in a linked list.
- LFSMethods.LinkedList2 - weka.attributeSelection中的类
-
Class for handling a linked list.
- LibLINEAR - weka.classifiers.functions中的类
-
A wrapper class for the liblinear tools (the liblinear classes, typically the jar file, need to be in the classpath to use this classifier).
Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin (2008). - LibLINEAR() - 类的构造器 weka.classifiers.functions.LibLINEAR
- LibSVM - weka.classifiers.functions中的类
-
A wrapper class for the libsvm tools (the libsvm classes, typically the jar file, need to be in the classpath to use this classifier).
LibSVM runs faster than SMO since it uses LibSVM to build the SVM classifier.
LibSVM allows users to experiment with One-class SVM, Regressing SVM, and nu-SVM supported by LibSVM tool. - LibSVM() - 类的构造器 weka.classifiers.functions.LibSVM
- LibSVMLoader - weka.core.converters中的类
-
Reads a source that is in libsvm format.
For more information about libsvm see:
http://www.csie.ntu.edu.tw/~cjlin/libsvm/ - LibSVMLoader() - 类的构造器 weka.core.converters.LibSVMLoader
- LibSVMSaver - weka.core.converters中的类
-
Writes to a destination that is in libsvm format.
For more information about libsvm see:
http://www.csie.ntu.edu.tw/~cjlin/libsvm/ - LibSVMSaver() - 类的构造器 weka.core.converters.LibSVMSaver
-
Constructor
- LIFT - enum class 中的枚举常量 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
- LIFT_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: Lift
- liftForRule(AprioriItemSet, AprioriItemSet, int) - 类中的方法 weka.associations.AprioriItemSet
-
Outputs the lift for a rule.
- likelihoodThresholdTipText() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the tip text for this property
- LINE - 类中的静态变量 weka.gui.visualize.VisualizePanelEvent
- LinearForwardSelection - weka.attributeSelection中的类
-
LinearForwardSelection:
Extension of BestFirst. - LinearForwardSelection() - 类的构造器 weka.attributeSelection.LinearForwardSelection
-
Constructor
- LinearNNSearch - weka.core.neighboursearch中的类
-
Class implementing the brute force search algorithm for nearest neighbour search.
- LinearNNSearch() - 类的构造器 weka.core.neighboursearch.LinearNNSearch
-
Constructor.
- LinearNNSearch(Instances) - 类的构造器 weka.core.neighboursearch.LinearNNSearch
-
Constructor that uses the supplied set of instances.
- LinearRegression - weka.classifiers.functions中的类
-
Class for using linear regression for prediction.
- LinearRegression - weka.core.matrix中的类
-
Class for performing (ridged) linear regression using Tikhonov regularization.
- LinearRegression() - 类的构造器 weka.classifiers.functions.LinearRegression
- LinearRegression(Matrix, Matrix, double) - 类的构造器 weka.core.matrix.LinearRegression
-
Performs a (ridged) linear regression.
- LinearRegression(Matrix, Matrix, double[], double) - 类的构造器 weka.core.matrix.LinearRegression
-
Performs a weighted (ridged) linear regression.
- LinearUnit - weka.classifiers.functions.neural中的类
-
This can be used by the neuralnode to perform all it's computations (as a Linear unit).
- LinearUnit() - 类的构造器 weka.classifiers.functions.neural.LinearUnit
- lineWrap(String, int) - 类中的静态方法 weka.core.Utils
-
Implements simple line breaking.
- Link2(Object[], double) - 类的构造器 weka.attributeSelection.BestFirst.Link2
-
Constructor
- Link2(Object[], double) - 类的构造器 weka.attributeSelection.LFSMethods.Link2
- LinkedList2(int) - 类的构造器 weka.attributeSelection.BestFirst.LinkedList2
- LinkedList2(int) - 类的构造器 weka.attributeSelection.LFSMethods.LinkedList2
- LinkedListInverseIterator() - 类的构造器 weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
- LinkedListIterator() - 类的构造器 weka.associations.tertius.SimpleLinkedList.LinkedListIterator
- linkTypeTipText() - 类中的方法 weka.clusterers.HierarchicalClusterer
- LINUX_BROWSERS - 类中的静态变量 weka.gui.BrowserHelper
-
Linux/Unix binaries to look for
- listCapabilities(Capabilities) - 类中的静态方法 weka.gui.PropertySheetPanel
-
returns a comma-separated list of all the capabilities.
- listOptions() - 类中的方法 weka.associations.Apriori
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.associations.CheckAssociator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.associations.FilteredAssociator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.associations.FPGrowth
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns an enumeration of the available options.
- listOptions() - 类中的方法 weka.associations.PredictiveApriori
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.associations.SingleAssociatorEnhancer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.associations.Tertius
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.BestFirst
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.Ranker
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.RankSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns an enumeration describing all the available options
- listOptions() - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.fixed.FromFile
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.global.TAN
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.local.TAN
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.net.search.SearchAlgorithm
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.bayes.WAODE
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.BVDecompose
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.CheckClassifier
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.CheckSource
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.Classifier
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns an enumeration of all the available options..
- listOptions() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.SMO
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.CheckKernel
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.IteratedSingleClassifierEnhancer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.Bagging
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.Dagging
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.GridSearch
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.Stacking
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.meta.Vote
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns an enumeration of all the available options..
- listOptions() - 类中的方法 weka.classifiers.mi.MDD
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.mi.MIBoost
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.mi.MIDD
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.mi.MILR
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.mi.MINND
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.misc.VFI
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.MultipleClassifiersCombiner
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.RandomizableClassifier
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.RandomizableMultipleClassifiersCombiner
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.RandomizableSingleClassifierEnhancer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns an enumeration describing the available options Valid options are:
- listOptions() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.rules.DTNB
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.rules.JRip
-
Returns an enumeration describing the available options Valid options are:
- listOptions() - 类中的方法 weka.classifiers.rules.NNge
-
Returns an enumeration of all the available options..
- listOptions() - 类中的方法 weka.classifiers.rules.OneR
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.classifiers.rules.PART
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns an enumeration describing the available options Valid options are:
- listOptions() - 类中的方法 weka.classifiers.SingleClassifierEnhancer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.trees.FT
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.trees.J48
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.trees.LMT
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.trees.M5P
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.classifiers.trees.RandomTree
-
Lists the command-line options for this classifier.
- listOptions() - 类中的方法 weka.classifiers.trees.REPTree
-
Lists the command-line options for this classifier.
- listOptions() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.CheckClusterer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.CLOPE
- listOptions() - 类中的方法 weka.clusterers.Cobweb
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.DBSCAN
-
Returns an enumeration of all the available options..
- listOptions() - 类中的方法 weka.clusterers.EM
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.FarthestFirst
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.FilteredClusterer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.HierarchicalClusterer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.clusterers.OPTICS
-
Returns an enumeration of all the available options.
- listOptions() - 类中的方法 weka.clusterers.RandomizableClusterer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.RandomizableDensityBasedClusterer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.RandomizableSingleClustererEnhancer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.sIB
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.SingleClustererEnhancer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.clusterers.XMeans
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.Check
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.CheckGOE
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.CheckOptionHandler
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.CheckScheme
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.converters.ArffSaver
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.converters.C45Saver
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.converters.CSVLoader
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.converters.DatabaseLoader
-
Lists the available options
- listOptions() - 类中的方法 weka.core.converters.DatabaseSaver
-
Lists the available options.
- listOptions() - 类中的方法 weka.core.converters.LibSVMSaver
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.converters.SVMLightSaver
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Lists the available options
- listOptions() - 类中的方法 weka.core.converters.XRFFSaver
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.FindWithCapabilities
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.Javadoc
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.ListOptions
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.balltrees.BallSplitter
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.NormalizableDistance
-
Returns an enumeration describing the available options.
- listOptions() - 接口中的方法 weka.core.OptionHandler
-
Returns an enumeration of all the available options..
- listOptions() - 类中的方法 weka.core.OptionHandlerJavadoc
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.stemmers.SnowballStemmer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.TechnicalInformationHandlerJavadoc
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.TestInstances
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.core.tokenizers.CharacterDelimitedTokenizer
-
Returns an enumeration of all the available options..
- listOptions() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Returns an enumeration of all the available options..
- listOptions() - 类中的方法 weka.core.tokenizers.Tokenizer
-
Returns an enumeration of all the available options..
- listOptions() - 类中的方法 weka.datagenerators.ClassificationGenerator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.ClusterDefinition
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.ClusterGenerator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.DataGenerator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.datagenerators.RegressionGenerator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.estimators.CheckEstimator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.estimators.Estimator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.CSVResultListener
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.experiment.Experiment
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.InstanceQuery
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.PairedTTester
-
Lists options understood by this object.
- listOptions() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Returns an enumeration describing the available options..
- listOptions() - 类中的方法 weka.filters.CheckSource
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.MultiFilter
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.SimpleFilter
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Gets an enumeration describing the available options..
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.PotentialClassIgnorer
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Returns an enumeration describing the available options
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Gets an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Gets an enumeration describing the available options..
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Gets an enumeration describing the available options..
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Returns an enumeration describing the available options.
- listOptions() - 类中的方法 weka.gui.Main
-
Gets an enumeration describing the available options.
- ListOptions - weka.core中的类
-
Lists the options of an OptionHandler
- ListOptions() - 类的构造器 weka.core.ListOptions
- ListSelectorDialog - weka.gui中的类
-
A dialog to present the user with a list of items, that the user can make a selection from, or cancel the selection.
- ListSelectorDialog(Frame, JList) - 类的构造器 weka.gui.ListSelectorDialog
-
Create the list selection dialog.
- listStemmers() - 类中的静态方法 weka.core.stemmers.SnowballStemmer
-
returns an enumeration over all currently stored stemmer names.
- Literal - weka.associations.tertius中的类
- Literal(Predicate, int, int) - 类的构造器 weka.associations.tertius.Literal
- LiteralSet - weka.associations.tertius中的类
-
Class representing a set of literals, being either the body or the head of a rule.
- LiteralSet() - 类的构造器 weka.associations.tertius.LiteralSet
-
Constructor for a set that does not store its counter-instances.
- LiteralSet(Instances) - 类的构造器 weka.associations.tertius.LiteralSet
-
Constructor initializing the set of counter-instances to all the instances.
- LMT - weka.classifiers.trees中的类
-
Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.
- LMT() - 类的构造器 weka.classifiers.trees.LMT
-
Creates an instance of LMT with standard options
- LMTNode - weka.classifiers.trees.lmt中的类
-
Class for logistic model tree structure.
- LMTNode(ModelSelection, int, boolean, boolean, int, double, boolean) - 类的构造器 weka.classifiers.trees.lmt.LMTNode
-
Constructor for logistic model tree node.
- lnFactorial(double) - 类中的静态方法 weka.core.SpecialFunctions
-
Returns natural logarithm of factorial using gamma function.
- lnFactorial(int) - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Fast computation of ln(n!) for non-negative ints negative ints are passed on to the general gamma-function based version in weka.core.SpecialFunctions if the current n value is higher than any previous one, the cache is extended and filled to cover it the common case is reduced to a simple array lookup
- lnGamma(double) - 类中的静态方法 weka.core.Statistics
-
Returns natural logarithm of gamma function.
- LNormTipText() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Returns the tip text for this property
- lnsrch(double[], double[], double[], double, boolean[], double[][], Optimization.DynamicIntArray) - 类中的方法 weka.core.Optimization
-
Find a new point x in the direction p from a point xold at which the value of the function has decreased sufficiently, the positive definiteness of B matrix (approximation of the inverse of the Hessian) is preserved and no bound constraints are violated.
- load(InputStream) - 类中的方法 weka.core.ProtectedProperties
-
Overrides a method to prevent the properties from being modified.
- load(String) - 类中的方法 weka.gui.beans.FlowRunner
-
Load a serialized KnowledgeFlow (either binary or xml)
- loadBinary(String) - 类中的方法 weka.gui.beans.FlowRunner
-
Load a binary serialized KnowledgeFlow
- Loader - weka.gui.beans中的类
-
Loads data sets using weka.core.converter classes
- Loader - weka.gui中的类
-
This class is for loading resources from a JAR archive.
- Loader - weka.core.converters中的接口
-
Interface to something that can load Instances from an input source in some format.
- Loader() - 类的构造器 weka.gui.beans.Loader
- Loader(String) - 类的构造器 weka.gui.Loader
-
initializes the object
- LOADER_DIALOG - 类中的静态变量 weka.gui.ConverterFileChooser
-
the loader dialog
- LoaderBeanInfo - weka.gui.beans中的类
-
Bean info class for the loader bean
- LoaderBeanInfo() - 类的构造器 weka.gui.beans.LoaderBeanInfo
- LoaderCustomizer - weka.gui.beans中的类
-
GUI Customizer for the loader bean
- LoaderCustomizer() - 类的构造器 weka.gui.beans.LoaderCustomizer
- loadFile() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
loads the specified file into the table
- loadFile(String) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
loads the specified file
- loadFromFile(String) - 类中的静态方法 weka.core.Debug
-
deserializes the content of the file and returns it, null if an error occurred.
- loadIcons(String, String) - 类中的方法 weka.gui.beans.BeanVisual
-
Loads static and animated versions of a beans icons.
- loadInitialLayout(String) - 类中的方法 weka.gui.beans.KnowledgeFlowApp
-
Loads the specified file at input Added by Zerbetto
- loadModel() - 类中的方法 weka.gui.beans.Classifier
- loadModel() - 类中的方法 weka.gui.beans.Clusterer
- loadProperties() - 类中的静态方法 weka.gui.beans.KnowledgeFlowApp
-
Loads KnowledgeFlow properties and any plugins (adds jars to the classpath)
- loadXML(String) - 类中的方法 weka.gui.beans.FlowRunner
-
Load an XML serialized KnowledgeFlow
- localDistributionForInstance(Instance, LBR.Indexes) - 类中的方法 weka.classifiers.lazy.LBR
-
Calculates the class membership probabilities.
- locallyPredictiveTipText() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Returns the tip text for this property
- localNaiveBayes(LBR.Indexes) - 类中的方法 weka.classifiers.lazy.LBR
-
Class for building and using a simple Naive Bayes classifier.
- LocalScoreSearchAlgorithm - weka.classifiers.bayes.net.search.local中的类
-
The ScoreBasedSearchAlgorithm class supports Bayes net structure search algorithms that are based on maximizing scores (as opposed to for example conditional independence based search algorithms).
- LocalScoreSearchAlgorithm() - 类的构造器 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
default constructor
- LocalScoreSearchAlgorithm(BayesNet, Instances) - 类的构造器 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
constructor
- locateIndex(int) - 类中的方法 weka.core.SparseInstance
-
Locates the greatest index that is not greater than the given index.
- LOCATION - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
A location associated with the entry, such as the city in which a conference took place.
- log(String) - 类中的方法 weka.core.Debug
-
prints the given message with level INFO
- log(String) - 类中的方法 weka.core.Debug.SimpleLog
-
logs the given message to the file
- log(Level, String) - 类中的方法 weka.core.Debug
-
prints the given message with the specified level and an empty sourceclass
- log(Level, String) - 类中的方法 weka.core.Debug.Log
-
logs the given message
- log(Level, String, String) - 类中的方法 weka.core.Debug
-
prints the given message with the specified level
- log(Level, String, String) - 类中的方法 weka.core.Debug.Log
-
prints the given message with the specified level
- log(Level, String, String, String) - 类中的方法 weka.core.Debug
-
prints the given message with the specified level
- log(Level, String, String, String) - 类中的方法 weka.core.Debug.Log
-
prints the given message with the specified level
- log(Logger.Level, String) - 类中的静态方法 weka.core.logging.Logger
-
Logs the given message under the given level.
- log(Logger.Level, Throwable) - 类中的静态方法 weka.core.logging.Logger
-
Logs the given message under the given level.
- Log() - 类的构造器 weka.core.Debug.Log
-
default constructor, uses only stdout
- Log(String) - 类的构造器 weka.core.Debug.Log
-
creates a logger that logs into the specified file, if null then only stdout is used.
- Log(String, int, int) - 类的构造器 weka.core.Debug.Log
-
creates a logger that logs into the specified file, if null then only stdout is used.
- LOG - 接口中的静态变量 weka.core.mathematicalexpression.sym
- LOG - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- log2 - 类中的静态变量 weka.core.Utils
-
The natural logarithm of 2.
- log2(double) - 类中的静态方法 weka.core.Utils
-
Returns the logarithm of a for base 2.
- LOG2 - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- log2Binomial(double, double) - 类中的静态方法 weka.core.SpecialFunctions
-
Returns base 2 logarithm of binomial coefficient using gamma function.
- log2Multinomial(double, double[]) - 类中的静态方法 weka.core.SpecialFunctions
-
Returns base 2 logarithm of multinomial using gamma function.
- log2MultipleHypergeometric(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.
- logbinomialCoefficient(int, int) - 类中的静态方法 weka.associations.PriorEstimation
-
Method that calculates the base 2 logarithm of a binomial coefficient
- logDensityForInstance(Instance) - 类中的方法 weka.clusterers.AbstractDensityBasedClusterer
-
Computes the density for a given instance.
- logDensityForInstance(Instance) - 接口中的方法 weka.clusterers.DensityBasedClusterer
-
Computes the density for a given instance.
- logDensityPerClusterForInstance(Instance) - 类中的方法 weka.clusterers.AbstractDensityBasedClusterer
-
Computes the log of the conditional density (per cluster) for a given instance.
- logDensityPerClusterForInstance(Instance) - 接口中的方法 weka.clusterers.DensityBasedClusterer
-
Computes the log of the conditional density (per cluster) for a given instance.
- logDensityPerClusterForInstance(Instance) - 类中的方法 weka.clusterers.EM
-
Computes the log of the conditional density (per cluster) for a given instance.
- logDensityPerClusterForInstance(Instance) - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Computes the log of the conditional density (per cluster) for a given instance.
- logFileTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- logFunc(double) - 类中的方法 weka.classifiers.trees.j48.EntropyBasedSplitCrit
-
Help method for computing entropy.
- Logger - weka.core.logging中的类
-
Abstract superclass for all loggers.
- Logger - weka.gui中的接口
-
Interface for objects that display log (permanent historical) and status (transient) messages.
- Logger() - 类的构造器 weka.core.logging.Logger
-
Initializes the logger.
- Logger.Level - weka.core.logging中的Enum Class
-
The logging level.
- Logistic - weka.classifiers.functions中的类
-
Class for building and using a multinomial logistic regression model with a ridge estimator.
There are some modifications, however, compared to the paper of leCessie and van Houwelingen(1992):
If there are k classes for n instances with m attributes, the parameter matrix B to be calculated will be an m*(k-1) matrix.
The probability for class j with the exception of the last class is
Pj(Xi) = exp(XiBj)/((sum[j=1..(k-1)]exp(Xi*Bj))+1)
The last class has probability
1-(sum[j=1..(k-1)]Pj(Xi))
= 1/((sum[j=1..(k-1)]exp(Xi*Bj))+1)
The (negative) multinomial log-likelihood is thus:
L = -sum[i=1..n]{
sum[j=1..(k-1)](Yij * ln(Pj(Xi)))
+(1 - (sum[j=1..(k-1)]Yij))
* ln(1 - sum[j=1..(k-1)]Pj(Xi))
} + ridge * (B^2)
In order to find the matrix B for which L is minimised, a Quasi-Newton Method is used to search for the optimized values of the m*(k-1) variables. - Logistic() - 类的构造器 weka.classifiers.functions.Logistic
- LogisticBase - weka.classifiers.trees.lmt中的类
-
Base/helper class for building logistic regression models with the LogitBoost algorithm.
- LogisticBase() - 类的构造器 weka.classifiers.trees.lmt.LogisticBase
-
Constructor that creates LogisticBase object with standard options.
- LogisticBase(int, boolean, boolean) - 类的构造器 weka.classifiers.trees.lmt.LogisticBase
-
Constructor to create LogisticBase object.
- logisticLinkFunction(double) - 类中的静态方法 weka.classifiers.bayes.BayesianLogisticRegression
-
This method computes the values for the logistic link function.
- LogitBoost - weka.classifiers.meta中的类
-
Class for performing additive logistic regression.
- LogitBoost() - 类的构造器 weka.classifiers.meta.LogitBoost
-
Constructor.
- logJointDensitiesForInstance(Instance) - 类中的方法 weka.clusterers.AbstractDensityBasedClusterer
-
Returns the logs of the joint densities for a given instance.
- logJointDensitiesForInstance(Instance) - 接口中的方法 weka.clusterers.DensityBasedClusterer
-
Returns the logs of the joint densities for a given instance.
- LogLikelihood - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Log-likelihood values to be used to choose the best hyperparameter.
- logMessage(String) - 类中的方法 weka.gui.beans.FlowRunner.SimpleLogger
- logMessage(String) - 类中的方法 weka.gui.beans.LogPanel
-
Sends the supplied message to the log area.
- logMessage(String) - 接口中的方法 weka.gui.Logger
-
Sends the supplied message to the log area.
- logMessage(String) - 类中的方法 weka.gui.LogPanel
-
Sends the supplied message to the log area.
- logMessage(String) - 类中的方法 weka.gui.SysErrLog
-
Sends the supplied message to the log area.
- LogPanel - weka.gui.beans中的类
-
Class for displaying a status area (made up of a variable number of lines) and a log area.
- LogPanel - weka.gui中的类
-
This panel allows log and status messages to be posted.
- LogPanel() - 类的构造器 weka.gui.beans.LogPanel
- LogPanel() - 类的构造器 weka.gui.LogPanel
-
Creates the log panel with no task monitor and the log always visible.
- LogPanel(WekaTaskMonitor) - 类的构造器 weka.gui.LogPanel
-
Creates the log panel with a task monitor, where the log is hidden.
- LogPanel(WekaTaskMonitor, boolean) - 类的构造器 weka.gui.LogPanel
-
Creates the log panel, possibly with task monitor, where the log is optionally hidden.
- LogPanel(WekaTaskMonitor, boolean, boolean, boolean) - 类的构造器 weka.gui.LogPanel
-
Creates the log panel, possibly with task monitor, where the either the log is optionally hidden or the status (having both hidden is not allowed).
- logPSI - 类中的静态变量 weka.core.matrix.Maths
-
The constant - log( sqrt(2 pi) )
- logs2probs(double[]) - 类中的静态方法 weka.core.Utils
-
Converts an array containing the natural logarithms of probabilities stored in a vector back into probabilities.
- logScore(int) - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
logScore returns the log of the quality of a network (e.g.
- logScore(int, int) - 类中的方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Gets the log score contribution of this distribution
- logScore(int, int) - 接口中的方法 weka.classifiers.bayes.net.search.local.Scoreable
-
Returns log-score
- logSystemInfo() - 类中的方法 weka.core.Debug.Log
-
a convenience method for dumping the current system info in the log file
- logSystemInfo() - 类中的方法 weka.core.Debug.SimpleLog
-
a convenience method for dumping the current system info in the log file
- LogWindow - weka.gui中的类
-
Frame that shows the output from stdout and stderr.
- LogWindow() - 类的构造器 weka.gui.LogWindow
-
creates the frame
- LogWriter - weka.gui.beans中的接口
-
Interface to be implemented by classes that should be able to write their own output to the Weka logger.
- LONG - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for LONG used for reading experiment results.
- LookAndFeel - weka.gui中的类
-
A little helper class for setting the Look and Feel of the user interface.
- LookAndFeel() - 类的构造器 weka.gui.LookAndFeel
- lookupCacheSizeTipText() - 类中的方法 weka.attributeSelection.BestFirst
-
Returns the tip text for this property
- lookupCacheSizeTipText() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the tip text for this property
- lookupCacheSizeTipText() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the tip text for this property
- LOSS_STRING - 类中的变量 weka.experiment.ResultMatrix
-
loss string
- lossFunctionTipText() - 类中的方法 weka.classifiers.functions.SPegasos
-
Returns the tip text for this property
- lossTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- LovinsStemmer - weka.core.stemmers中的类
-
A stemmer based on the Lovins stemmer, described here:
Julie Beth Lovins (1968). - LovinsStemmer() - 类的构造器 weka.core.stemmers.LovinsStemmer
- LOW_MEMORY_MINIMUM - 类中的静态变量 weka.core.Memory
- lowerBoundMinSupportTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- lowerBoundMinSupportTipText() - 类中的方法 weka.associations.FPGrowth
-
Returns the tip text for this property
- lowerCaseTokensTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- lowerNumericBoundIsOpen() - 类中的方法 weka.core.Attribute
-
Returns whether the lower numeric bound of the attribute is open.
- lowerSizeTipText() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns the tip text for this property
- LPAREN - 接口中的静态变量 weka.core.mathematicalexpression.sym
- LPAREN - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- lsqr(PaceMatrix, IntVector, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
QR transformation for a least squares problem
A x = b
implicitly both A and b are transformed. - lsqrSelection(PaceMatrix, IntVector, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
QR transformation for a least squares problem
A x = b
implicitly both A and b are transformed. - LT - 接口中的静态变量 weka.core.mathematicalexpression.sym
- LT - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- lu() - 类中的方法 weka.core.matrix.Matrix
-
LU Decomposition
- LUDecomposition - weka.core.matrix中的类
-
LU Decomposition.
- LUDecomposition(Matrix) - 类的构造器 weka.core.matrix.LUDecomposition
-
LU Decomposition
- LUDecomposition() - 类中的方法 weka.core.Matrix
-
已过时。Performs a LUDecomposition on the matrix.
- LWL - weka.classifiers.lazy中的类
-
Locally weighted learning.
- LWL() - 类的构造器 weka.classifiers.lazy.LWL
-
Constructor.
M
- m_ADNodes - 类中的变量 weka.classifiers.bayes.net.VaryNode
-
list of ADNode children
- m_alpha - 类中的变量 weka.classifiers.functions.supportVector.RegOptimizer
-
alpha and alpha* arrays containing weights for solving dual problem
- m_alpha - 类中的变量 weka.classifiers.trees.lmt.LMTNode
-
Alpha-value (for pruning) at the node
- m_alphaStar - 类中的变量 weka.classifiers.functions.supportVector.RegOptimizer
- m_alwaysDisplayPointsOfThisSize - 类中的变量 weka.gui.visualize.PlotData2D
-
If the shape size of a point equals this size then always plot it (i.e.
- m_AttIndexes - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
the array attribute indexes
- M_AVERAGE - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- m_children - 类中的变量 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
- m_ClassIndex - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
the Class Index for the data set
- m_col - 类中的变量 weka.gui.treevisualizer.NamedColor
-
The actual color object
- m_cols - 类中的变量 weka.gui.treevisualizer.Colors
-
The array with all the colors input
- m_CoordCount - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The number of coordinates looked at for the current/last query.
- m_CurrDebugFlag - 类中的变量 weka.clusterers.XMeans
-
Flag: I'm debugging.
- m_customColour - 类中的变量 weka.gui.visualize.PlotData2D
- m_defaultExpression - 类中的静态变量 weka.filters.unsupervised.attribute.MathExpression
-
The default modification expression
- M_DELETE - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
-
Missing value handling mode
- m_displayAllPoints - 类中的变量 weka.gui.visualize.PlotData2D
-
Display all points (ie.
- m_Distributions - 类中的变量 weka.classifiers.bayes.BayesNet
-
The attribute estimators containing CPTs.
- m_End - 类中的变量 weka.core.neighboursearch.balltrees.BallNode
-
The end index of the portion of the master index array, which stores indices of the instances/points the node contains.
- m_End - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
The end index of the portion of the master index array, which stores indices of the instances/points the node contains.
- m_experimentFinished - 类中的变量 weka.experiment.RemoteExperimentEvent
-
True if a remote experiment has finished
- m_Filter - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Filter interface used to point to weka.filters.unsupervised.attribute.Normalize object
- m_indexVal - 类中的变量 weka.gui.visualize.AttributePanelEvent
-
The index for the new attribute
- m_iNode - 类中的变量 weka.classifiers.bayes.net.VaryNode
-
index of the node varied
- m_Instances - 类中的变量 weka.classifiers.bayes.BayesNet
-
The dataset header for the purposes of printing out a semi-intelligible model
- m_Instances - 类中的变量 weka.classifiers.bayes.net.ADNode
-
list of Instance children (either m_Instances or m_VaryNodes is instantiated)
- m_InstIndexes - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
the array instance indexes
- m_Left - 类中的变量 weka.core.neighboursearch.balltrees.BallNode
-
The left child of the node.
- m_Left - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
left subtree; contains instances with smaller or equal to split value.
- m_logMessage - 类中的变量 weka.experiment.RemoteExperimentEvent
-
A log type message
- m_MaxC - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The min and max coordinates(attributes) looked at per query.
- M_MAXDIFF - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- m_MaxP - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The min and max data points looked for a query by the NNS algorithm.
- m_messageString - 类中的变量 weka.experiment.RemoteExperimentEvent
-
The message
- m_MinC - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The min and max coordinates(attributes) looked at per query.
- m_MinP - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The min and max data points looked for a query by the NNS algorithm.
- m_name - 类中的变量 weka.gui.treevisualizer.NamedColor
-
The name of the color
- m_nCount - 类中的变量 weka.classifiers.bayes.net.ADNode
-
count
- m_nMCV - 类中的变量 weka.classifiers.bayes.net.VaryNode
-
most common value
- m_nNodes - 类中的变量 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
-
nodes of the Bayes net in this junction node
- m_NodeNumber - 类中的变量 weka.core.neighboursearch.balltrees.BallNode
-
The node number/id.
- m_NodeNumber - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
node number (only for debug).
- m_NodeRanges - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
lowest and highest value and width (= high - low) for each dimension.
- m_NodesRectBounds - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
The lo and high bounds of the hyper rectangle described by the node.
- M_NORMAL - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- m_nStartNode - 类中的变量 weka.classifiers.bayes.net.ADNode
-
first node in VaryNode array
- m_NumAttsSet - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
the number of attributes "in use" or set to a the original value (true or false)
- m_numIncorrectModel - 类中的变量 weka.classifiers.trees.lmt.LMTNode
-
Weighted number of training examples currently misclassified by the logistic model at the node
- m_numIncorrectTree - 类中的变量 weka.classifiers.trees.lmt.LMTNode
-
Weighted number of training examples currently misclassified by the subtree rooted at the node
- m_NumInstances - 类中的变量 weka.core.neighboursearch.balltrees.BallNode
-
The number of instances/points in the node.
- m_NumInstsSet - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
the number of instances "in use" or set to a the original value (true or false)
- m_numParameters - 类中的变量 weka.classifiers.trees.m5.RuleNode
-
the number of paramters in the chosen model for this node---either the subtree model or the linear model.
- m_NumSeqAttsSet - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
the number of sequential attributes "in use" or set to a the original value (true or false)
- m_NumSeqInstsSet - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
the number of sequential instances "in use" or set to a the original value (true or false)
- m_OutputFormat - 类中的变量 weka.core.Debug.Clock
-
the format of the output
- m_outputTypes - 类中的变量 weka.core.Debug.DBO
-
range of outputtyp
- m_PointCount - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The number of data points looked at for the current/last query.
- m_Right - 类中的变量 weka.core.neighboursearch.balltrees.BallNode
-
The right child of the node.
- m_Right - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
right subtree; contains instances with larger than split value.
- m_root - 类中的变量 weka.classifiers.bayes.net.MarginCalculator
- m_seed - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
seed for randomizing the instances before CV
- m_SequentialAttIndexes - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
an array of attribute indexes that are set to either true or false
- m_SequentialInstIndexes - 类中的变量 weka.classifiers.lazy.LBR.Indexes
-
the array of instance indexes that are set to a either true or false
- m_SplitAttrib - 类中的变量 weka.core.neighboursearch.balltrees.BallNode
-
The attribute that splits this node (not always used).
- m_SplitDim - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
attribute to split on.
- m_SplitVal - 类中的变量 weka.core.neighboursearch.balltrees.BallNode
-
The value of m_SpiltAttrib that splits this node (not always used).
- m_SplitValue - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
value to split on.
- m_Start - 类中的变量 weka.core.neighboursearch.balltrees.BallNode
-
The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.
- m_Start - 类中的变量 weka.core.neighboursearch.kdtrees.KDTreeNode
-
The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.
- m_statusMessage - 类中的变量 weka.experiment.RemoteExperimentEvent
-
A status type message
- m_SumC - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The sum of coordinates/attributes looked at for all the queries.
- m_SumP - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The sum of data points looked at for all the queries.
- m_SumSqC - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The squared sum of coordinates/attributes looked at for all the queries.
- m_SumSqP - 类中的变量 weka.core.neighboursearch.PerformanceStats
-
The squared sum of data points looked at for all the queries.
- m_useCustomColour - 类中的变量 weka.gui.visualize.PlotData2D
-
Custom colour for this plot
- m_UseWordwrap - 类中的变量 weka.gui.LogWindow
-
whether the JTextPane has wordwrap or not
- m_VaryNodes - 类中的变量 weka.classifiers.bayes.net.ADNode
-
list of VaryNode children
- m_verboseOn - 类中的变量 weka.core.Debug.DBO
-
enables/disables output of debug information
- m_xChange - 类中的变量 weka.gui.visualize.AttributePanelEvent
-
True if the x selection changed
- m_yChange - 类中的变量 weka.gui.visualize.AttributePanelEvent
-
True if the y selection changed
- M5Base - weka.classifiers.trees.m5中的类
-
M5Base.
- M5Base() - 类的构造器 weka.classifiers.trees.m5.M5Base
-
Constructor
- M5P - weka.classifiers.trees中的类
-
M5Base.
- M5P() - 类的构造器 weka.classifiers.trees.M5P
-
Creates a new
M5P
instance. - M5Rules - weka.classifiers.rules中的类
-
Generates a decision list for regression problems using separate-and-conquer.
- M5Rules() - 类的构造器 weka.classifiers.rules.M5Rules
-
Constructor
- MahalanobisEstimator - weka.estimators中的类
-
Simple probability estimator that places a single normal distribution over the observed values.
- MahalanobisEstimator(Matrix, double, double) - 类的构造器 weka.estimators.MahalanobisEstimator
-
Constructor
- main(String[]) - 类中的静态方法 weka.associations.Apriori
-
Main method.
- main(String[]) - 类中的静态方法 weka.associations.AssociatorEvaluation
-
A test method for this class.
- main(String[]) - 类中的静态方法 weka.associations.CheckAssociator
-
Test method for this class
- main(String[]) - 类中的静态方法 weka.associations.FilteredAssociator
-
Main method for running this class.
- main(String[]) - 类中的静态方法 weka.associations.FPGrowth
-
Main method.
- main(String[]) - 类中的静态方法 weka.associations.GeneralizedSequentialPatterns
-
Main method.
- main(String[]) - 类中的静态方法 weka.associations.PredictiveApriori
-
Main method.
- main(String[]) - 类中的静态方法 weka.associations.Tertius
-
Main method.
- main(String[]) - 类中的静态方法 weka.attributeSelection.AttributeSelection
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.CfsSubsetEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.CheckAttributeSelection
-
Test method for this class
- main(String[]) - 类中的静态方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Main method.
- main(String[]) - 类中的静态方法 weka.attributeSelection.ClassifierSubsetEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.ConsistencySubsetEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.CostSensitiveAttributeEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.CostSensitiveSubsetEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.FilteredAttributeEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.FilteredSubsetEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.GainRatioAttributeEval
-
Main method.
- main(String[]) - 类中的静态方法 weka.attributeSelection.InfoGainAttributeEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.LatentSemanticAnalysis
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.attributeSelection.OneRAttributeEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.PrincipalComponents
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.attributeSelection.ReliefFAttributeEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.SVMAttributeEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.attributeSelection.WrapperSubsetEval
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.AODE
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.AODEsr
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.BayesNet
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.DMNBtext
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.HNB
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.NaiveBayes
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.NaiveBayesSimple
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.NaiveBayesUpdateable
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.ADNode
-
for testing only
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.BayesNetGenerator
-
Main method
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.BIFReader
-
Loads the file specified as first parameter and prints it to stdout.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.EditableBayesNet
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.GUI
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.MarginCalculator
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
-
for testing the class
- main(String[]) - 类中的静态方法 weka.classifiers.bayes.WAODE
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.BVDecompose
-
Test method for this class
- main(String[]) - 类中的静态方法 weka.classifiers.BVDecomposeSegCVSub
-
Test method for this class
- main(String[]) - 类中的静态方法 weka.classifiers.CheckClassifier
-
Test method for this class
- main(String[]) - 类中的静态方法 weka.classifiers.CheckSource
-
Executes the tests, use "-h" to list the commandline options.
- main(String[]) - 类中的静态方法 weka.classifiers.evaluation.CostCurve
-
Tests the CostCurve generation from the command line.
- main(String[]) - 类中的静态方法 weka.classifiers.Evaluation
-
A test method for this class.
- main(String[]) - 类中的静态方法 weka.classifiers.evaluation.MarginCurve
-
Tests the MarginCurve generation from the command line.
- main(String[]) - 类中的静态方法 weka.classifiers.evaluation.ThresholdCurve
-
Tests the ThresholdCurve generation from the command line.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.GaussianProcesses
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.IsotonicRegression
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.functions.LeastMedSq
-
generate a Linear regression predictor for testing
- main(String[]) - 类中的静态方法 weka.classifiers.functions.LibLINEAR
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.LibSVM
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.LinearRegression
-
Generates a linear regression function predictor.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.Logistic
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.MultilayerPerceptron
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.pace.ChisqMixture
-
Method to test this class
- main(String[]) - 类中的静态方法 weka.classifiers.functions.pace.DiscreteFunction
- main(String[]) - 类中的静态方法 weka.classifiers.functions.pace.NormalMixture
-
Method to test this class
- main(String[]) - 类中的静态方法 weka.classifiers.functions.pace.PaceMatrix
-
for testing only
- main(String[]) - 类中的静态方法 weka.classifiers.functions.PaceRegression
-
Generates a linear regression function predictor.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.PLSClassifier
-
Main method for running this classifier from commandline.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.RBFNetwork
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.SimpleLinearRegression
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.functions.SimpleLogistic
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.functions.SMO
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.SMOreg
-
Main method for running this classifier.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.SPegasos
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.supportVector.CheckKernel
-
Test method for this class
- main(String[]) - 类中的静态方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
A test method for this class.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.VotedPerceptron
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.functions.Winnow
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.lazy.IB1
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.lazy.IBk
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.lazy.KStar
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.lazy.LBR
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.lazy.LWL
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.AdaBoostM1
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.AdditiveRegression
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.Bagging
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.ClassificationViaClustering
-
Runs the classifier with the given options
- main(String[]) - 类中的静态方法 weka.classifiers.meta.ClassificationViaRegression
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.CostSensitiveClassifier
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.CVParameterSelection
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.Dagging
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.Decorate
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.END
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.FilteredClassifier
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.Grading
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.GridSearch
-
Main method for running this classifier from commandline.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.LogitBoost
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.MetaCost
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.MultiBoostAB
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.MultiClassClassifier
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.MultiScheme
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.nestedDichotomies.ND
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.OrdinalClassClassifier
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Main method for this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.RandomCommittee
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.RandomSubSpace
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.RegressionByDiscretization
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.RotationForest
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.Stacking
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.StackingC
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.ThresholdSelector
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.meta.Vote
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.CitationKNN
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MDD
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MIBoost
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MIDD
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MIEMDD
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MILR
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MINND
-
Main method for testing.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MIOptimalBall
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MISMO
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MISVM
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.MIWrapper
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.mi.SimpleMI
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.misc.HyperPipes
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.misc.SerializedClassifier
-
Runs the classifier with the given options
- main(String[]) - 类中的静态方法 weka.classifiers.misc.VFI
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.rules.ConjunctiveRule
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.rules.DecisionTable
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.rules.DTNB
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.rules.JRip
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.rules.M5Rules
-
Main method by which this class can be tested
- main(String[]) - 类中的静态方法 weka.classifiers.rules.NNge
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.rules.OneR
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.rules.PART
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.rules.Prism
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.rules.Ridor
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.rules.ZeroR
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.ADTree
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.BFTree
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.DecisionStump
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.FT
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.trees.Id3
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.J48
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.trees.J48graft
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.trees.LADTree
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.LMT
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.trees.M5P
-
Main method by which this class can be tested
- main(String[]) - 类中的静态方法 weka.classifiers.trees.NBTree
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.classifiers.trees.RandomForest
-
Main method for this class.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.RandomTree
-
Main method for this class.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.REPTree
-
Main method for this class.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.SimpleCart
-
Main method.
- main(String[]) - 类中的静态方法 weka.classifiers.trees.UserClassifier
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.clusterers.CheckClusterer
-
Test method for this class
- main(String[]) - 类中的静态方法 weka.clusterers.CLOPE
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.clusterers.ClusterEvaluation
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.clusterers.Cobweb
-
Main method.
- main(String[]) - 类中的静态方法 weka.clusterers.DBSCAN
-
Main Method for testing DBSCAN
- main(String[]) - 类中的静态方法 weka.clusterers.EM
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.clusterers.FarthestFirst
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.clusterers.FilteredClusterer
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.OPTICS_Visualizer
-
Displays the GUI.
- main(String[]) - 类中的静态方法 weka.clusterers.HierarchicalClusterer
- main(String[]) - 类中的静态方法 weka.clusterers.MakeDensityBasedClusterer
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.clusterers.OPTICS
-
Main Method for testing OPTICS
- main(String[]) - 类中的静态方法 weka.clusterers.sIB
- main(String[]) - 类中的静态方法 weka.clusterers.SimpleKMeans
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.clusterers.XMeans
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.AlgVector
-
Main method for testing this class, can take an ARFF file as first argument.
- main(String[]) - 类中的静态方法 weka.core.AllJavadoc
-
Parses the given commandline parameters and generates the Javadoc.
- main(String[]) - 类中的静态方法 weka.core.Attribute
-
Simple main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.BinarySparseInstance
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.Capabilities
-
loads the given dataset and prints the Capabilities necessary to process it.
- main(String[]) - 类中的静态方法 weka.core.CheckGOE
-
Main method for using the CheckGOE.
- main(String[]) - 类中的静态方法 weka.core.CheckOptionHandler
-
Main method for using the CheckOptionHandler.
- main(String[]) - 类中的静态方法 weka.core.ClassDiscovery
-
Possible calls: weka.core.ClassDiscovery <packages>
Prints all the packages in the current classpath weka.core.ClassDiscovery <classname> <packagename(s)>
Prints the classes it found. - main(String[]) - 类中的静态方法 weka.core.ContingencyTables
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.converters.ArffLoader
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.ArffSaver
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.C45Loader
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.converters.C45Saver
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSink
-
for testing only - takes a data file as input and a data file for the output.
- main(String[]) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSource
-
for testing only - takes a data file as input.
- main(String[]) - 类中的静态方法 weka.core.converters.CSVLoader
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.CSVSaver
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.DatabaseLoader
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.DatabaseSaver
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.LibSVMLoader
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.LibSVMSaver
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.SerializedInstancesLoader
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.SerializedInstancesSaver
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.SVMLightLoader
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.SVMLightSaver
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.TextDirectoryLoader
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.XRFFLoader
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.converters.XRFFSaver
-
Main method.
- main(String[]) - 类中的静态方法 weka.core.Copyright
-
Only for testing
- main(String[]) - 类中的静态方法 weka.core.Environment
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.FindWithCapabilities
-
Executes the location of classes with parameters from the commandline.
- main(String[]) - 类中的静态方法 weka.core.GlobalInfoJavadoc
-
Parses the given commandline parameters and generates the Javadoc.
- main(String[]) - 类中的静态方法 weka.core.Instance
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.InstanceComparator
-
for testing only.
- main(String[]) - 类中的静态方法 weka.core.Instances
-
Main method for this class.
- main(String[]) - 类中的静态方法 weka.core.Jython
-
If no arguments are given, it just prints the presence of the Jython classes, otherwise it expects a Jython filename to execute.
- main(String[]) - 类中的静态方法 weka.core.ListOptions
-
runs the javadoc producer with the given commandline options
- main(String[]) - 类中的静态方法 weka.core.mathematicalexpression.Parser
-
Runs the parser from commandline.
- main(String[]) - 类中的静态方法 weka.core.matrix.DoubleVector
- main(String[]) - 类中的静态方法 weka.core.matrix.IntVector
-
Tests the IntVector class
- main(String[]) - 类中的静态方法 weka.core.Matrix
-
已过时。Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.matrix.Matrix
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.Memory
-
prints only some statistics
- main(String[]) - 类中的静态方法 weka.core.neighboursearch.CoverTree
-
Method for testing the class from command line.
- main(String[]) - 类中的静态方法 weka.core.OptionHandlerJavadoc
-
Parses the given commandline parameters and generates the Javadoc.
- main(String[]) - 类中的静态方法 weka.core.pmml.Constant
- main(String[]) - 类中的静态方法 weka.core.pmml.PMMLFactory
- main(String[]) - 类中的静态方法 weka.core.PropertyPath
-
for testing only
- main(String[]) - 类中的静态方法 weka.core.Queue
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.RandomVariates
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.Range
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.RevisionUtils
-
For testing only.
- main(String[]) - 类中的静态方法 weka.core.SerializationHelper
-
Outputs information about a class on the commandline, takes class name as arguments.
- main(String[]) - 类中的静态方法 weka.core.SingleIndex
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.SparseInstance
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.SpecialFunctions
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.Statistics
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.stemmers.IteratedLovinsStemmer
-
Runs the stemmer with the given options
- main(String[]) - 类中的静态方法 weka.core.stemmers.LovinsStemmer
-
Runs the stemmer with the given options
- main(String[]) - 类中的静态方法 weka.core.stemmers.NullStemmer
-
Runs the stemmer with the given options
- main(String[]) - 类中的静态方法 weka.core.stemmers.SnowballStemmer
-
Runs the stemmer with the given options.
- main(String[]) - 类中的静态方法 weka.core.Stopwords
-
Accepts the following parameter:
- main(String[]) - 类中的静态方法 weka.core.SystemInfo
-
for printing the system info to stdout.
- main(String[]) - 类中的静态方法 weka.core.TechnicalInformation
-
Prints some examples of technical informations if there are no commandline options given.
- main(String[]) - 类中的静态方法 weka.core.TechnicalInformationHandlerJavadoc
-
Parses the given commandline parameters and generates the Javadoc.
- main(String[]) - 类中的静态方法 weka.core.TestInstances
-
for running the class from commandline, prints the generated data to stdout
- main(String[]) - 类中的静态方法 weka.core.tokenizers.AlphabeticTokenizer
-
Runs the tokenizer with the given options and strings to tokenize.
- main(String[]) - 类中的静态方法 weka.core.tokenizers.NGramTokenizer
-
Runs the tokenizer with the given options and strings to tokenize.
- main(String[]) - 类中的静态方法 weka.core.tokenizers.WordTokenizer
-
Runs the tokenizer with the given options and strings to tokenize.
- main(String[]) - 类中的静态方法 weka.core.Trie
-
Only for testing (prints the built Trie).
- main(String[]) - 类中的静态方法 weka.core.Utils
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.core.Version
-
only for testing
- main(String[]) - 类中的静态方法 weka.core.xml.SerialUIDChanger
-
exchanges an old UID for a new one.
- main(String[]) - 类中的静态方法 weka.core.xml.XMLDocument
-
for testing only.
- main(String[]) - 类中的静态方法 weka.core.xml.XMLInstances
-
takes an XML document as first argument and then outputs the Instances statistics
- main(String[]) - 类中的静态方法 weka.core.xml.XMLOptions
-
for testing only.
- main(String[]) - 类中的静态方法 weka.core.xml.XMLSerialization
-
for testing only.
- main(String[]) - 类中的静态方法 weka.datagenerators.classifiers.classification.Agrawal
-
Main method for executing this class.
- main(String[]) - 类中的静态方法 weka.datagenerators.classifiers.classification.BayesNet
-
Main method for executing this class.
- main(String[]) - 类中的静态方法 weka.datagenerators.classifiers.classification.LED24
-
Main method for executing this class.
- main(String[]) - 类中的静态方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Main method for executing this class.
- main(String[]) - 类中的静态方法 weka.datagenerators.classifiers.classification.RDG1
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.datagenerators.classifiers.regression.Expression
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.datagenerators.clusterers.BIRCHCluster
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.datagenerators.clusterers.SubspaceCluster
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.CheckEstimator
-
Test method for this class
- main(String[]) - 类中的静态方法 weka.estimators.DDConditionalEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.DiscreteEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.DKConditionalEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.DNConditionalEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.KDConditionalEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.KernelEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.KKConditionalEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.MahalanobisEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.NDConditionalEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.NNConditionalEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.NormalEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.estimators.PoissonEstimator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.experiment.CrossValidationResultProducer
-
Quick test of timestamp
- main(String[]) - 类中的静态方法 weka.experiment.Experiment
-
Configures/Runs the Experiment from the command line.
- main(String[]) - 类中的静态方法 weka.experiment.InstanceQuery
-
Test the class from the command line.
- main(String[]) - 类中的静态方法 weka.experiment.OutputZipper
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.experiment.PairedCorrectedTTester
-
Test the class from the command line.
- main(String[]) - 类中的静态方法 weka.experiment.PairedStats
-
Tests the paired stats object from the command line.
- main(String[]) - 类中的静态方法 weka.experiment.PairedTTester
-
Test the class from the command line.
- main(String[]) - 类中的静态方法 weka.experiment.RemoteEngine
-
Main method.
- main(String[]) - 类中的静态方法 weka.experiment.RemoteExperiment
-
Configures/Runs the Experiment from the command line.
- main(String[]) - 类中的静态方法 weka.experiment.ResultMatrixCSV
-
for testing only
- main(String[]) - 类中的静态方法 weka.experiment.ResultMatrixGnuPlot
-
for testing only
- main(String[]) - 类中的静态方法 weka.experiment.ResultMatrixHTML
-
for testing only
- main(String[]) - 类中的静态方法 weka.experiment.ResultMatrixLatex
-
for testing only
- main(String[]) - 类中的静态方法 weka.experiment.ResultMatrixPlainText
-
for testing only
- main(String[]) - 类中的静态方法 weka.experiment.ResultMatrixSignificance
-
for testing only
- main(String[]) - 类中的静态方法 weka.experiment.Stats
-
Tests the paired stats object from the command line.
- main(String[]) - 类中的静态方法 weka.experiment.xml.XMLExperiment
-
for testing only.
- main(String[]) - 类中的静态方法 weka.filters.AllFilter
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.CheckSource
-
Executes the tests, use "-h" to list the commandline options.
- main(String[]) - 类中的静态方法 weka.filters.Filter
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.MultiFilter
-
Main method for executing this class.
- main(String[]) - 类中的静态方法 weka.filters.supervised.attribute.AddClassification
-
runs the filter with the given arguments.
- main(String[]) - 类中的静态方法 weka.filters.supervised.attribute.AttributeSelection
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.supervised.attribute.ClassOrder
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.supervised.attribute.Discretize
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.supervised.attribute.NominalToBinary
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.supervised.attribute.PLSFilter
-
runs the filter with the given arguments.
- main(String[]) - 类中的静态方法 weka.filters.supervised.instance.Resample
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.supervised.instance.SMOTE
-
Main method for running this filter.
- main(String[]) - 类中的静态方法 weka.filters.supervised.instance.SpreadSubsample
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Add
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.AddCluster
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.AddExpression
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.AddID
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.AddNoise
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.AddValues
-
Main method for testing and running this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Center
-
Main method for running this filter.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.ClassAssigner
-
Main method for executing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Copy
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Discretize
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.FirstOrder
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.KernelFilter
-
runs the filter with the given arguments
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.MathExpression
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Main method for running this filter.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.NominalToString
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Normalize
-
Main method for running this filter.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Runs the filter from commandline, use "-h" to see all options.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.NumericToBinary
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Runs the filter with the given parameters.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.NumericTransform
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Obfuscate
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Main method for executing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Main method for running this filter.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Main method for running this filter.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.RandomProjection
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.RandomSubset
-
Runs the filter with the given parameters.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.RELAGGS
-
runs the filter with the given arguments
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Remove
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.RemoveType
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Reorder
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.ReplaceMissingValues
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Standardize
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.StringToNominal
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.SwapValues
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.TimeSeriesDelta
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.TimeSeriesTranslate
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.attribute.Wavelet
-
runs the filter with the given arguments
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.NonSparseToSparse
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.Normalize
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.Randomize
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.RemoveFolds
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.RemovePercentage
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.RemoveRange
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.Resample
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.ReservoirSample
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.SparseToNonSparse
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Main method for running this filter.
- main(String[]) - 类中的静态方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Runs the parser from commandline.
- main(String[]) - 类中的静态方法 weka.gui.arffviewer.ArffViewer
-
shows the frame and it tries to load all the arff files that were provided as arguments.
- main(String[]) - 类中的静态方法 weka.gui.AttributeListPanel
-
Tests the attribute list panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.AttributeSelectionPanel
-
Tests the attribute selection panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.AttributeSummaryPanel
-
Tests out the attribute summary panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.AttributeVisualizationPanel
-
Main method to test this class from command line
- main(String[]) - 类中的静态方法 weka.gui.beans.AttributeSummarizer
- main(String[]) - 类中的静态方法 weka.gui.beans.CostBenefitAnalysis
- main(String[]) - 类中的静态方法 weka.gui.beans.DataVisualizer
- main(String[]) - 类中的静态方法 weka.gui.beans.FlowRunner
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.gui.beans.KnowledgeFlow
-
Shows the splash screen, launches the application and then disposes the splash screen.
- main(String[]) - 类中的静态方法 weka.gui.beans.KnowledgeFlowApp
-
Main method.
- main(String[]) - 类中的静态方法 weka.gui.beans.Loader
- main(String[]) - 类中的静态方法 weka.gui.beans.LogPanel
-
Main method to test this class.
- main(String[]) - 类中的静态方法 weka.gui.beans.ModelPerformanceChart
- main(String[]) - 类中的静态方法 weka.gui.beans.Saver
-
The main method for testing
- main(String[]) - 类中的静态方法 weka.gui.beans.ScatterPlotMatrix
- main(String[]) - 类中的静态方法 weka.gui.beans.StripChart
-
Tests out the StripChart from the command line
- main(String[]) - 类中的静态方法 weka.gui.beans.TextViewer
- main(String[]) - 类中的静态方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.gui.boundaryvisualizer.BoundaryPanelDistributed
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.gui.ConverterFileChooser
-
For testing the file chooser
- main(String[]) - 类中的静态方法 weka.gui.DatabaseConnectionDialog
-
for testing only
- main(String[]) - 类中的静态方法 weka.gui.experiment.AlgorithmListPanel
-
Tests out the algorithm list panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.experiment.DatasetListPanel
-
Tests out the dataset list panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.experiment.DistributeExperimentPanel
-
Tests out the panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.experiment.Experimenter
-
Tests out the experiment environment.
- main(String[]) - 类中的静态方法 weka.gui.experiment.ExperimenterDefaults
-
only for testing - prints the content of the props file
- main(String[]) - 类中的静态方法 weka.gui.experiment.GeneratorPropertyIteratorPanel
-
Tests out the panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.experiment.HostListPanel
-
Tests out the host list panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.experiment.OutputFormatDialog
-
for testing only.
- main(String[]) - 类中的静态方法 weka.gui.experiment.ResultsPanel
-
Tests out the results panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.experiment.RunNumberPanel
-
Tests out the panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.experiment.RunPanel
-
Tests out the run panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.experiment.SetupPanel
-
Tests out the experiment setup from the command line.
- main(String[]) - 类中的静态方法 weka.gui.explorer.AssociationsPanel
-
Tests out the Associator panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.explorer.AttributeSelectionPanel
-
Tests out the attribute selection panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.explorer.ClassifierPanel
-
Tests out the classifier panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.explorer.ClustererPanel
-
Tests out the clusterer panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.explorer.Explorer
-
Tests out the explorer environment.
- main(String[]) - 类中的静态方法 weka.gui.explorer.ExplorerDefaults
-
only for testing - prints the content of the props file.
- main(String[]) - 类中的静态方法 weka.gui.explorer.PreprocessPanel
-
Tests out the instance-preprocessing panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.explorer.VisualizePanel
-
Tests out the visualize panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.GenericArrayEditor
-
Tests out the array editor from the command line.
- main(String[]) - 类中的静态方法 weka.gui.GenericObjectEditor
-
Tests out the Object editor from the command line.
- main(String[]) - 类中的静态方法 weka.gui.GenericPropertiesCreator
-
for generating props file: no parameter: see default constructor 1 parameter (i.e., filename): see default constructor + setOutputFilename(String) 2 parameters (i.e, filenames): see constructor with String argument + setOutputFilename(String)
- main(String[]) - 类中的静态方法 weka.gui.graphvisualizer.GraphVisualizer
-
Main method to load a text file with the description of a graph from the command line
- main(String[]) - 类中的静态方法 weka.gui.GUIChooser
-
Tests out the GUIChooser environment.
- main(String[]) - 类中的静态方法 weka.gui.HierarchyPropertyParser
-
Tests out the parser.
- main(String[]) - 类中的静态方法 weka.gui.hierarchyvisualizer.HierarchyVisualizer
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.gui.InstancesSummaryPanel
-
Tests out the instance summary panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.ListSelectorDialog
-
Tests out the list selector from the command line.
- main(String[]) - 类中的静态方法 weka.gui.LogPanel
-
Tests out the log panel from the command line.
- main(String[]) - 类中的静态方法 weka.gui.LogWindow
-
for testing only
- main(String[]) - 类中的静态方法 weka.gui.LookAndFeel
-
prints all the available LnFs to stdout
- main(String[]) - 类中的静态方法 weka.gui.Main
-
starts the application.
- main(String[]) - 类中的静态方法 weka.gui.PropertySelectorDialog
-
Tests out the property selector from the command line.
- main(String[]) - 类中的静态方法 weka.gui.ResultHistoryPanel
-
Tests out the result history from the command line.
- main(String[]) - 类中的静态方法 weka.gui.SaveBuffer
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.gui.SelectedTagEditor
-
Tests out the selectedtag editor from the command line.
- main(String[]) - 类中的静态方法 weka.gui.SimpleCLI
-
Method to start up the simple cli
- main(String[]) - 类中的静态方法 weka.gui.SimpleCLIPanel
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.gui.sql.SqlViewer
-
starts the SQL-Viewer interface.
- main(String[]) - 类中的静态方法 weka.gui.sql.SqlViewerDialog
-
for testing only
- main(String[]) - 类中的静态方法 weka.gui.treevisualizer.TreeVisualizer
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.gui.visualize.AttributePanel
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.gui.visualize.BMPWriter
-
for testing only
- main(String[]) - 类中的静态方法 weka.gui.visualize.ClassPanel
-
Main method for testing this class.
- main(String[]) - 类中的静态方法 weka.gui.visualize.JPEGWriter
-
for testing only.
- main(String[]) - 类中的静态方法 weka.gui.visualize.LegendPanel
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.gui.visualize.MatrixPanel
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.gui.visualize.Plot2D
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.gui.visualize.PNGWriter
-
for testing only
- main(String[]) - 类中的静态方法 weka.gui.visualize.PostscriptWriter
-
for testing only
- main(String[]) - 类中的静态方法 weka.gui.visualize.ThresholdVisualizePanel
-
Starts the ThresholdVisualizationPanel with parameters from the command line.
- main(String[]) - 类中的静态方法 weka.gui.visualize.VisualizePanel
-
Main method for testing this class
- main(String[]) - 类中的静态方法 weka.gui.WekaTaskMonitor
-
Main method for testing this class
- Main - weka.gui中的类
-
Menu-based GUI for Weka, replacement for the GUIChooser.
- Main() - 类的构造器 weka.gui.Main
-
default constructor.
- Main.BackgroundDesktopPane - weka.gui中的类
-
DesktopPane with background image.
- Main.ChildFrameMDI - weka.gui中的类
-
Specialized JInternalFrame class.
- Main.ChildFrameSDI - weka.gui中的类
-
Specialized JFrame class.
- MainMenuExtension - weka.gui中的接口
-
Classes implementing this interface will be displayed in the "Extensions" menu in the main GUI of Weka.
- MAJOR - 类中的静态变量 weka.core.Version
-
the major version
- MAJORITY_VOTING_RULE - 类中的静态变量 weka.classifiers.meta.Vote
-
combination rule: Majority Voting (only nominal classes)
- majorityClassTipText() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns the tip text for this property
- makeADTree(int, FastVector, Instances) - 类中的静态方法 weka.classifiers.bayes.net.ADNode
-
create sub tree
- makeADTree(Instances) - 类中的静态方法 weka.classifiers.bayes.net.ADNode
-
create AD tree from set of instances
- makeBinaryTipText() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns the tip text for this property
- makeBinaryTipText() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the tip text for this property
- makeCopies(Associator, int) - 类中的静态方法 weka.associations.AbstractAssociator
-
Creates copies of the current associator.
- makeCopies(ASEvaluation, int) - 类中的静态方法 weka.attributeSelection.ASEvaluation
-
Creates copies of the current evaluator.
- makeCopies(ASSearch, int) - 类中的静态方法 weka.attributeSelection.ASSearch
-
Creates copies of the current search scheme.
- makeCopies(Classifier, int) - 类中的静态方法 weka.classifiers.Classifier
-
Creates a given number of deep copies of the given classifier using serialization.
- makeCopies(Kernel, int) - 类中的静态方法 weka.classifiers.functions.supportVector.Kernel
-
Creates a given number of deep or shallow (if the kernel implements Copyable) copies of the given kernel using serialization.
- makeCopies(Clusterer, int) - 类中的静态方法 weka.clusterers.AbstractClusterer
-
Creates copies of the current clusterer.
- makeCopies(DensityBasedClusterer, int) - 类中的静态方法 weka.clusterers.AbstractDensityBasedClusterer
-
Creates copies of the current clusterer.
- makeCopies(Estimator, int) - 类中的静态方法 weka.estimators.Estimator
-
Creates a given number of deep copies of the given estimator using serialization.
- makeCopies(Filter, int) - 类中的静态方法 weka.filters.Filter
-
Creates a given number of deep copies of the given filter using serialization.
- makeCopy(Object) - 类中的静态方法 weka.gui.GenericArrayEditor
-
Makes a copy of an object using serialization.
- makeCopy(Object) - 类中的静态方法 weka.gui.GenericObjectEditor
-
Makes a copy of an object using serialization.
- makeCopy(Associator) - 类中的静态方法 weka.associations.AbstractAssociator
-
Creates a deep copy of the given associator using serialization.
- makeCopy(Classifier) - 类中的静态方法 weka.classifiers.Classifier
-
Creates a deep copy of the given classifier using serialization.
- makeCopy(Kernel) - 类中的静态方法 weka.classifiers.functions.supportVector.Kernel
-
Creates a shallow copy of the kernel (if it implements Copyable) otherwise a deep copy using serialization.
- makeCopy(Clusterer) - 类中的静态方法 weka.clusterers.AbstractClusterer
-
Creates a deep copy of the given clusterer using serialization.
- makeCopy(Estimator) - 类中的静态方法 weka.estimators.Estimator
-
Creates a deep copy of the given estimator using serialization.
- makeCopy(Filter) - 类中的静态方法 weka.filters.Filter
-
Creates a deep copy of the given filter using serialization.
- makeData(DataGenerator, String[]) - 类中的静态方法 weka.datagenerators.DataGenerator
-
Calls the data generator.
- MakeDecList - weka.classifiers.rules.part中的类
-
Class for handling a decision list.
- MakeDecList(ModelSelection, double, int) - 类的构造器 weka.classifiers.rules.part.MakeDecList
-
Constructor for dec list pruned using C4.5 pruning.
- MakeDecList(ModelSelection, int) - 类的构造器 weka.classifiers.rules.part.MakeDecList
-
Constructor for unpruned dec list.
- MakeDecList(ModelSelection, int, int, int) - 类的构造器 weka.classifiers.rules.part.MakeDecList
-
Constructor for dec list pruned using hold-out pruning.
- MakeDensityBasedClusterer - weka.clusterers中的类
-
Class for wrapping a Clusterer to make it return a distribution and density.
- MakeDensityBasedClusterer() - 类的构造器 weka.clusterers.MakeDensityBasedClusterer
-
Default constructor.
- MakeDensityBasedClusterer(Clusterer) - 类的构造器 weka.clusterers.MakeDensityBasedClusterer
-
Contructs a MakeDensityBasedClusterer wrapping a given Clusterer.
- makeDistribution(double, int) - 类中的静态方法 weka.classifiers.evaluation.NominalPrediction
-
Convert a single prediction into a probability distribution with all zero probabilities except the predicted value which has probability 1.0.
- MakeIndicator - weka.filters.unsupervised.attribute中的类
-
A filter that creates a new dataset with a boolean attribute replacing a nominal attribute.
- MakeIndicator() - 类的构造器 weka.filters.unsupervised.attribute.MakeIndicator
-
Constructor
- makeUniformDistribution(int) - 类中的静态方法 weka.classifiers.evaluation.NominalPrediction
-
Creates a uniform probability distribution -- where each of the possible classes is assigned equal probability.
- makeVaryNode(int, FastVector, Instances) - 类中的静态方法 weka.classifiers.bayes.net.ADNode
-
create sub tree
- makeWeighted(CostMatrix) - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Makes a copy of this ConfusionMatrix after applying the supplied CostMatrix to the cells.
- ManhattanDataObject - weka.clusterers.forOPTICSAndDBScan.DataObjects中的类
-
ManhattanDataObject.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 19, 2004
Time: 5:50:22 PM
$ Revision 1.4 $ - ManhattanDataObject(Instance, String, Database) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Constructs a new DataObject.
- ManhattanDistance - weka.core中的类
-
Implements the Manhattan distance (or Taxicab geometry).
- ManhattanDistance() - 类的构造器 weka.core.ManhattanDistance
-
Constructs an Manhattan Distance object, Instances must be still set.
- ManhattanDistance(Instances) - 类的构造器 weka.core.ManhattanDistance
-
Constructs an Manhattan Distance object and automatically initializes the ranges.
- MANUAL - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
Technical documentation.
- manualThresholdValueTipText() - 类中的方法 weka.classifiers.meta.ThresholdSelector
- map(String, String) - 类中的方法 weka.core.matrix.DoubleVector
-
Applies a method to the vector
- mapClasses(int, int, int[][], int[], double[], double[], int) - 类中的静态方法 weka.clusterers.ClusterEvaluation
-
Finds the minimum error mapping of classes to clusters.
- MappingInfo - weka.core.pmml中的类
-
Class that maintains the mapping between incoming data set structure and that of the mining schema.
- MappingInfo(Instances, MiningSchema, Logger) - 类的构造器 weka.core.pmml.MappingInfo
- mapToMiningSchema(Instances) - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Map mining schema to incoming instances.
- margin() - 类中的方法 weka.classifiers.evaluation.NominalPrediction
-
Calculates the prediction margin.
- MarginCalculator - weka.classifiers.bayes.net中的类
- MarginCalculator() - 类的构造器 weka.classifiers.bayes.net.MarginCalculator
- MarginCalculator.JunctionTreeNode - weka.classifiers.bayes.net中的类
- MarginCalculator.JunctionTreeSeparator - weka.classifiers.bayes.net中的类
- MarginCurve - weka.classifiers.evaluation中的类
-
Generates points illustrating the prediction margin.
- MarginCurve() - 类的构造器 weka.classifiers.evaluation.MarginCurve
- markovBlanketClassifierTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
- markovBlanketClassifierTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
- maskKeyword(String) - 类中的方法 weka.experiment.DatabaseUtils
-
If the given string is a keyword, then the mask character will be appended and returned.
- MASTERSTHESIS - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
A Master's thesis.
- Matchable - weka.core中的接口
-
Interface to something that can be matched with tree matching algorithms.
- matchMissingValuesTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the tip text for this property
- MathematicalExpression - weka.core中的类
-
Class for evaluating a string adhering the following grammar:
- MathematicalExpression() - 类的构造器 weka.core.MathematicalExpression
- MathExpression - weka.filters.unsupervised.attribute中的类
-
Modify numeric attributes according to a given expression
- MathExpression() - 类的构造器 weka.filters.unsupervised.attribute.MathExpression
-
Constructor
- Maths - weka.core.matrix中的类
-
Utility class.
- Maths() - 类的构造器 weka.core.matrix.Maths
- matrix() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns matrix with distribution of class values.
- Matrix - weka.core中的类
-
已过时。Use
weka.core.matrix.Matrix
instead - only for backwards compatibility. - Matrix - weka.core.matrix中的类
-
Jama = Java Matrix class.
- Matrix(double[][]) - 类的构造器 weka.core.Matrix
-
已过时。Constructs a matrix using a given array.
- Matrix(double[][]) - 类的构造器 weka.core.matrix.Matrix
-
Construct a matrix from a 2-D array.
- Matrix(double[][], int, int) - 类的构造器 weka.core.matrix.Matrix
-
Construct a matrix quickly without checking arguments.
- Matrix(double[], int) - 类的构造器 weka.core.matrix.Matrix
-
Construct a matrix from a one-dimensional packed array
- Matrix(int, int) - 类的构造器 weka.core.Matrix
-
已过时。Constructs a matrix and initializes it with default values.
- Matrix(int, int) - 类的构造器 weka.core.matrix.Matrix
-
Construct an m-by-n matrix of zeros.
- Matrix(int, int, double) - 类的构造器 weka.core.matrix.Matrix
-
Construct an m-by-n constant matrix.
- Matrix(Reader) - 类的构造器 weka.core.Matrix
-
已过时。Reads a matrix from a reader.
- Matrix(Reader) - 类的构造器 weka.core.matrix.Matrix
-
Reads a matrix from a reader.
- MATRIX_ON_DEMAND - 类中的静态变量 weka.attributeSelection.CostSensitiveASEvaluation
-
load cost matrix on demand
- MATRIX_ON_DEMAND - 类中的静态变量 weka.classifiers.meta.CostSensitiveClassifier
-
load cost matrix on demand
- MATRIX_ON_DEMAND - 类中的静态变量 weka.classifiers.meta.MetaCost
-
load cost matrix on demand
- MATRIX_SUPPLIED - 类中的静态变量 weka.attributeSelection.CostSensitiveASEvaluation
-
use explicit cost matrix
- MATRIX_SUPPLIED - 类中的静态变量 weka.classifiers.meta.CostSensitiveClassifier
-
use explicit cost matrix
- MATRIX_SUPPLIED - 类中的静态变量 weka.classifiers.meta.MetaCost
-
use explicit matrix
- MatrixPanel - weka.gui.visualize中的类
-
This panel displays a plot matrix of the user selected attributes of a given data set.
- MatrixPanel() - 类的构造器 weka.gui.visualize.MatrixPanel
-
Constructor
- max - 类中的变量 weka.experiment.Stats
-
The maximum value seen, or Double.NaN if no values seen
- max() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the maximum value of all elements
- MAX - 类中的静态变量 weka.core.neighboursearch.KDTree
-
The index of MAX value in attributes' range array.
- MAX - 类中的静态变量 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Index of max value in an array of attributes' range.
- MAX_DIGITS - 类中的静态变量 weka.core.converters.SVMLightSaver
-
the number of digits after the decimal point.
- MAX_ROWS - 类中的静态变量 weka.gui.sql.QueryPanel
-
the name for the max rows in the history.
- MAX_RULE - 类中的静态变量 weka.classifiers.meta.Vote
-
combination rule: Maximum Probability
- MAX_SHAPES - 类中的静态变量 weka.gui.visualize.Plot2D
- MAX_SLEEP_TIME - 类中的静态变量 weka.core.Memory
- maxAbs() - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns the maximum absolute value of all elements
- maxAbs(int, int, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns the maximum absolute value of some elements of a column, that is, the elements of A[i0:i1][j].
- maxBag() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns index of bag containing maximum number of instances.
- maxBoostingIterationsTipText() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the tip text for this property
- maxCardinalityTipText() - 类中的方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
- maxCardinalityTipText() - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Returns the tip text for this property
- maxChunkSizeTipText() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
- maxClass() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns class with highest frequency over all bags.
- maxClass(int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns class with highest frequency for given bag.
- maxClassForSubsetOfInterest() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- maxCountTipText() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns the tip text for this property
- maxDefaultTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- maxDepthTipText() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns the tip text for this property
- maxDepthTipText() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns the tip text for this property
- maxDepthTipText() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the tip text for this property
- maxGenerationsTipText() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns the tip text for this property
- maxGridExtensionsTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- maxGroupTipText() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns the tip text for this property
- maxImpurity() - 类中的方法 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Returns the impurity of this split
- maxImpurity() - 接口中的方法 weka.classifiers.trees.m5.SplitEvaluate
-
Returns the impurity of this split
- maxImpurity() - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Returns the impurity of this split
- maximumAttributeNamesTipText() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns the tip text for this property
- maximumAttributeNamesTipText() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns the tip text for this property
- maximumAttributeNamesTipText() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Returns the tip text for this property.
- maximumAttributesTipText() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Returns the tip text for this property.
- maximumVariancePercentageAllowedTipText() - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Returns the tip text for this property
- maxIndex(double[]) - 类中的静态方法 weka.core.Utils
-
Returns index of maximum element in a given array of doubles.
- maxIndex(int[]) - 类中的静态方法 weka.core.Utils
-
Returns index of maximum element in a given array of integers.
- maxInstancesInLeafTipText() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the tip text for this property.
- maxInstInLeafTipText() - 类中的方法 weka.core.neighboursearch.KDTree
-
Tip text for this property.
- maxInstNumTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- maxInstNumTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns the tip text for this property
- maxIterations - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Maximum number of iterations
- maxIterationsTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- maxIterationsTipText() - 类中的方法 weka.classifiers.mi.MIBoost
-
Returns the tip text for this property
- maxIterationsTipText() - 类中的方法 weka.classifiers.mi.MISVM
-
Returns the tip text for this property
- maxIterationsTipText() - 类中的方法 weka.clusterers.EM
-
Returns the tip text for this property
- maxIterationsTipText() - 类中的方法 weka.clusterers.sIB
-
Returns the tip text for this property.
- maxIterationsTipText() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns the tip text for this property
- maxIterationsTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- maxIterationsTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns the tip text for this property
- maxItsTipText() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns the tip text for this property
- maxItsTipText() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns the tip text for this property
- maxKMeansForChildrenTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- maxKMeansTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- maxKTipText() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns the tip text for this property
- maxNrOfParentsTipText() - 类中的方法 weka.classifiers.bayes.net.search.SearchAlgorithm
- maxNumberOfItemsTipText() - 类中的方法 weka.associations.FPGrowth
-
Tip text for this property suitable for displaying in the GUI.
- maxNumClustersTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- maxParentSetSize(int) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
reserve memory for parent set
- maxRadiusTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- maxRangeTipText() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Returns the tip text for this property
- maxRelativeLeafRadiusTipText() - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Returns the tip text for this property.
- maxRuleSizeTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the tip text for this property
- maxSubsequenceLengthTipText() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the tip text for this property
- maxThresholdTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- MAYBE_SUPPORT - 类中的静态变量 weka.gui.GenericObjectEditor.GOETreeNode
-
color for "maybe support".
- MDD - weka.classifiers.mi中的类
-
Modified Diverse Density algorithm, with collective assumption.
More information about DD:
Oded Maron (1998). - MDD() - 类的构造器 weka.classifiers.mi.MDD
- MDL - 接口中的静态变量 weka.classifiers.bayes.net.search.local.Scoreable
- mean - 类中的变量 weka.experiment.Stats
-
The mean of values at the last calculateDerived() call
- mean(double[]) - 类中的静态方法 weka.core.Utils
-
Computes the mean for an array of doubles.
- meanAbsoluteError() - 类中的方法 weka.classifiers.Evaluation
-
Returns the mean absolute error.
- meanOrMode(int) - 类中的方法 weka.core.Instances
-
Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.
- meanOrMode(Attribute) - 类中的方法 weka.core.Instances
-
Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.
- meanPriorAbsoluteError() - 类中的方法 weka.classifiers.Evaluation
-
Returns the mean absolute error of the prior.
- meanSquaredTipText() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the tip text for this property.
- meanStddevTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns the tip text for this property
- measureAICScore() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureAttributesUsed() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the fraction of all attributes in the data that are used in the logistic model (in percent).
- measureBayesScore() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureBDeuScore() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureDivergence() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureEntropyScore() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureExamplesCounted() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns the number of examples "counted".
- measureExamplesProcessed() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns the number of examples "counted".
- measureExtraArcs() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureMaxDepth() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the depth of the tree.
- measureMaxDepth() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the depth of the tree.
- measureMaxDepth() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the depth of the tree.
- measureMDLScore() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureMissingArcs() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureNodesExpanded() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns the number of nodes expanded.
- measureNodesExpanded() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns the number of nodes expanded.
- measureNumAttributesSelected() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Additional measure --- number of attributes selected
- measureNumIterations() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
return the number of iterations (base classifiers) completed
- measureNumLeaves() - 类中的方法 weka.classifiers.trees.ADTree
-
Calls measure function for leaf size - the number of prediction nodes.
- measureNumLeaves() - 类中的方法 weka.classifiers.trees.FT
-
Returns the number of leaves in the tree
- measureNumLeaves() - 类中的方法 weka.classifiers.trees.J48
-
Returns the number of leaves
- measureNumLeaves() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the number of leaves
- measureNumLeaves() - 类中的方法 weka.classifiers.trees.LADTree
-
Calls measure function for leaf size.
- measureNumLeaves() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the number of leaves in the tree
- measureNumLeaves() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns the number of leaves
- measureNumLeaves() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the number of leaves.
- measureNumLeaves() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the number of leaves.
- measureNumLeaves() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the number of leaves.
- measureNumPredictionLeaves() - 类中的方法 weka.classifiers.trees.ADTree
-
Calls measure function for prediction leaf size - the number of prediction nodes without children.
- measureNumPredictionLeaves() - 类中的方法 weka.classifiers.trees.LADTree
-
Calls measure function for leaf size.
- measureNumRules() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns the number of rules
- measureNumRules() - 类中的方法 weka.classifiers.rules.PART
-
Return the number of rules.
- measureNumRules() - 类中的方法 weka.classifiers.trees.J48
-
Returns the number of rules (same as number of leaves)
- measureNumRules() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the number of rules (same as number of leaves)
- measureNumRules() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
return the number of rules
- measureNumRules() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns the number of rules (same as number of leaves)
- measureOutOfBagError() - 类中的方法 weka.classifiers.meta.Bagging
-
Gets the out of bag error that was calculated as the classifier was built.
- measureOutOfBagError() - 类中的方法 weka.classifiers.trees.RandomForest
-
Gets the out of bag error that was calculated as the classifier was built.
- measurePercentAttsUsedByDT() - 类中的方法 weka.classifiers.rules.DTNB
-
Returns the number of rules
- measurePerformanceTipText() - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns the tip text for this property.
- measureReversedArcs() - 类中的方法 weka.classifiers.bayes.BayesNet
- measureSelectionTime() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Additional measure --- time taken (milliseconds) to select the attributes
- measureTime() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Additional measure --- time taken (milliseconds) to select attributes and build the classifier
- measureTipText() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Tooltip for this property.
- measureTreeSize() - 类中的方法 weka.classifiers.trees.ADTree
-
Calls measure function for tree size - the total number of nodes.
- measureTreeSize() - 类中的方法 weka.classifiers.trees.BFTree
-
Return number of tree size.
- measureTreeSize() - 类中的方法 weka.classifiers.trees.FT
-
Returns the size of the tree
- measureTreeSize() - 类中的方法 weka.classifiers.trees.J48
-
Returns the size of the tree
- measureTreeSize() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the size of the tree
- measureTreeSize() - 类中的方法 weka.classifiers.trees.LADTree
-
Calls measure function for tree size.
- measureTreeSize() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the size of the tree
- measureTreeSize() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns the size of the tree
- measureTreeSize() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Return number of tree size.
- measureTreeSize() - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the size of the tree.
- measureTreeSize() - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the size of the tree.
- measureTreeSize() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the size of the tree.
- MEDIAN_RULE - 类中的静态变量 weka.classifiers.meta.Vote
-
combination rule: Median Probability (only numeric class)
- MedianDistanceFromArbitraryPoint - weka.core.neighboursearch.balltrees中的类
-
Class that splits a BallNode of a ball tree using Uhlmann's described method.
For information see:
Jeffrey K. - MedianDistanceFromArbitraryPoint() - 类的构造器 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Constructor.
- MedianDistanceFromArbitraryPoint(int[], Instances, EuclideanDistance) - 类的构造器 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Constructor.
- MedianOfWidestDimension - weka.core.neighboursearch.balltrees中的类
-
Class that splits a BallNode of a ball tree based on the median value of the widest dimension of the points in the ball.
- MedianOfWidestDimension - weka.core.neighboursearch.kdtrees中的类
-
The class that splits a KDTree node based on the median value of a dimension in which the node's points have the widest spread.
For more information see also:
Jerome H. - MedianOfWidestDimension() - 类的构造器 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Constructor.
- MedianOfWidestDimension() - 类的构造器 weka.core.neighboursearch.kdtrees.MedianOfWidestDimension
- MedianOfWidestDimension(int[], Instances, EuclideanDistance) - 类的构造器 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Constructor.
- Memory - weka.core中的类
-
A little helper class for Memory management.
- Memory() - 类的构造器 weka.core.Memory
-
initializes the memory management without GUI support
- Memory(boolean) - 类的构造器 weka.core.Memory
-
initializes the memory management
- memoryIsLow() - 类中的方法 weka.core.Memory
-
Checks to see if memory is running low.
- MemoryUsagePanel - weka.gui中的类
-
A panel for displaying the memory usage.
- MemoryUsagePanel() - 类的构造器 weka.gui.MemoryUsagePanel
-
default constructor.
- merge(Element, Element) - 类中的静态方法 weka.associations.gsp.Element
-
Merges two Elements into one.
- merge(SimpleLinkedList, Comparator) - 类中的方法 weka.associations.tertius.SimpleLinkedList
- merge(ADTree) - 类中的方法 weka.classifiers.trees.ADTree
-
Merges two trees together.
- merge(PredictionNode, ADTree) - 类中的方法 weka.classifiers.trees.adtree.PredictionNode
-
Merges this node with another.
- merge(LADTree) - 类中的方法 weka.classifiers.trees.LADTree
-
Merges two trees together.
- mergeAllItemSets(FastVector, int, int) - 类中的静态方法 weka.associations.AprioriItemSet
-
Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
- mergeAllItemSets(FastVector, int, int) - 类中的静态方法 weka.associations.ItemSet
-
Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
- mergeAllItemSets(FastVector, int, int) - 类中的静态方法 weka.associations.LabeledItemSet
-
Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
- mergeInstance(Instance) - 类中的方法 weka.core.BinarySparseInstance
-
Merges this instance with the given instance and returns the result.
- mergeInstance(Instance) - 类中的方法 weka.core.Instance
-
Merges this instance with the given instance and returns the result.
- mergeInstance(Instance) - 类中的方法 weka.core.SparseInstance
-
Merges this instance with the given instance and returns the result.
- mergeInstances(Instances, Instances) - 类中的静态方法 weka.core.Instances
-
Merges two sets of Instances together.
- MergeTwoValues - weka.filters.unsupervised.attribute中的类
-
Merges two values of a nominal attribute into one value.
- MergeTwoValues() - 类的构造器 weka.filters.unsupervised.attribute.MergeTwoValues
- Messages - weka.associations.gsp中的类
-
Messages.
- Messages - weka.associations中的类
-
Messages.
- Messages - weka.gui.arffviewer中的类
-
Messages.
- Messages - weka.gui.beans中的类
-
Messages.
- Messages - weka.gui.beans.xml中的类
-
Messages.
- Messages - weka.gui.boundaryvisualizer中的类
-
Messages.
- Messages - weka.gui.experiment中的类
-
Messages.
- Messages - weka.gui.explorer中的类
-
Messages.
- Messages - weka.gui.graphvisualizer中的类
-
Messages.
- Messages - weka.gui.hierarchyvisualizer中的类
-
Messages.
- Messages - weka.gui中的类
-
Messages.
- Messages - weka.gui.sql.event中的类
-
Messages.
- Messages - weka.gui.sql中的类
-
Messages.
- Messages - weka.gui.streams中的类
-
Messages.
- Messages - weka.gui.treevisualizer中的类
-
Messages.
- Messages - weka.gui.visualize中的类
-
Messages.
- Messages() - 类的构造器 weka.associations.gsp.Messages
- Messages() - 类的构造器 weka.associations.Messages
- Messages() - 类的构造器 weka.gui.arffviewer.Messages
- Messages() - 类的构造器 weka.gui.beans.Messages
- Messages() - 类的构造器 weka.gui.beans.xml.Messages
- Messages() - 类的构造器 weka.gui.boundaryvisualizer.Messages
- Messages() - 类的构造器 weka.gui.experiment.Messages
- Messages() - 类的构造器 weka.gui.explorer.Messages
- Messages() - 类的构造器 weka.gui.graphvisualizer.Messages
- Messages() - 类的构造器 weka.gui.hierarchyvisualizer.Messages
- Messages() - 类的构造器 weka.gui.Messages
- Messages() - 类的构造器 weka.gui.sql.event.Messages
- Messages() - 类的构造器 weka.gui.sql.Messages
- Messages() - 类的构造器 weka.gui.streams.Messages
- Messages() - 类的构造器 weka.gui.treevisualizer.Messages
- Messages() - 类的构造器 weka.gui.visualize.Messages
- MEstimate(double, double, double) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns the probability estimate, using m-estimate
- mestWeightTipText() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns the tip text for this property
- MetaBean - weka.gui.beans中的类
-
A meta bean that encapsulates several other regular beans, useful for grouping large KnowledgeFlows.
- MetaBean() - 类的构造器 weka.gui.beans.MetaBean
- metaClassifierTipText() - 类中的方法 weka.classifiers.meta.Stacking
-
Returns the tip text for this property
- MetaCost - weka.classifiers.meta中的类
-
This metaclassifier makes its base classifier cost-sensitive using the method specified in
Pedro Domingos: MetaCost: A general method for making classifiers cost-sensitive. - MetaCost() - 类的构造器 weka.classifiers.meta.MetaCost
- METHOD_1_AGAINST_1 - 类中的静态变量 weka.classifiers.meta.MultiClassClassifier
-
1-against-1
- METHOD_1_AGAINST_ALL - 类中的静态变量 weka.classifiers.meta.MultiClassClassifier
-
1-against-all
- METHOD_ERROR_EXHAUSTIVE - 类中的静态变量 weka.classifiers.meta.MultiClassClassifier
-
exhaustive correction code
- METHOD_ERROR_RANDOM - 类中的静态变量 weka.classifiers.meta.MultiClassClassifier
-
random correction code
- MethodHandler - weka.core.xml中的类
-
This class handles relationships between display names of properties (or classes) and Methods that are associated with them.
- MethodHandler() - 类的构造器 weka.core.xml.MethodHandler
-
initializes the handler
- methodNameTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Returns the tip text for this property
- methodTipText() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
- methodTipText() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns the tip text for this property
- metricString() - 类中的方法 weka.associations.Apriori
-
Returns the metric string for the chosen metric type
- metricString() - 接口中的方法 weka.associations.CARuleMiner
-
Gets name of the scoring metric used for car mining
- metricString() - 类中的方法 weka.associations.PredictiveApriori
-
Returns the metric string for the chosen metric type.
- metricTypeTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- metricTypeTipText() - 类中的方法 weka.associations.FPGrowth
-
Tip text for this property suitable for displaying in the GUI.
- MexicanHat - weka.datagenerators.classifiers.regression中的类
-
A data generator for the simple 'Mexian Hat' function:
y = sin|x| / |x|
In addition to this simple function, the amplitude can be changed and gaussian noise can be added. - MexicanHat() - 类的构造器 weka.datagenerators.classifiers.regression.MexicanHat
-
initializes the generator
- MIBoost - weka.classifiers.mi中的类
-
MI AdaBoost method, considers the geometric mean of posterior of instances inside a bag (arithmatic mean of log-posterior) and the expectation for a bag is taken inside the loss function.
For more information about Adaboost, see:
Yoav Freund, Robert E. - MIBoost() - 类的构造器 weka.classifiers.mi.MIBoost
- MIDD - weka.classifiers.mi中的类
-
Re-implement the Diverse Density algorithm, changes the testing procedure.
Oded Maron (1998). - MIDD() - 类的构造器 weka.classifiers.mi.MIDD
- MiddleOutConstructor - weka.core.neighboursearch.balltrees中的类
-
The class that builds a BallTree middle out.
For more information see also:
Andrew W. - MiddleOutConstructor() - 类的构造器 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Creates a new instance of MiddleOutConstructor.
- midPoint(double, int) - 类中的方法 weka.associations.PriorEstimation
-
calculates the mid point of an interval
- MidPointOfWidestDimension - weka.core.neighboursearch.kdtrees中的类
-
The class that splits a KDTree node based on the midpoint value of a dimension in which the node's points have the widest spread.
For more information see also:
Andrew Moore (1991). - MidPointOfWidestDimension() - 类的构造器 weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension
- midPoints() - 类中的方法 weka.associations.PriorEstimation
-
split the interval [0,1] into a predefined number of intervals and calculates their mid points
- MIEMDD - weka.classifiers.mi中的类
-
EMDD model builds heavily upon Dietterich's Diverse Density (DD) algorithm.
It is a general framework for MI learning of converting the MI problem to a single-instance setting using EM. - MIEMDD() - 类的构造器 weka.classifiers.mi.MIEMDD
- MILR - weka.classifiers.mi中的类
-
Uses either standard or collective multi-instance assumption, but within linear regression.
- MILR() - 类的构造器 weka.classifiers.mi.MILR
- min - 类中的变量 weka.experiment.Stats
-
The minimum value seen, or Double.NaN if no values seen
- MIN - 类中的静态变量 weka.core.neighboursearch.KDTree
-
The index of MIN value in attributes' range array.
- MIN - 类中的静态变量 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Index of min value in an array of attributes' range.
- MIN_RULE - 类中的静态变量 weka.classifiers.meta.Vote
-
combination rule: Minimum Probability
- minAbs(int, int, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns the minimum absolute value of some elements of a column, that is, the elements of A[i0:i1][j].
- minBagDistance(Instance, Instance) - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Calculate the distance from one data point to a bag
- minBoxRelWidthTipText() - 类中的方法 weka.core.neighboursearch.KDTree
-
Tip text for this property.
- minBucketSizeTipText() - 类中的方法 weka.classifiers.rules.OneR
-
Returns the tip text for this property
- minChangeTipText() - 类中的方法 weka.clusterers.sIB
-
Returns the tip text for this property.
- minChunkSizeTipText() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
- minDataDLIfDeleted(int, double, boolean) - 类中的方法 weka.classifiers.rules.RuleStats
-
Compute the minimal data description length of the ruleset if the rule in the given position is deleted.
The min_data_DL_if_deleted = data_DL_if_deleted - potential - minDataDLIfExists(int, double, boolean) - 类中的方法 weka.classifiers.rules.RuleStats
-
Compute the minimal data description length of the ruleset if the rule in the given position is NOT deleted.
The min_data_DL_if_n_deleted = data_DL_if_n_deleted - potential - minDefaultTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- mineCARs(Instances) - 类中的方法 weka.associations.Apriori
-
Method that mines all class association rules with minimum support and with a minimum confidence.
- mineCARs(Instances) - 接口中的方法 weka.associations.CARuleMiner
-
Method for mining class association rules.
- mineCARs(Instances) - 类中的方法 weka.associations.PredictiveApriori
-
Method that mines the n best class association rules.
- minGroupTipText() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns the tip text for this property
- minimax(Instances, int) - 类中的静态方法 weka.classifiers.mi.SimpleMI
-
Get the minimal and maximal value of a certain attribute in a certain data
- minimaxTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- minimizeExpectedCostTipText() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
- minimizeWindows() - 类中的方法 weka.gui.Main
-
minimizes all windows.
- minimumBucketSizeTipText() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns a string for this option suitable for display in the gui as a tip text
- minIndex(double[]) - 类中的静态方法 weka.core.Utils
-
Returns index of minimum element in a given array of doubles.
- minIndex(int[]) - 类中的静态方法 weka.core.Utils
-
Returns index of minimum element in a given array of integers.
- MiningFieldMetaInfo - weka.core.pmml中的类
-
Class encapsulating information about a MiningField.
- MiningFieldMetaInfo(Element) - 类的构造器 weka.core.pmml.MiningFieldMetaInfo
-
Constructs a new MiningFieldMetaInfo object.
- MiningSchema - weka.core.pmml中的类
-
This class encapsulates the mining schema from a PMML xml file.
- MiningSchema(Element, Instances, TransformationDictionary) - 类的构造器 weka.core.pmml.MiningSchema
-
Constructor for MiningSchema.
- minInstNumTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- minInstNumTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns the tip text for this property
- minMetricTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- minMetricTipText() - 类中的方法 weka.associations.FPGrowth
-
Returns the tip text for this property
- MINND - weka.classifiers.mi中的类
-
Multiple-Instance Nearest Neighbour with Distribution learner.
It uses gradient descent to find the weight for each dimension of each exeamplar from the starting point of 1.0. - MINND() - 类的构造器 weka.classifiers.mi.MINND
- minNoTipText() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns the tip text for this property
- minNoTipText() - 类中的方法 weka.classifiers.rules.JRip
-
Returns the tip text for this property
- minNoTipText() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns the tip text for this property
- minNumClustersTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- minNumInstancesTipText() - 类中的方法 weka.classifiers.trees.FT
-
Returns the tip text for this property
- minNumInstancesTipText() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the tip text for this property
- minNumInstancesTipText() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns the tip text for this property
- minNumObjTipText() - 类中的方法 weka.classifiers.rules.PART
-
Returns the tip text for this property
- minNumObjTipText() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the tip text for this property
- minNumObjTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- minNumObjTipText() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the tip text for this property
- minNumObjTipText() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns the tip text for this property
- minNumTipText() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns the tip text for this property
- minNumTipText() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the tip text for this property
- MINOR - 类中的静态变量 weka.core.Version
-
the minor version
- minPointsTipText() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the tip text for this property
- minPointsTipText() - 类中的方法 weka.clusterers.OPTICS
-
Returns the tip text for this property
- minProb - 类中的变量 weka.classifiers.lazy.kstar.KStarWrapper
-
used/reused to hold the smallest transformation probability
- minRadiusTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- minRangeTipText() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Returns the tip text for this property
- minRuleSizeTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the tip text for this property
- minsAndMaxs(Instances, double[][], int) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns the minsAndMaxs of the index.th subset.
- minStdDevTipText() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns the tip text for this property
- minStdDevTipText() - 类中的方法 weka.clusterers.EM
-
Returns the tip text for this property
- minStdDevTipText() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns the tip text for this property
- minSupportTipText() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns the minimum support option tip text for the Weka GUI.
- minTermFreqTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- minThresholdTipText() - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Returns the tip text for this property
- minus(double) - 类中的方法 weka.core.matrix.DoubleVector
-
Subtracts a value
- minus(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Subtracts another DoubleVector element by element
- minus(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
C = A - B
- MINUS - 接口中的静态变量 weka.core.mathematicalexpression.sym
- MINUS - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- minusEquals(double) - 类中的方法 weka.core.matrix.DoubleVector
-
Subtracts a value in place
- minusEquals(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Subtracts another DoubleVector element by element in place
- minusEquals(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
A = A - B
- minVariancePropTipText() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the tip text for this property
- MIOptimalBall - weka.classifiers.mi中的类
-
This classifier tries to find a suitable ball in the multiple-instance space, with a certain data point in the instance space as a ball center.
- MIOptimalBall() - 类的构造器 weka.classifiers.mi.MIOptimalBall
- MIPolyKernel - weka.classifiers.mi.supportVector中的类
-
The polynomial kernel : K(x, y) = <x, y>^p or K(x, y) = (<x, y>+1)^p
- MIPolyKernel() - 类的构造器 weka.classifiers.mi.supportVector.MIPolyKernel
-
default constructor - does nothing.
- MIPolyKernel(Instances, int, double, boolean) - 类的构造器 weka.classifiers.mi.supportVector.MIPolyKernel
-
Creates a new
MIPolyKernel
instance. - MIRBFKernel - weka.classifiers.mi.supportVector中的类
-
The RBF kernel.
- MIRBFKernel() - 类的构造器 weka.classifiers.mi.supportVector.MIRBFKernel
-
default constructor - does nothing.
- MIRBFKernel(Instances, int, double) - 类的构造器 weka.classifiers.mi.supportVector.MIRBFKernel
-
Constructor.
- MISC - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
Use this type when nothing else fits.
- MISMO - weka.classifiers.mi中的类
-
Implements John Platt's sequential minimal optimization algorithm for training a support vector classifier.
This implementation globally replaces all missing values and transforms nominal attributes into binary ones. - MISMO() - 类的构造器 weka.classifiers.mi.MISMO
- MISSING - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Value.Property
- MISSING_CLASS_VALUES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle missing values in class attribute
- MISSING_SHAPE - 类中的静态变量 weka.gui.visualize.Plot2D
- MISSING_VALUE - 接口中的静态变量 weka.classifiers.evaluation.Prediction
-
Constant representing a missing value.
- MISSING_VALUES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle missing values in attributes
- missingArcs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
Count nr of arcs missing from other network compared to current network Note that an arc is not 'missing' if it is reversed.
- missingCount - 类中的变量 weka.core.AttributeStats
-
The number of missing values
- missingMergeTipText() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Returns the tip text for this property
- missingMergeTipText() - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Returns the tip text for this property
- missingMergeTipText() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Returns the tip text for this property
- missingMergeTipText() - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Returns the tip text for this property
- missingModeTipText() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns the tip text for this property
- missingSeparateTipText() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Returns the tip text for this property
- missingValue() - 类中的静态方法 weka.core.Instance
-
Returns the double that codes "missing".
- missingValuesTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- missingValueTipText() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the tip text for this property.
- MISVM - weka.classifiers.mi中的类
-
Implements Stuart Andrews' mi_SVM (Maximum pattern Margin Formulation of MIL).
- MISVM() - 类的构造器 weka.classifiers.mi.MISVM
- MIWrapper - weka.classifiers.mi中的类
-
A simple Wrapper method for applying standard propositional learners to multi-instance data.
For more information see:
E. - MIWrapper() - 类的构造器 weka.classifiers.mi.MIWrapper
- MixtureDistribution - weka.classifiers.functions.pace中的类
-
Abtract class for manipulating mixture distributions.
- MixtureDistribution() - 类的构造器 weka.classifiers.functions.pace.MixtureDistribution
- MODEL_FILE_EXTENSION - 类中的静态变量 weka.gui.explorer.ClassifierPanel
-
The filename extension that should be used for model files
- MODEL_FILE_EXTENSION - 类中的静态变量 weka.gui.explorer.ClustererPanel
-
The filename extension that should be used for model files
- MODEL_FT - 类中的静态变量 weka.classifiers.trees.FT
-
model types
- MODEL_FTInner - 类中的静态变量 weka.classifiers.trees.FT
- MODEL_FTLeaves - 类中的静态变量 weka.classifiers.trees.FT
- modelBuilt() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
flag to indicate whether the model was built yet
- modelDistributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns the class probabilities for an instance according to the logistic model at the node.
- modelDistributionForInstance(Instance) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns the class probabilities for an instance according to the logistic model at the node.
- modelErrors() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Updates the numIncorrectModel field for all nodes.
- modelErrors() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Updates the numIncorrectModel field for all nodes when subtree (to be pruned) is rooted.
- modelFileTipText() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Returns the tip text for this property
- ModelPerformanceChart - weka.gui.beans中的类
-
Bean that can be used for displaying threshold curves (e.g.
- ModelPerformanceChart() - 类的构造器 weka.gui.beans.ModelPerformanceChart
- ModelPerformanceChartBeanInfo - weka.gui.beans中的类
-
Bean info class for the model performance chart
- ModelPerformanceChartBeanInfo() - 类的构造器 weka.gui.beans.ModelPerformanceChartBeanInfo
- ModelSelection - weka.classifiers.trees.j48中的类
-
Abstract class for model selection criteria.
- ModelSelection() - 类的构造器 weka.classifiers.trees.j48.ModelSelection
- modelsToString() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns a string describing the logistic regression function at the node.
- modelsToString() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns a string describing the logistic regression function at the node.
- modelTypeTipText() - 类中的方法 weka.classifiers.trees.FT
-
Returns the tip text for this property
- modifyHeaderTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns the tip text for this property
- modifyHeaderTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the tip text for this property
- momentumTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- MONTH - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The month in which the work was published or, for an unpublished work, in which it was written.
- moralize(BayesNet) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
-
moralize DAG and calculate adjacency matrix representation for a Bayes Network, effecively converting the directed acyclic graph to an undirected graph.
- mostExplainingColumn(PaceMatrix, IntVector, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns the index of the column that has the largest (squared) response, when each of columns pvt[ks:] is moved to become the ks-th column.
- mouseClicked(MouseEvent) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
Invoked when a mouse button has been pressed and released on a component
- mouseClicked(MouseEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Does nothing.
- mouseDragged(MouseEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Performs intermediate updates to what the user wishes to do.
- mouseEntered(MouseEvent) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
Invoked when the mouse enters a component.
- mouseEntered(MouseEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Does nothing.
- mouseExited(MouseEvent) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
Invoked when the mouse exits a component
- mouseExited(MouseEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Does nothing.
- mouseMoved(MouseEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Does nothing.
- mousePressed(MouseEvent) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
Invoked when a mouse button has been pressed on a component
- mousePressed(MouseEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Determines what action the user wants to perform.
- mouseReleased(MouseEvent) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
Invoked when a mouse button has been released on a component.
- mouseReleased(MouseEvent) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Performs the final stages of what the user wants to perform.
- MOVE_DOWN - 类中的静态变量 weka.gui.JListHelper
-
moves items down
- MOVE_UP - 类中的静态变量 weka.gui.JListHelper
-
moves items up
- moveBottom(JList) - 类中的静态方法 weka.gui.JListHelper
-
moves the selected items to the end
- moveDown(JList) - 类中的静态方法 weka.gui.JListHelper
-
moves the selected item down by 1
- MoveInstanceToBestCluster(Instance) - 类中的方法 weka.clusterers.CLOPE
-
Move instance to best cluster
- moveTop(JList) - 类中的静态方法 weka.gui.JListHelper
-
moves the selected items to the top
- moveUp(JList) - 类中的静态方法 weka.gui.JListHelper
-
moves the selected items up by 1
- MRNUMBER - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The Mathematical Reviews number.
- MultiBoostAB - weka.classifiers.meta中的类
-
Class for boosting a classifier using the MultiBoosting method.
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. - MultiBoostAB() - 类的构造器 weka.classifiers.meta.MultiBoostAB
- MultiClassClassifier - weka.classifiers.meta中的类
-
A metaclassifier for handling multi-class datasets with 2-class classifiers.
- MultiClassClassifier() - 类的构造器 weka.classifiers.meta.MultiClassClassifier
-
Constructor.
- MultiFilter - weka.filters中的类
-
Applies several filters successively.
- MultiFilter() - 类的构造器 weka.filters.MultiFilter
- MultiInstanceCapabilitiesHandler - weka.core中的接口
-
Multi-Instance classifiers can specify an additional Capabilities object for the data in the relational attribute, since the format of multi-instance data is fixed to "bag/NOMINAL,data/RELATIONAL,class".
- MultiInstanceToPropositional - weka.filters.unsupervised.attribute中的类
-
Converts the multi-instance dataset into single instance dataset so that the Nominalize, Standardize and other type of filters or transformation can be applied to these data for the further preprocessing.
Note: the first attribute of the converted dataset is a nominal attribute and refers to the bagId. - MultiInstanceToPropositional() - 类的构造器 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
- MultilayerPerceptron - weka.classifiers.functions中的类
-
A Classifier that uses backpropagation to classify instances.
This network can be built by hand, created by an algorithm or both. - MultilayerPerceptron() - 类的构造器 weka.classifiers.functions.MultilayerPerceptron
-
The constructor.
- MultiNomialBMAEstimator - weka.classifiers.bayes.net.estimate中的类
-
Multinomial BMA Estimator.
- MultiNomialBMAEstimator() - 类的构造器 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
- multinomialWordTipText() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Returns the tip text for this property
- MultipleClassifiersCombiner - weka.classifiers中的类
-
Abstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers.
- MultipleClassifiersCombiner() - 类的构造器 weka.classifiers.MultipleClassifiersCombiner
- multiply(Matrix) - 类中的方法 weka.core.Matrix
-
已过时。Returns the multiplication of two matrices
- multiResultsetFull(int, int) - 类中的方法 weka.experiment.PairedTTester
-
Creates a comparison table where a base resultset is compared to the other resultsets.
- multiResultsetFull(int, int) - 接口中的方法 weka.experiment.Tester
-
Creates a comparison table where a base resultset is compared to the other resultsets.
- multiResultsetRanking(int) - 类中的方法 weka.experiment.PairedTTester
-
returns a ranking of the resultsets
- multiResultsetRanking(int) - 接口中的方法 weka.experiment.Tester
- multiResultsetSummary(int) - 类中的方法 weka.experiment.PairedTTester
-
Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
- multiResultsetSummary(int) - 接口中的方法 weka.experiment.Tester
-
Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
- multiResultsetWins(int, int[][]) - 类中的方法 weka.experiment.PairedTTester
-
Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
- multiResultsetWins(int, int[][]) - 接口中的方法 weka.experiment.Tester
-
Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
- MultiScheme - weka.classifiers.meta中的类
-
Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data.
- MultiScheme() - 类的构造器 weka.classifiers.meta.MultiScheme
- mutationProbTipText() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns the tip text for this property
N
- NaiveBayes - weka.classifiers.bayes中的类
-
Class for a Naive Bayes classifier using estimator classes.
- NaiveBayes - weka.classifiers.bayes.net.search.fixed中的类
-
The NaiveBayes class generates a fixed Bayes network structure with arrows from the class variable to each of the attribute variables.
- NaiveBayes() - 类的构造器 weka.classifiers.bayes.NaiveBayes
- NaiveBayes() - 类的构造器 weka.classifiers.bayes.net.search.fixed.NaiveBayes
- NaiveBayesMultinomial - weka.classifiers.bayes中的类
-
Class for building and using a multinomial Naive Bayes classifier.
- NaiveBayesMultinomial() - 类的构造器 weka.classifiers.bayes.NaiveBayesMultinomial
- NaiveBayesMultinomialUpdateable - weka.classifiers.bayes中的类
-
Class for building and using a multinomial Naive Bayes classifier.
- NaiveBayesMultinomialUpdateable() - 类的构造器 weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
- NaiveBayesSimple - weka.classifiers.bayes中的类
-
Class for building and using a simple Naive Bayes classifier.Numeric attributes are modelled by a normal distribution.
For more information, see
Richard Duda, Peter Hart (1973). - NaiveBayesSimple() - 类的构造器 weka.classifiers.bayes.NaiveBayesSimple
- NaiveBayesUpdateable - weka.classifiers.bayes中的类
-
Class for a Naive Bayes classifier using estimator classes.
- NaiveBayesUpdateable() - 类的构造器 weka.classifiers.bayes.NaiveBayesUpdateable
- name() - 类中的方法 weka.core.Attribute
-
Returns the attribute's name.
- name() - 类中的方法 weka.core.Option
-
Returns the option's name.
- NAME_CLASSFIRST - 类中的静态变量 weka.experiment.xml.XMLExperiment
-
the name of the classFirst property
- NAME_PROPERTYNODE_PARENTCLASS - 类中的静态变量 weka.experiment.xml.XMLExperiment
-
PropertyNode member
- NAME_PROPERTYNODE_PROPERTY - 类中的静态变量 weka.experiment.xml.XMLExperiment
-
PropertyNode member
- NAME_PROPERTYNODE_VALUE - 类中的静态变量 weka.experiment.xml.XMLExperiment
-
PropertyNode member
- NamedColor - weka.gui.treevisualizer中的类
-
This class contains a color name and the rgb values of that color
- NamedColor(String, int, int, int) - 类的构造器 weka.gui.treevisualizer.NamedColor
- nameTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Returns the tip text for this property
- NBconditionalProb(Instance, int) - 类中的方法 weka.classifiers.bayes.AODE
-
Calculates the probability of the specified class for the given test instance, using naive Bayes.
- NBconditionalProb(Instance, int) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Calculates the probability of the specified class for the given test instance, using naive Bayes.
- NBTree - weka.classifiers.trees中的类
-
Class for generating a decision tree with naive Bayes classifiers at the leaves.
For more information, see
Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. - NBTree() - 类的构造器 weka.classifiers.trees.NBTree
- NBTreeClassifierTree - weka.classifiers.trees.j48中的类
-
Class for handling a naive bayes tree structure used for classification.
- NBTreeClassifierTree(ModelSelection) - 类的构造器 weka.classifiers.trees.j48.NBTreeClassifierTree
- NBTreeModelSelection - weka.classifiers.trees.j48中的类
-
Class for selecting a NB tree split.
- NBTreeModelSelection(int, Instances) - 类的构造器 weka.classifiers.trees.j48.NBTreeModelSelection
-
Initializes the split selection method with the given parameters.
- NBTreeNoSplit - weka.classifiers.trees.j48中的类
-
Class implementing a "no-split"-split (leaf node) for naive bayes trees.
- NBTreeNoSplit() - 类的构造器 weka.classifiers.trees.j48.NBTreeNoSplit
- NBTreeSplit - weka.classifiers.trees.j48中的类
-
Class implementing a NBTree split on an attribute.
- NBTreeSplit(int, int, double) - 类的构造器 weka.classifiers.trees.j48.NBTreeSplit
-
Initializes the split model.
- ND - weka.classifiers.meta.nestedDichotomies中的类
-
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random tree structure.
For more info, check
Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. - ND() - 类的构造器 weka.classifiers.meta.nestedDichotomies.ND
-
Constructor.
- NDConditionalEstimator - weka.estimators中的类
-
Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate normal estimators for each discrete conditioning value).
- NDConditionalEstimator(int, double) - 类的构造器 weka.estimators.NDConditionalEstimator
-
Constructor
- nearestNeighborsTipText() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns the tip text for this property.
- nearestNeighbour(Instance) - 类中的方法 weka.core.neighboursearch.BallTree
-
Returns the nearest instance in the current neighbourhood to the supplied instance.
- nearestNeighbour(Instance) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Returns the NN instance of a given target instance, from among the previously supplied training instances.
- nearestNeighbour(Instance) - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the nearest neighbour of the supplied target instance.
- nearestNeighbour(Instance) - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Returns the nearest instance in the current neighbourhood to the supplied instance.
- nearestNeighbour(Instance) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Returns the nearest instance in the current neighbourhood to the supplied instance.
- NearestNeighbourSearch - weka.core.neighboursearch中的类
-
Abstract class for nearest neighbour search.
- NearestNeighbourSearch() - 类的构造器 weka.core.neighboursearch.NearestNeighbourSearch
-
Constructor.
- NearestNeighbourSearch(Instances) - 类的构造器 weka.core.neighboursearch.NearestNeighbourSearch
-
Constructor.
- nearestNeighbourSearchAlgorithmTipText() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the tip text for this property.
- nearestNeighbourSearchAlgorithmTipText() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns the tip text for this property.
- needExponentialFormat(double) - 类中的方法 weka.core.matrix.FlexibleDecimalFormat
- needsUID(Class) - 类中的静态方法 weka.core.SerializationHelper
-
checks whether a class needs to declare a serialVersionUID, i.e., it implements the java.io.Serializable interface but doesn't declare a serialVersionUID.
- needsUID(String) - 类中的静态方法 weka.core.SerializationHelper
-
checks whether a class needs to declare a serialVersionUID, i.e., it implements the java.io.Serializable interface but doesn't declare a serialVersionUID.
- NEG - 类中的静态变量 weka.associations.tertius.Literal
- negationIncludedIn(LiteralSet) - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if the negation of this LiteralSet is included in another LiteralSet.
- negationSatisfies(Instance) - 类中的方法 weka.associations.tertius.AttributeValueLiteral
- negationSatisfies(Instance) - 类中的方法 weka.associations.tertius.Literal
- negationTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- negative() - 类中的方法 weka.associations.tertius.Literal
- nestedEstimate(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Returns the optimal nested model estimate of a vector.
- NeuralConnection - weka.classifiers.functions.neural中的类
-
Abstract unit in a NeuralNetwork.
- NeuralConnection(String) - 类的构造器 weka.classifiers.functions.neural.NeuralConnection
-
Constructs The unit with the basic connection information prepared for use.
- NeuralMethod - weka.classifiers.functions.neural中的接口
-
This is an interface used to create classes that can be used by the neuralnode to perform all it's computations.
- NeuralNetwork - weka.classifiers.pmml.consumer中的类
-
Class implementing import of PMML Neural Network model.
- NeuralNetwork(Element, Instances, MiningSchema) - 类的构造器 weka.classifiers.pmml.consumer.NeuralNetwork
- NeuralNode - weka.classifiers.functions.neural中的类
-
This class is used to represent a node in the neuralnet.
- NeuralNode(String, Random, NeuralMethod) - 类的构造器 weka.classifiers.functions.neural.NeuralNode
- NEW_BATCH - 类中的静态变量 weka.gui.beans.IncrementalClassifierEvent
- newClock() - 类中的静态方法 weka.core.Debug
-
returns a new instance of a clock
- newDataFormat(DataSetEvent) - 类中的方法 weka.gui.beans.ClassAssignerCustomizer
- newDataFormat(DataSetEvent) - 接口中的方法 weka.gui.beans.DataFormatListener
-
Recieve a DataSetEvent that encapsulates a new data format.
- newDocument(String, String) - 类中的方法 weka.core.xml.XMLDocument
-
creates a new Document with the given information.
- newEnt(Distribution) - 类中的方法 weka.classifiers.trees.j48.EntropyBasedSplitCrit
-
Computes entropy of distribution after splitting.
- Newick - 接口中的静态变量 weka.core.Drawable
- newInstance(File, Class) - 类中的静态方法 weka.core.Jython
-
loads the module and returns a new instance of it as instance of the provided Java class template.
- newInstance(File, Class, File[]) - 类中的静态方法 weka.core.Jython
-
loads the module and returns a new instance of it as instance of the provided Java class template.
- newInterpreter() - 类中的静态方法 weka.core.Jython
-
initializes and returns a Python Interpreter
- newLog(String, int, int) - 类中的静态方法 weka.core.Debug
-
returns a new Log instance
- newNominalRule(Attribute, Instances, int[]) - 类中的方法 weka.classifiers.rules.OneR
-
Create a rule branching on this nominal attribute.
- newNumericRule(Attribute, Instances, int[]) - 类中的方法 weka.classifiers.rules.OneR
-
Create a rule branching on this numeric attribute
- newRandom() - 类中的静态方法 weka.core.Debug
-
returns a default debug random object, with no particular seed and debugging enabled.
- newRandom(int) - 类中的静态方法 weka.core.Debug
-
returns a debug random object with the specified seed and debugging enabled.
- newRule(Attribute, Instances) - 类中的方法 weka.classifiers.rules.OneR
-
Create a rule branching on this attribute.
- newTimestamp() - 类中的静态方法 weka.core.Debug
-
returns a default timestamp for the current date/time
- next - 类中的变量 weka.classifiers.lazy.kstar.KStarCache.TableEntry
-
next table entry (separate chaining)
- next() - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListIterator
- next() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue
-
Returns the element with the highest priority
- next() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue
-
Returns the element with the lowest priority
- next() - 类中的方法 weka.core.Trie.TrieIterator
-
Returns the next element in the iteration.
- next(int) - 接口中的方法 weka.classifiers.IterativeClassifier
-
Performs one iteration.
- next(int) - 类中的方法 weka.classifiers.trees.ADTree
-
Performs one iteration.
- next(int) - 类中的方法 weka.classifiers.trees.LADTree
- next_token() - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Resumes scanning until the next regular expression is matched, the end of input is encountered or an I/O-Error occurs.
- next_token() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Resumes scanning until the next regular expression is matched, the end of input is encountered or an I/O-Error occurs.
- nextBoolean() - 类中的方法 weka.core.Debug.Random
-
Returns the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence.
- nextBytes(byte[]) - 类中的方法 weka.core.Debug.Random
-
Generates random bytes and places them into a user-supplied byte array.
- nextDouble() - 类中的方法 weka.core.Debug.Random
-
Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.
- nextElement() - 类中的方法 weka.core.FastVector.FastVectorEnumeration
-
Returns the next element.
- nextElement() - 类中的方法 weka.core.tokenizers.AlphabeticTokenizer
-
returns the next element
- nextElement() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Returns N-grams and also (N-1)-grams and ....
- nextElement() - 类中的方法 weka.core.tokenizers.Tokenizer
-
Returns the next element of this enumeration if this enumeration object has at least one more element to provide.
- nextElement() - 类中的方法 weka.core.tokenizers.WordTokenizer
-
Returns the next element of this enumeration if this enumeration object has at least one more element to provide.
- nextElement(Instances) - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
returns the next element and sets the specified dataset, null if none available.
- nextErlang(int) - 类中的方法 weka.core.RandomVariates
-
Generate a value of a variate following standard Erlang distribution.
- nextExponential() - 类中的方法 weka.core.RandomVariates
-
Generate a value of a variate following standard exponential distribution using simple inverse method.
- nextFloat() - 类中的方法 weka.core.Debug.Random
-
Returns the next pseudorandom, uniformly distributed float value between 0.0 and 1.0 from this random number generator's sequence.
- nextGamma(double) - 类中的方法 weka.core.RandomVariates
-
Generate a value of a variate following standard Gamma distribution with shape parameter a.
- nextGaussian() - 类中的方法 weka.core.Debug.Random
-
Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.
- nextInt() - 类中的方法 weka.core.Debug.Random
-
Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence.
- nextInt(int) - 类中的方法 weka.core.Debug.Random
-
Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
- nextIteration() - 类中的方法 weka.experiment.Experiment
-
Carries out the next iteration of the experiment.
- nextIteration() - 类中的方法 weka.experiment.RemoteExperiment
-
Overides the one in Experiment
- nextLong() - 类中的方法 weka.core.Debug.Random
-
Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence.
- nextSplitAddedOrder() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns the next number in the order that splitter nodes have been added to the tree, and records that a new splitter has been added.
- NGramMaxSizeTipText() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Returns the tip text for this property.
- NGramMinSizeTipText() - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Returns the tip text for this property.
- NGramTokenizer - weka.core.tokenizers中的类
-
Splits a string into an n-gram with min and max grams.
- NGramTokenizer() - 类的构造器 weka.core.tokenizers.NGramTokenizer
- NNConditionalEstimator - weka.estimators中的类
-
Conditional probability estimator for a numeric domain conditional upon a numeric domain (using Mahalanobis distance).
- NNConditionalEstimator() - 类的构造器 weka.estimators.NNConditionalEstimator
- NNge - weka.classifiers.rules中的类
-
Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules).
- NNge() - 类的构造器 weka.classifiers.rules.NNge
- nnls(PaceMatrix, IntVector) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Solves the nonnegative linear squares problem.
- nnlse(PaceMatrix, PaceMatrix, PaceMatrix, IntVector) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Solves the nonnegative least squares problem with equality constraint.
- nnlse1(PaceMatrix, IntVector) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Solves the nonnegative least squares problem with equality constraint.
- NNMMethod - 类中的静态变量 weka.classifiers.functions.pace.MixtureDistribution
-
The nonnegative-measure-based method
- NO_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle data without class attribute, eg clusterers
- NO_CLASS - 类中的静态变量 weka.associations.CheckAssociator
-
a "dummy" class type
- NO_CLASS - 类中的静态变量 weka.core.TestInstances
-
can be used to avoid generating a class attribute
- NO_COMMAND - 类中的静态变量 weka.gui.treevisualizer.TreeDisplayEvent
- NO_SUPPORT - 类中的静态变量 weka.gui.GenericObjectEditor.GOETreeNode
-
color for "no support".
- Node - weka.gui.treevisualizer中的类
-
This class records all the data about a particular node for displaying.
- Node(String, String, int, int, Color, String) - 类的构造器 weka.gui.treevisualizer.Node
-
This will setup all the values of the node except for its top and center.
- NodePlace - weka.gui.treevisualizer中的接口
-
This is an interface for classes that wish to take a node structure and arrange them
- nodeSplitterTipText() - 类中的方法 weka.core.neighboursearch.KDTree
-
Returns the tip text for this property.
- nodeToString() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Returns a description of this node (debugging purposes)
- nodeType - 类中的变量 weka.gui.graphvisualizer.GraphNode
-
Type of node.
- NOISE - 接口中的静态变量 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
- noisePercentTipText() - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Returns the tip text for this property
- noiseRateTipText() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Returns the tip text for this property
- noiseRateTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- noiseRateTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Returns the tip text for this property
- noiseThresholdTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- noiseTipText() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Returns the tip text for this property
- noiseVarianceTipText() - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Returns the tip text for this property
- NOMINAL - 类中的静态变量 weka.core.Attribute
-
Constant set for nominal attributes.
- NOMINAL_ATTRIBUTES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle nominal attributes
- NOMINAL_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle nominal classes
- NominalAntd(Attribute) - 类的构造器 weka.classifiers.rules.JRip.NominalAntd
-
Constructor
- nominalAttributesTipText() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the tip text for this property.
- nominalColsTipText() - 类中的方法 weka.datagenerators.ClusterGenerator
-
Returns the tip text for this property
- nominalCounts - 类中的变量 weka.core.AttributeStats
-
Counts of each nominal value
- nominalIndicesTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the tip text for this property
- nominalLabelsTipText() - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Returns the tip text for this property.
- NominalPrediction - weka.classifiers.evaluation中的类
-
Encapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value.
- NominalPrediction(double, double[]) - 类的构造器 weka.classifiers.evaluation.NominalPrediction
-
Creates the NominalPrediction object with a default weight of 1.0.
- NominalPrediction(double, double[], double) - 类的构造器 weka.classifiers.evaluation.NominalPrediction
-
Creates the NominalPrediction object.
- NominalToBinary - weka.filters.supervised.attribute中的类
-
Converts all nominal attributes into binary numeric attributes.
- NominalToBinary - weka.filters.unsupervised.attribute中的类
-
Converts all nominal attributes into binary numeric attributes.
- NominalToBinary() - 类的构造器 weka.filters.supervised.attribute.NominalToBinary
- NominalToBinary() - 类的构造器 weka.filters.unsupervised.attribute.NominalToBinary
-
Constructor - initialises the filter
- nominalToBinaryFilterTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- NominalToString - weka.filters.unsupervised.attribute中的类
-
Converts a nominal attribute (i.e.
- NominalToString() - 类的构造器 weka.filters.unsupervised.attribute.NominalToString
- NON_NUMERIC - 类中的静态变量 weka.filters.unsupervised.attribute.InterquartileRange
-
indicator for non-numeric attributes
- NONE - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Optype
- NONE - 接口中的静态变量 weka.core.converters.Loader
-
The retrieval modes
- NONE - 接口中的静态变量 weka.core.converters.Saver
-
The retrieval modes
- NONE - 类中的静态变量 weka.gui.visualize.VisualizePanelEvent
-
No longer used
- NonSparseToSparse - weka.filters.unsupervised.instance中的类
-
An instance filter that converts all incoming instances into sparse format.
- NonSparseToSparse() - 类的构造器 weka.filters.unsupervised.instance.NonSparseToSparse
- noPruningTipText() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the tip text for this property
- noReplacementTipText() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns the tip text for this property.
- noReplacementTipText() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Returns the tip text for this property
- norm() - 类中的方法 weka.core.AlgVector
-
Returns the norm of the vector
- NORM_BASED - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Methods for selecting the hyperparameter value
- NORM_EXPECTED_COST_NAME - 类中的静态变量 weka.classifiers.evaluation.CostCurve
-
attribute name: Normalized Expected Cost
- norm1() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the L1-norm of the vector
- norm1() - 类中的方法 weka.core.matrix.Matrix
-
One norm
- norm2() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the L2-norm of the vector
- norm2() - 类中的方法 weka.core.matrix.Matrix
-
Two norm
- norm2() - 类中的方法 weka.core.matrix.SingularValueDecomposition
-
Two norm
- NORMAL - 接口中的静态变量 weka.gui.graphvisualizer.GraphConstants
-
NORMAL node - node actually contained in graphs description
- normalDistribution - 类中的静态变量 weka.core.matrix.Maths
-
Distribution type: noraml
- NormalEstimator - weka.estimators中的类
-
Simple probability estimator that places a single normal distribution over the observed values.
- NormalEstimator(double) - 类的构造器 weka.estimators.NormalEstimator
-
Constructor that takes a precision argument.
- normalInverse(double) - 类中的静态方法 weka.core.Statistics
-
Returns the value, x, for which the area under the Normal (Gaussian) probability density function (integrated from minus infinity to x) is equal to the argument y (assumes mean is zero, variance is one).
- NormalizableDistance - weka.core中的类
-
Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.
- NormalizableDistance() - 类的构造器 weka.core.NormalizableDistance
-
Invalidates the distance function, Instances must be still set.
- NormalizableDistance(Instances) - 类的构造器 weka.core.NormalizableDistance
-
Initializes the distance function and automatically initializes the ranges.
- normalize() - 类中的方法 weka.classifiers.CostMatrix
-
Normalizes the matrix so that the diagonal contains zeros.
- normalize() - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Normalizes the function values with L1-norm.
- normalize(double[]) - 类中的静态方法 weka.core.Utils
-
Normalizes the doubles in the array by their sum.
- normalize(double[], double) - 类中的静态方法 weka.core.Utils
-
Normalizes the doubles in the array using the given value.
- Normalize - weka.filters.unsupervised.attribute中的类
-
Normalizes all numeric values in the given dataset (apart from the class attribute, if set).
- Normalize - weka.filters.unsupervised.instance中的类
-
An instance filter that normalize instances considering only numeric attributes and ignoring class index.
- Normalize() - 类的构造器 weka.filters.unsupervised.attribute.Normalize
- Normalize() - 类的构造器 weka.filters.unsupervised.instance.Normalize
- normalizeAttributesTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- NormalizeData - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Choose whether to normalize data or not
- normalizeDataTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- normalizeDimWidthsTipText() - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Returns the tip text for this property.
- normalizedKernel(char[], char[]) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
evaluates the normalized kernel between s and t.
- normalizeDocLengthTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- NormalizedPolyKernel - weka.classifiers.functions.supportVector中的类
-
The normalized polynomial kernel.
K(x,y) = <x,y>/sqrt(<x,x><y,y>) where <x,y> = PolyKernel(x,y) - NormalizedPolyKernel() - 类的构造器 weka.classifiers.functions.supportVector.NormalizedPolyKernel
-
default constructor - does nothing
- NormalizedPolyKernel(Instances, int, double, boolean) - 类的构造器 weka.classifiers.functions.supportVector.NormalizedPolyKernel
-
Creates a new
NormalizedPolyKernel
instance. - normalizeNodeWidthTipText() - 类中的方法 weka.core.neighboursearch.KDTree
-
Tip text for this property.
- normalizeNumericClassTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- normalizeTipText() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns the tip text for this property
- normalizeTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- normalizeTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- normalizeWordWeightsTipText() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Returns the tip text for this property
- NormalMixture - weka.classifiers.functions.pace中的类
-
Class for manipulating normal mixture distributions.
- NormalMixture() - 类的构造器 weka.classifiers.functions.pace.NormalMixture
-
Contructs an empty NormalMixture
- normalProbability(double) - 类中的静态方法 weka.core.Statistics
-
Returns the area under the Normal (Gaussian) probability density function, integrated from minus infinity to x (assumes mean is zero, variance is one).
- normBasedHyperParameter() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
This function computes the norm-based hyperparameters and stores them in the m_Hyperparameters.
- NormContinuous - weka.core.pmml中的类
-
Class encapsulating a NormContinuous Expression.
- NormContinuous(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - 类的构造器 weka.core.pmml.NormContinuous
- NormDiscrete - weka.core.pmml中的类
-
Class encapsulating a NormDiscrete Expression.
- NormDiscrete(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - 类的构造器 weka.core.pmml.NormDiscrete
-
Constructor.
- normF() - 类中的方法 weka.core.matrix.Matrix
-
Frobenius norm
- normInf() - 类中的方法 weka.core.matrix.Matrix
-
Infinity norm
- normTipText() - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Returns the tip text for this property
- normVector() - 类中的方法 weka.core.AlgVector
-
Norms this vector to length 1.0
- NORTH_CONNECTOR - 类中的静态变量 weka.gui.beans.BeanVisual
- NoSplit - weka.classifiers.trees.j48中的类
-
Class implementing a "no-split"-split.
- NoSplit(Distribution) - 类的构造器 weka.classifiers.trees.j48.NoSplit
-
Creates "no-split"-split for given distribution.
- NoSupportForMissingValuesException - weka.core中的异常错误
-
Exception that is raised by an object that is unable to process data with missing values.
- NoSupportForMissingValuesException() - 异常错误的构造器 weka.core.NoSupportForMissingValuesException
-
Creates a new NoSupportForMissingValuesException with no message.
- NoSupportForMissingValuesException(String) - 异常错误的构造器 weka.core.NoSupportForMissingValuesException
-
Creates a new NoSupportForMissingValuesException.
- NOT - 接口中的静态变量 weka.core.mathematicalexpression.sym
- NOT - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- NOT_DRAWABLE - 接口中的静态变量 weka.core.Drawable
- notCoveredInstances() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Get the instances not covered by this rule
- NOTE - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
Any additional information that can help the reader.
- notifyCapabilitiesFilterListener(Capabilities) - 类中的方法 weka.gui.explorer.Explorer
-
notifies all the listeners of a change
- notifyListener() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
notfies all listener of the change
- notifyListener(TableModelEvent) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
notfies all listener of the change of the model
- notifyListener(TableModelEvent) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
notfies all listener of the change of the model
- notUnifyNormTipText() - 类中的方法 weka.clusterers.sIB
-
Returns the tip text for this property.
- nrOfGoodOperationsTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
- nrOfLookAheadStepsTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
- NullStemmer - weka.core.stemmers中的类
-
A dummy stemmer that performs no stemming at all.
- NullStemmer() - 类的构造器 weka.core.stemmers.NullStemmer
- NUM_RAND_COLS - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- numAllConditions(Instances) - 类中的静态方法 weka.classifiers.rules.RuleStats
-
Compute the number of all possible conditions that could appear in a rule of a given data.
- numAntdsTipText() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns the tip text for this property
- numArcsTipText() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Returns the tip text for this property
- numArguments() - 类中的方法 weka.core.Option
-
Returns the option's number of arguments.
- numAttemptsOfGeneOptionTipText() - 类中的方法 weka.classifiers.rules.NNge
-
Returns the tip text for this property
- numAttributes() - 类中的方法 weka.core.Instance
-
Returns the number of attributes.
- numAttributes() - 类中的方法 weka.core.Instances
-
Returns the number of attributes.
- numAttributes() - 类中的方法 weka.core.SparseInstance
-
Returns the number of attributes.
- numAttributesTipText() - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Returns the tip text for this property
- numAttributesTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Returns the tip text for this property
- numAttributesTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the tip text for this property
- numAttributesTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Returns the tip text for this property
- numAttributesTipText() - 类中的方法 weka.datagenerators.ClusterGenerator
-
Returns the tip text for this property
- numAttributesTipText() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Returns the tip text for this property.
- numBags() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns number of bags.
- NUMBER - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The number of a journal, magazine, technical report, or of a work in a series.
- NUMBER - 接口中的静态变量 weka.core.mathematicalexpression.sym
- NUMBER - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- numberAttributesSelected() - 类中的方法 weka.attributeSelection.AttributeSelection
-
Return the number of attributes selected from the most recent run of attribute selection
- numberLiteralsTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- numberOfAttributesTipText() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns the tip text for this property
- numberOfClusters() - 类中的方法 weka.clusterers.AbstractClusterer
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.CLOPE
- numberOfClusters() - 接口中的方法 weka.clusterers.Clusterer
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.Cobweb
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.DBSCAN
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.EM
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.FarthestFirst
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.HierarchicalClusterer
- numberOfClusters() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.OPTICS
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.sIB
-
Get the number of clusters
- numberOfClusters() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.SingleClustererEnhancer
-
Returns the number of clusters.
- numberOfClusters() - 类中的方法 weka.clusterers.XMeans
-
Returns the number of clusters.
- NumberOfClustersRequestable - weka.clusterers中的接口
-
Interface to a clusterer that can generate a requested number of clusters
- numberOfGroupsTipText() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns the tip text for this property
- numberOfLinearModels() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the number of linear models in the tree
- numBinsTipText() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns the tip text for this property
- numBoostingIterationsTipText() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the tip text for this property
- numBoostingIterationsTipText() - 类中的方法 weka.classifiers.trees.FT
-
Returns the tip text for this property
- numBoostingIterationsTipText() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the tip text for this property
- numCacheHits() - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Returns the number of cache hits on dot products.
- numCacheHits() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns the number of dot product cache hits.
- numCacheHits() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Returns the number of dot product cache hits.
- numCacheHits() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the number of dot product cache hits.
- numCentroidsTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Returns the tip text for this property
- numChildren() - 类中的方法 weka.gui.HierarchyPropertyParser
-
The number of the children nodes.
- numCitersTipText() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns the tip text for this property
- numClassAttributeValues() - 类中的方法 weka.classifiers.functions.SMO
- numClassAttributeValues() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the number of values of the class attribute.
- numClasses() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns number of classes.
- numClasses() - 类中的方法 weka.core.Instance
-
Returns the number of class labels.
- numClasses() - 类中的方法 weka.core.Instances
-
Returns the number of class labels.
- numClassesTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Returns the tip text for this property
- numClassesTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the tip text for this property
- numClustersTipText() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns the tip text for this property
- numClustersTipText() - 类中的方法 weka.clusterers.EM
-
Returns the tip text for this property
- numClustersTipText() - 类中的方法 weka.clusterers.FarthestFirst
-
Returns the tip text for this property
- numClustersTipText() - 类中的方法 weka.clusterers.HierarchicalClusterer
- numClustersTipText() - 类中的方法 weka.clusterers.sIB
-
Returns the tip text for this property.
- numClustersTipText() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns the tip text for this property
- numClustersTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- numColumns() - 类中的方法 weka.classifiers.CostMatrix
-
Same as size
- numColumns() - 类中的方法 weka.core.Matrix
-
已过时。Returns the number of columns in the matrix.
- numComponentsTipText() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns the tip text for this property
- numCorrect() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns perClass(maxClass()).
- numCorrect(int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns perClassPerBag(index,maxClass(index)).
- numCyclesTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- numDistinctValues(int) - 类中的方法 weka.core.Instances
-
Returns the number of distinct values of a given attribute.
- numDistinctValues(Attribute) - 类中的方法 weka.core.Instances
-
Returns the number of distinct values of a given attribute.
- numElements() - 类中的方法 weka.classifiers.functions.supportVector.SMOset
-
Returns the number of elements in the set.
- numElements() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns the number of elements in the partition.
- numElements() - 类中的方法 weka.core.AlgVector
-
Returns the number of elements in the vector.
- NUMERIC - 类中的静态变量 weka.core.Attribute
-
Constant set for numeric attributes.
- NUMERIC_ATTRIBUTES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle numeric attributes
- NUMERIC_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle numeric classes
- NumericAntd(Attribute) - 类的构造器 weka.classifiers.rules.JRip.NumericAntd
-
Constructor
- NumericCleaner - weka.filters.unsupervised.attribute中的类
-
A filter that 'cleanses' the numeric data from values that are too small, too big or very close to a certain value (e.g., 0) and sets these values to a pre-defined default.
- NumericCleaner() - 类的构造器 weka.filters.unsupervised.attribute.NumericCleaner
- NumericPrediction - weka.classifiers.evaluation中的类
-
Encapsulates an evaluatable numeric prediction: the predicted class value plus the actual class value.
- NumericPrediction(double, double) - 类的构造器 weka.classifiers.evaluation.NumericPrediction
-
Creates the NumericPrediction object with a default weight of 1.0.
- NumericPrediction(double, double, double) - 类的构造器 weka.classifiers.evaluation.NumericPrediction
-
Creates the NumericPrediction object.
- numericStats - 类中的变量 weka.core.AttributeStats
-
Stats on numeric value distributions
- numericTipText() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
- NumericToBinary - weka.filters.unsupervised.attribute中的类
-
Converts all numeric attributes into binary attributes (apart from the class attribute, if set): if the value of the numeric attribute is exactly zero, the value of the new attribute will be zero.
- NumericToBinary() - 类的构造器 weka.filters.unsupervised.attribute.NumericToBinary
- NumericToNominal - weka.filters.unsupervised.attribute中的类
-
A filter for turning numeric attributes into nominal ones.
- NumericToNominal() - 类的构造器 weka.filters.unsupervised.attribute.NumericToNominal
- NumericTransform - weka.filters.unsupervised.attribute中的类
-
Transforms numeric attributes using a given transformation method.
- NumericTransform() - 类的构造器 weka.filters.unsupervised.attribute.NumericTransform
-
Default constructor -- sets the default transform method to java.lang.Math.abs().
- numEvals() - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Returns the number of time Eval has been called.
- numEvals() - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Returns the number of kernel evaluation performed.
- numEvals() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Returns the number of kernel evaluation performed.
- numEvals() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the number of kernel evaluation performed.
- numExamplesTipText() - 类中的方法 weka.datagenerators.ClassificationGenerator
-
Returns the tip text for this property
- numExamplesTipText() - 类中的方法 weka.datagenerators.RegressionGenerator
-
Returns the tip text for this property
- numFalseNegatives(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate number of false negatives with respect to a particular class.
- numFalsePositives(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate number of false positives with respect to a particular class.
- numFeaturesTipText() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns the tip text for this property
- numFoldersMIOptionTipText() - 类中的方法 weka.classifiers.rules.NNge
-
Returns the tip text for this property
- NumFolds - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
NumFolds for CV based Hyperparameters selection
- numFoldsPruningTipText() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the tip text for this property
- numFoldsPruningTipText() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.meta.Dagging
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.meta.Stacking
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.rules.PART
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Returns the tip text for this property
- numFoldsTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns the tip text for this property
- numIncorrect() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns total-numCorrect().
- numIncorrect(int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns perBag(index)-numCorrect(index).
- numInnerNodes() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Method to count the number of inner nodes in the tree.
- numInstances() - 类中的方法 weka.classifiers.Evaluation
-
Gets the number of test instances that had a known class value (actually the sum of the weights of test instances with known class value).
- numInstances() - 类中的方法 weka.core.Instances
-
Returns the number of instances in the dataset.
- numInstances() - 类中的方法 weka.core.neighboursearch.balltrees.BallNode
-
Returns the number of instances in the hyper-spherical region of this node.
- numInstances() - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNode
-
Returns the number of Instances in the rectangular region defined by this node.
- numIrrelevantTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the tip text for this property
- numIterationsTipText() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Returns the tip text for this property
- numIterationsTipText() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns the tip text for this property
- numIterationsTipText() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns the tip text for this property
- numIterationsTipText() - 类中的方法 weka.classifiers.IteratedSingleClassifierEnhancer
-
Returns the tip text for this property
- numIterationsTipText() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns the tip text for this property
- numIterationsTipText() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns the tip text for this property
- numLeaves() - 类中的方法 weka.classifiers.trees.BFTree
-
Compute number of leaf nodes.
- numLeaves() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns the number of leaves (normal count).
- numLeaves() - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns number of leaves in tree structure.
- numLeaves() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns the number of leaves (normal count).
- numLeaves() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Compute number of leaf nodes.
- numLeaves(int) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Sets the leaves' numbers
- numLiterals() - 类中的方法 weka.associations.tertius.LiteralSet
-
Give the number of literals in this set.
- numLiterals() - 类中的方法 weka.associations.tertius.Predicate
- numLiterals() - 类中的方法 weka.associations.tertius.Rule
-
Give the number of literals in this rule.
- numNeighboursTipText() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns the tip text for this property
- numNeighboursTipText() - 类中的方法 weka.classifiers.mi.MINND
-
Returns the tip text for this property
- numNodes() - 类中的方法 weka.classifiers.trees.BFTree
-
Compute size of the tree.
- numNodes() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns the number of nodes.
- numNodes() - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns number of nodes in tree structure.
- numNodes() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns the number of nodes.
- numNodes() - 类中的方法 weka.classifiers.trees.REPTree
-
Computes size of the tree.
- numNodes() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Compute size of the tree.
- numNumericTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the tip text for this property
- numOfBoostingIterationsTipText() - 类中的方法 weka.classifiers.trees.ADTree
- numOfBoostingIterationsTipText() - 类中的方法 weka.classifiers.trees.LADTree
- numParameters() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Get the number of coefficients used in the model
- numParameters() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Get the number of coefficients used in the model
- numParameters() - 类中的方法 weka.classifiers.trees.m5.PreConstructedLinearModel
-
Return the number of parameters (coefficients) in the linear model
- numPendingOutput() - 类中的方法 weka.filters.Filter
-
Returns the number of instances pending output
- numPendingOutput() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Returns the number of instances pending output
- numReferencesTipText() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Returns the tip text for this property
- numRestartsTipText() - 类中的方法 weka.clusterers.sIB
-
Returns the tip text for this property.
- numRows() - 类中的方法 weka.classifiers.CostMatrix
-
Same as size
- numRows() - 类中的方法 weka.core.Matrix
-
已过时。Returns the number of rows in the matrix.
- numRules() - 类中的方法 weka.classifiers.rules.part.MakeDecList
-
Outputs the number of rules in the classifier.
- numRulesTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- numRulesTipText() - 类中的方法 weka.associations.PredictiveApriori
-
Returns the tip text for this property
- numRulesToFindTipText() - 类中的方法 weka.associations.FPGrowth
-
Tip text for this property suitable for displaying in the GUI.
- numRunsTipText() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the tip text for this property
- numSubCmtysTipText() - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Returns the tip text for this property
- numSubsets() - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Returns the number of created subsets for the split.
- numSubsetSizeCVFoldsTipText() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the tip text for this property
- numTestingNoisesTipText() - 类中的方法 weka.classifiers.mi.MINND
-
Returns the tip text for this property
- numToSelectTipText() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns the tip text for this property
- numToSelectTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- numToSelectTipText() - 类中的方法 weka.attributeSelection.Ranker
-
Returns the tip text for this property
- numTrainingNoisesTipText() - 类中的方法 weka.classifiers.mi.MINND
-
Returns the tip text for this property
- numTreesTipText() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns the tip text for this property
- numTrueNegatives(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the number of true negatives with respect to a particular class.
- numTruePositives(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the number of true positives with respect to a particular class.
- numUsedAttributesTipText() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the tip text for this property
- numUsedAttributesTipText() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the tip text for this property
- numValues() - 类中的方法 weka.core.Attribute
-
Returns the number of attribute values.
- numValues() - 类中的方法 weka.core.Instance
-
Returns the number of values present.
- numValues() - 类中的方法 weka.core.SparseInstance
-
Returns the number of values in the sparse vector.
- numValuesTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns the tip text for this property
- numXValFoldsTipText() - 类中的方法 weka.classifiers.meta.ThresholdSelector
- nuTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
O
- Obfuscate - weka.filters.unsupervised.attribute中的类
-
A simple instance filter that renames the relation, all attribute names and all nominal (and string) attribute values.
- Obfuscate() - 类的构造器 weka.filters.unsupervised.attribute.Obfuscate
- ObjectCellRenderer() - 类的构造器 weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer
- observedComparator - 类中的静态变量 weka.associations.tertius.Rule
-
Comparator used to compare two rules according to their observed number of counter-instances.
- obtainVotes(Instance) - 类中的方法 weka.classifiers.functions.SMO
-
Returns an array of votes for the given instance.
- OFF - enum class 中的枚举常量 weka.core.logging.Logger.Level
-
turns logging off.
- OFF - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- OFF - 类中的静态变量 weka.core.Debug
-
the log level Off - i.e., no logging
- oldEnt(Distribution) - 类中的方法 weka.classifiers.trees.j48.EntropyBasedSplitCrit
-
Computes entropy of distribution before splitting.
- omegaTipText() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Returns the tip text for this property
- ON - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
-
Some usefull constants
- onDemandDirectoryTipText() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
- onDemandDirectoryTipText() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
- onDemandDirectoryTipText() - 类中的方法 weka.classifiers.meta.MetaCost
-
Returns the tip text for this property
- onDemandDirectoryTipText() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Returns the tip text for this property
- oneElementsToSequences(FastVector) - 类中的静态方法 weka.associations.gsp.Sequence
-
Converts a set of 1-Elements into a set of 1-Sequences.
- OneR - weka.classifiers.rules中的类
-
Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing numeric attributes.
- OneR() - 类的构造器 weka.classifiers.rules.OneR
- OneRAttributeEval - weka.attributeSelection中的类
-
OneRAttributeEval :
Evaluates the worth of an attribute by using the OneR classifier. - OneRAttributeEval() - 类的构造器 weka.attributeSelection.OneRAttributeEval
-
Constructor
- ONLY_MULTIINSTANCE - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle multi-instance data
- onUnit(Graphics, int, int, int, int) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this function to determine if the point at x,y is on the unit.
- OPENCLOSED - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Interval.Closure
- openFrame(String) - 类中的方法 weka.gui.ResultHistoryPanel
-
Opens the named result in a separate frame.
- OPENOPEN - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Interval.Closure
- openURL(Component, String) - 类中的静态方法 weka.gui.BrowserHelper
-
opens the URL in a browser.
- openURL(Component, String, boolean) - 类中的静态方法 weka.gui.BrowserHelper
-
opens the URL in a browser.
- openURL(String) - 类中的静态方法 weka.gui.BrowserHelper
-
opens the URL in a browser.
- OPTICS - weka.clusterers中的类
-
Basic implementation of OPTICS clustering algorithm that should *not* be used as a reference for runtime benchmarks: more sophisticated implementations exist! Clustering of new instances is not supported.
- OPTICS() - 类的构造器 weka.clusterers.OPTICS
- OPTICS_Visualizer - weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI中的类
-
Start the OPTICS Visualizer from command-line:
java weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.OPTICS_Visualizer [file.ser]
- OPTICS_Visualizer(SERObject, String) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.OPTICS_Visualizer
- optimisticComparator - 类中的静态变量 weka.associations.tertius.Rule
-
Comparator used to compare two rules according to their optimistic estimate.
- optimisticThenObservedComparator - 类中的静态变量 weka.associations.tertius.Rule
-
Comparator used to compare two rules according to their optimistic estimate and then their observed number of counter-instances.
- Optimization - weka.core中的类
-
Implementation of Active-sets method with BFGS update to solve optimization problem with only bounds constraints in multi-dimensions.
- Optimization() - 类的构造器 weka.core.Optimization
- optimizationsTipText() - 类中的方法 weka.classifiers.rules.JRip
-
Returns the tip text for this property
- optimize() - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
finds alpha and alpha* parameters that optimize the SVM target function
- OPTIMIZE_0 - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
first class value
- OPTIMIZE_1 - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
second class value
- OPTIMIZE_LFREQ - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
least frequent class value
- OPTIMIZE_MFREQ - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
most frequent class value
- OPTIMIZE_POS_NAME - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
class value name, either 'yes' or 'pos(itive)'
- Option - weka.core中的类
-
Class to store information about an option.
- Option(String, String, int, String) - 类的构造器 weka.core.Option
-
Creates new option with the given parameters.
- OptionHandler - weka.core中的接口
-
Interface to something that understands options.
- OptionHandlerJavadoc - weka.core中的类
-
Generates Javadoc comments from the OptionHandler's options.
- OptionHandlerJavadoc() - 类的构造器 weka.core.OptionHandlerJavadoc
-
default constructor
- OPTIONS_ENDTAG - 类中的静态变量 weka.core.OptionHandlerJavadoc
-
the end comment tag for inserting the generated Javadoc
- OPTIONS_STARTTAG - 类中的静态变量 weka.core.OptionHandlerJavadoc
-
the start comment tag for inserting the generated Javadoc
- or(Capabilities) - 类中的方法 weka.core.Capabilities
-
performs an OR conjunction with the capabilities of the given Capabilities object and updates itself
- OR - 接口中的静态变量 weka.core.mathematicalexpression.sym
- OR - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- orderAdded - 类中的变量 weka.classifiers.trees.adtree.Splitter
-
The number this node was in the order of nodes added to the tree
- ORDERED - 类中的静态变量 weka.datagenerators.clusterers.BIRCHCluster
-
Constant set for input order (option O)
- ordering() - 类中的方法 weka.core.Attribute
-
Returns the ordering of the attribute.
- ORDERING_MODULO - 类中的静态变量 weka.core.Attribute
-
Constant set for modulo-ordered attributes.
- ORDERING_ORDERED - 类中的静态变量 weka.core.Attribute
-
Constant set for ordered attributes.
- ORDERING_SYMBOLIC - 类中的静态变量 weka.core.Attribute
-
Constant set for symbolic attributes.
- ORDINAL - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Optype
- OrdinalClassClassifier - weka.classifiers.meta中的类
-
Meta classifier that allows standard classification algorithms to be applied to ordinal class problems.
For more information see:
Eibe Frank, Mark Hall: A Simple Approach to Ordinal Classification. - OrdinalClassClassifier() - 类的构造器 weka.classifiers.meta.OrdinalClassClassifier
-
Default constructor.
- ORGANIZATION - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The organization that sponsors a conference or that publishes a manual.
- originalValue(double) - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Return the original internal class value given the randomized class value, i.e.
- OUT_OF_MEMORY_THRESHOLD - 类中的静态变量 weka.core.Memory
- outlierFactorTipText() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns the tip text for this property
- output() - 类中的方法 weka.filters.Filter
-
Output an instance after filtering and remove from the output queue.
- output() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Output an instance after filtering and remove from the output queue.
- OUTPUT - 类中的静态变量 weka.classifiers.functions.neural.NeuralConnection
-
This unit is an output unit.
- outputCenterFileTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- outputClassificationTipText() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns the tip text for this property.
- outputDistributionTipText() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns the tip text for this property.
- outputErrorFlagTipText() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns the tip text for this property.
- outputFileName() - 类中的方法 weka.experiment.CSVResultListener
-
Get the value of OutputFileName.
- outputFilenameTipText() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
the tip text for this property
- outputFileTipText() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns the tip text for this property
- outputFileTipText() - 类中的方法 weka.experiment.CSVResultListener
-
Returns the tip text for this property
- outputFileTipText() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns the tip text for this property
- outputFormat() - 类中的方法 weka.gui.streams.InstanceJoiner
-
Gets the format of the output instances.
- outputFormat() - 类中的方法 weka.gui.streams.InstanceLoader
- outputFormat() - 接口中的方法 weka.gui.streams.InstanceProducer
- OutputFormatDialog - weka.gui.experiment中的类
-
A dialog for setting various output format parameters.
- OutputFormatDialog(Frame) - 类的构造器 weka.gui.experiment.OutputFormatDialog
-
initializes the dialog with the given parent frame.
- outputItemSetsTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- OutputLogger - weka.core.logging中的类
-
A logger that logs all output on stdout and stderr to a file.
- OutputLogger() - 类的构造器 weka.core.logging.OutputLogger
- OutputLogger.OutputPrintStream - weka.core.logging中的类
-
A print stream class to capture all data from stdout and stderr.
- outputOffsetMultiplierTipText() - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Returns the tip text for this property
- outputPeek() - 类中的方法 weka.filters.Filter
-
Output an instance after filtering but do not remove from the output queue.
- outputPeek() - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Output an instance after filtering but do not remove from the output queue.
- outputPeek() - 类中的方法 weka.gui.streams.InstanceJoiner
-
Output an instance after filtering but do not remove from the output queue.
- outputPeek() - 类中的方法 weka.gui.streams.InstanceLoader
- outputPeek() - 接口中的方法 weka.gui.streams.InstanceProducer
- outputPerClassInfoRetrievalStatsTipText() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Return a tip text string for this property
- OutputPrintStream(OutputLogger, PrintStream) - 类的构造器 weka.core.logging.OutputLogger.OutputPrintStream
-
Default constructor.
- outputs(Vector) - 类中的静态方法 weka.gui.beans.BeanConnection
-
Returns a vector of BeanInstances that can be considered as outputs (or the right-hand side of a sub-flow)
- outputsContains(BeanInstance) - 类中的方法 weka.gui.beans.MetaBean
- outputTipText() - 类中的方法 weka.datagenerators.DataGenerator
-
Returns the tip text for this property
- outputTypeSet(int) - 类中的方法 weka.core.Debug.DBO
-
Return true if the outputtype is set
- outputValue(boolean) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this to get the output value of this unit.
- outputValue(boolean) - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Call this to get the output value of this unit.
- outputValue(NeuralNode) - 类中的方法 weka.classifiers.functions.neural.LinearUnit
-
This function calculates what the output value should be.
- outputValue(NeuralNode) - 接口中的方法 weka.classifiers.functions.neural.NeuralMethod
-
This function calculates what the output value should be.
- outputValue(NeuralNode) - 类中的方法 weka.classifiers.functions.neural.SigmoidUnit
-
This function calculates what the output value should be.
- outputWordCountsTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- OutputZipper - weka.experiment中的类
-
OutputZipper writes output to either gzipped files or to a multi entry zip file.
- OutputZipper(File) - 类的构造器 weka.experiment.OutputZipper
-
Constructor.
- OVAL - 类中的静态变量 weka.gui.visualize.VisualizePanelEvent
- overFrequencyThreshold(double) - 类中的方法 weka.associations.tertius.LiteralSet
-
Test if this LiteralSet has more counter-instances than the threshold.
- overFrequencyThreshold(double) - 类中的方法 weka.associations.tertius.Rule
-
Test if this rule is over the frequency threshold.
P
- p() - 类中的方法 weka.core.neighboursearch.CoverTree.CoverTreeNode
-
Returns the instance represented by the node.
- p(String) - 类中的静态方法 weka.core.Debug.DBO
-
prints out text.
- p1evl(double, double[], int) - 类中的静态方法 weka.core.Statistics
-
Evaluates the given polynomial of degree N at x.
- pace2(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Returns the pace2 estimate of a vector.
- pace4(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Returns the pace4 estimate of a vector.
- pace6(double) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Returns the pace6 estimate of a single value.
- pace6(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Returns the pace6 estimate of a vector.
- PaceMatrix - weka.classifiers.functions.pace中的类
-
Class for matrix manipulation used for pace regression.
- PaceMatrix(double[][]) - 类的构造器 weka.classifiers.functions.pace.PaceMatrix
-
Construct a PACE matrix from a 2-D array.
- PaceMatrix(double[][], int, int) - 类的构造器 weka.classifiers.functions.pace.PaceMatrix
-
Construct a PACE matrix quickly without checking arguments.
- PaceMatrix(double[], int) - 类的构造器 weka.classifiers.functions.pace.PaceMatrix
-
Construct a PaceMatrix from a one-dimensional packed array
- PaceMatrix(int, int) - 类的构造器 weka.classifiers.functions.pace.PaceMatrix
-
Construct an m-by-n PACE matrix of zeros.
- PaceMatrix(int, int, double) - 类的构造器 weka.classifiers.functions.pace.PaceMatrix
-
Construct an m-by-n constant PACE matrix.
- PaceMatrix(DoubleVector) - 类的构造器 weka.classifiers.functions.pace.PaceMatrix
-
Construct a PaceMatrix with a single column from a DoubleVector
- PaceMatrix(Matrix) - 类的构造器 weka.classifiers.functions.pace.PaceMatrix
-
Construct a PaceMatrix from a Matrix
- PaceRegression - weka.classifiers.functions中的类
-
Class for building pace regression linear models and using them for prediction.
- PaceRegression() - 类的构造器 weka.classifiers.functions.PaceRegression
- PACKAGE - 类中的静态变量 weka.core.stemmers.SnowballStemmer
-
the package name for snowball.
- PACKAGE_EXT - 类中的静态变量 weka.core.stemmers.SnowballStemmer
-
the package name where the stemmers are located.
- pad(String, String, int, boolean) - 类中的静态方法 weka.core.pmml.PMMLUtils
-
Utility method to left or right pad strings with arbitrary characters.
- PADDING_ZERO - 类中的静态变量 weka.filters.unsupervised.attribute.Wavelet
-
the type of padding: Zero padding
- paddingTipText() - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Returns the tip text for this property
- padLeft(String, int) - 类中的静态方法 weka.core.Utils
-
Pads a string to a specified length, inserting spaces on the left as required.
- padRight(String, int) - 类中的静态方法 weka.core.Utils
-
Pads a string to a specified length, inserting spaces on the right as required.
- PAGES - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
One or more page numbers or range of numbers, such as 42--111 or 7,41,73--97 or 43+ (the `+' in this last example indicates pages following that don't form a simple range).
- paint(Graphics) - 类中的方法 weka.gui.SplashWindow
-
Paints the image on the window.
- paintComponent(Graphics) - 类中的方法 weka.gui.AttributeVisualizationPanel
-
Paints this component
- paintComponent(Graphics) - 类中的方法 weka.gui.beans.BeanVisual
- paintComponent(Graphics) - 类中的方法 weka.gui.hierarchyvisualizer.HierarchyVisualizer
-
Updates the screen contents.
- paintComponent(Graphics) - 类中的方法 weka.gui.Main.BackgroundDesktopPane
-
draws the background image.
- paintComponent(Graphics) - 类中的方法 weka.gui.MemoryUsagePanel
-
draws the background image.
- paintComponent(Graphics) - 类中的方法 weka.gui.PropertyPanel
-
Paints the component, using the property editor's paint method.
- paintComponent(Graphics) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Updates the screen contents.
- paintComponent(Graphics) - 类中的方法 weka.gui.visualize.ClassPanel
-
Renders this component
- paintComponent(Graphics) - 类中的方法 weka.gui.visualize.Plot2D
-
Renders this component
- paintConnections(Graphics) - 类中的静态方法 weka.gui.beans.BeanConnection
-
Renders the connections and their names on the supplied graphics context
- paintLabels(Graphics) - 类中的静态方法 weka.gui.beans.BeanInstance
-
Renders the textual labels for the beans.
- paintValue(Graphics, Rectangle) - 类中的方法 weka.gui.CostMatrixEditor
-
Paints a graphical representation of the object.
- paintValue(Graphics, Rectangle) - 类中的方法 weka.gui.FileEditor
-
Paints a representation of the current Object.
- paintValue(Graphics, Rectangle) - 类中的方法 weka.gui.GenericArrayEditor
-
Paints a representation of the current classifier.
- paintValue(Graphics, Rectangle) - 类中的方法 weka.gui.GenericObjectEditor
-
Paints a representation of the current Object.
- paintValue(Graphics, Rectangle) - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Paints a graphical representation of the object.
- PairedCorrectedTTester - weka.experiment中的类
-
Behaves the same as PairedTTester, only it uses the corrected resampled t-test statistic.
- PairedCorrectedTTester() - 类的构造器 weka.experiment.PairedCorrectedTTester
- PairedStats - weka.experiment中的类
-
A class for storing stats on a paired comparison (t-test and correlation)
- PairedStats(double) - 类的构造器 weka.experiment.PairedStats
-
Creates a new PairedStats object with the supplied significance level.
- PairedStatsCorrected - weka.experiment中的类
-
A class for storing stats on a paired comparison.
- PairedStatsCorrected(double, double) - 类的构造器 weka.experiment.PairedStatsCorrected
-
Creates a new PairedStatsCorrected object with the supplied significance level and train/test ratio.
- PairedTTester - weka.experiment中的类
-
Calculates T-Test statistics on data stored in a set of instances.
- PairedTTester() - 类的构造器 weka.experiment.PairedTTester
- pairwiseCoupling(double[][], double[][]) - 类中的静态方法 weka.classifiers.meta.MultiClassClassifier
-
Implements pairwise coupling.
- pairwiseCoupling(double[][], double[][]) - 类中的方法 weka.classifiers.mi.MISMO
-
Implements pairwise coupling.
- parentClass - 类中的变量 weka.experiment.PropertyNode
-
The class of the object with this property
- parentNode() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the parent of this node
- ParentSet - weka.classifiers.bayes.net中的类
-
Helper class for Bayes Network classifiers.
- ParentSet() - 类的构造器 weka.classifiers.bayes.net.ParentSet
-
default constructor
- ParentSet(int) - 类的构造器 weka.classifiers.bayes.net.ParentSet
-
constructor
- ParentSet(ParentSet) - 类的构造器 weka.classifiers.bayes.net.ParentSet
-
copy constructor
- parentTipText() - 类中的方法 weka.datagenerators.ClusterDefinition
-
Returns the tip text for this property
- parentValue() - 类中的方法 weka.gui.HierarchyPropertyParser
-
The value in the parent node.
- parse() - 类中的方法 weka.gui.graphvisualizer.BIFParser
-
This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors
- parse() - 类中的方法 weka.gui.graphvisualizer.DotParser
-
This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors
- parseDate(String) - 类中的方法 weka.core.Attribute
-
Parses the given String as Date, according to the current format and returns the corresponding amount of milliseconds.
- parseMatlab(String) - 类中的静态方法 weka.classifiers.CostMatrix
-
creates a matrix from the given Matlab string.
- parseMatlab(String) - 类中的静态方法 weka.core.matrix.Matrix
-
creates a matrix from the given Matlab string.
- parseMatlab(String) - 类中的静态方法 weka.core.Matrix
-
已过时。creates a matrix from the given Matlab string.
- parsePath(String) - 类中的静态方法 weka.core.PropertyPath.Path
-
returns a path object based on the given path string
- Parser - weka.core.mathematicalexpression中的类
-
CUP v0.11a beta 20060608 generated parser.
- Parser - weka.filters.unsupervised.instance.subsetbyexpression中的类
-
CUP v0.11a beta 20060608 generated parser.
- Parser() - 类的构造器 weka.core.mathematicalexpression.Parser
-
Default constructor.
- Parser() - 类的构造器 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Default constructor.
- Parser(Scanner) - 类的构造器 weka.core.mathematicalexpression.Parser
-
Constructor which sets the default scanner.
- Parser(Scanner) - 类的构造器 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Constructor which sets the default scanner.
- Parser(Scanner, SymbolFactory) - 类的构造器 weka.core.mathematicalexpression.Parser
-
Constructor which sets the default scanner.
- Parser(Scanner, SymbolFactory) - 类的构造器 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Constructor which sets the default scanner.
- PART - weka.classifiers.rules中的类
-
Class for generating a PART decision list.
- PART() - 类的构造器 weka.classifiers.rules.PART
- PART_PROPERTY - 类中的静态变量 weka.associations.tertius.IndividualLiteral
- partFileTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- partition(Instances, int) - 类中的静态方法 weka.classifiers.rules.RuleStats
-
Patition the data into 2, first of which has (numFolds-1)/numFolds of the data and the second has 1/numFolds of the data
- PartitionedMultiFilter - weka.filters.unsupervised.attribute中的类
-
A filter that applies filters on subsets of attributes and assembles the output into a new dataset.
- PartitionedMultiFilter() - 类的构造器 weka.filters.unsupervised.attribute.PartitionedMultiFilter
- partitionOptions(String[]) - 类中的静态方法 weka.classifiers.bayes.BayesNet
-
Returns the secondary set of options (if any) contained in the supplied options array.
- partitionOptions(String[]) - 类中的静态方法 weka.core.Utils
-
Returns the secondary set of options (if any) contained in the supplied options array.
- passesTest(Instance) - 类中的方法 weka.datagenerators.Test
-
Determines whether an instance passes the test.
- passwordTipText() - 类中的方法 weka.core.converters.DatabaseLoader
-
the tip text for this property
- passwordTipText() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the tip text for this property.
- passwordTipText() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns the tip text for this property.
- paste(String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Apply paste operation with XMLBIF fragment.
- Path(String) - 类的构造器 weka.core.PropertyPath.Path
-
uses the given dot-path
- Path(String[]) - 类的构造器 weka.core.PropertyPath.Path
-
uses the given array as elements for the path
- Path(Vector) - 类的构造器 weka.core.PropertyPath.Path
-
uses the vector with PathElement objects to initialize with
- PathElement(String) - 类的构造器 weka.core.PropertyPath.PathElement
-
initializes the path element with the given property
- pattern(int, int) - 类中的静态方法 weka.core.matrix.FloatingPointFormat
- patternTipText() - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Returns the tip text for this property
- pchisq(double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the cumulative probability of the Chi-squared distribution
- pchisq(double, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the cumulative probability of the noncentral Chi-squared distribution.
- pchisq(double, DoubleVector) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the cumulative probability of a set of noncentral Chi-squared distributions.
- pctCorrect() - 类中的方法 weka.classifiers.Evaluation
-
Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).
- pctIncorrect() - 类中的方法 weka.classifiers.Evaluation
-
Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).
- pctUnclassified() - 类中的方法 weka.classifiers.Evaluation
-
Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).
- PDF - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
A link to a postscript file.
- peek() - 类中的方法 weka.core.Queue
-
Gets object from the front of the queue.
- perBag(int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns number of (possibly fractional) instances in given bag.
- percentageTipText() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns the tip text for this property.
- percentageTipText() - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Returns the tip text for this property
- percentAttributesUsed() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Returns the fraction of all attributes in the data that are used in the logistic model (in percent).
- percentThresholdTipText() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns a tip text for this property suitable for display in the GUI
- percentTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Returns the tip text for this property
- percentTipText() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns the tip text for this property
- percentToEliminatePerIterationTipText() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns a tip text for this property suitable for display in the GUI
- perClass(int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns number of (possibly fractional) instances of given class.
- perClassPerBag(int, int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns number of (possibly fractional) instances of given class in given bag.
- PerformanceStats - weka.core.neighboursearch中的类
-
The class that measures the performance of a nearest neighbour search (NNS) algorithm.
- PerformanceStats() - 类的构造器 weka.core.neighboursearch.PerformanceStats
-
default constructor.
- performPredictionTipText() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns the tip text for this property
- performRankingTipText() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the tip text for this property
- performRankingTipText() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the tip text for this property
- performRequest(String) - 类中的方法 weka.gui.beans.Associator
-
Perform a particular request
- performRequest(String) - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Perform a named user request
- performRequest(String) - 类中的方法 weka.gui.beans.Classifier
-
Perform a particular request
- performRequest(String) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Perform the named request
- performRequest(String) - 类中的方法 weka.gui.beans.Clusterer
-
Perform a particular request
- performRequest(String) - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Perform the named request
- performRequest(String) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- performRequest(String) - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Perform the named request
- performRequest(String) - 类中的方法 weka.gui.beans.DataVisualizer
-
Describe
performRequest
method here. - performRequest(String) - 类中的方法 weka.gui.beans.Filter
-
Perform the named request
- performRequest(String) - 类中的方法 weka.gui.beans.GraphViewer
-
Perform the named request
- performRequest(String) - 类中的方法 weka.gui.beans.MetaBean
-
Perform a particular request
- performRequest(String) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Describe
performRequest
method here. - performRequest(String) - 类中的方法 weka.gui.beans.ScatterPlotMatrix
-
Perform a named user request
- performRequest(String) - 类中的方法 weka.gui.beans.StripChart
-
Describe
performRequest
method here. - performRequest(String) - 类中的方法 weka.gui.beans.TextViewer
-
Perform the named request
- performRequest(String) - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Perform the named request
- performRequest(String) - 接口中的方法 weka.gui.beans.UserRequestAcceptor
-
Perform the named request
- periodicPruningTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- perturbationFractionTipText() - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Returns the tip text for this property
- phaseIID(int, int[][]) - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
See Sugiyama et al.
- phaseIIU(int, int[][]) - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
See Sugiyama et al.
- phaseIU(int, int[][]) - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
See Sugiyama et al.
- PHDTHESIS - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
A PhD thesis.
- PI - 类中的静态变量 weka.core.xml.XMLDocument
-
the parsing instructions "<?xml version=\"1.0\" encoding=\"utf-8\"?>" (may not show up in Javadoc due to tags!).
- PKIDiscretize - weka.filters.unsupervised.attribute中的类
-
Discretizes numeric attributes using equal frequency binning, where the number of bins is equal to the square root of the number of non-missing values.
For more information, see:
Ying Yang, Geoffrey I. - PKIDiscretize() - 类的构造器 weka.filters.unsupervised.attribute.PKIDiscretize
- place(Node) - 接口中的方法 weka.gui.treevisualizer.NodePlace
-
The function to call to postion the tree that starts at Node r
- place(Node) - 类中的方法 weka.gui.treevisualizer.PlaceNode1
-
Call this function to have each node in the tree starting at 'r' placed in a visual (not logical, they already are) tree position.
- place(Node) - 类中的方法 weka.gui.treevisualizer.PlaceNode2
-
The Funtion to call to have the nodes arranged.
- PlaceNode1 - weka.gui.treevisualizer中的类
-
This class will place the Nodes of a tree.
- PlaceNode1() - 类的构造器 weka.gui.treevisualizer.PlaceNode1
- PlaceNode2 - weka.gui.treevisualizer中的类
-
This class will place the Nodes of a tree.
- PlaceNode2() - 类的构造器 weka.gui.treevisualizer.PlaceNode2
- PLAINTEXT_ENDTAG - 类中的静态变量 weka.core.TechnicalInformationHandlerJavadoc
-
the end comment tag for inserting the generated BibTex
- PLAINTEXT_STARTTAG - 类中的静态变量 weka.core.TechnicalInformationHandlerJavadoc
-
the start comment tag for inserting the generated BibTex
- pln(String) - 类中的静态方法 weka.core.Debug.DBO
-
prints out text + endofline.
- Plot2D - weka.gui.visualize中的类
-
This class plots datasets in two dimensions.
- Plot2D() - 类的构造器 weka.gui.visualize.Plot2D
-
Constructor
- Plot2DCompanion - weka.gui.visualize中的接口
-
Interface for classes that need to draw to the Plot2D panel *before* Plot2D renders anything (eg.
- PlotData2D - weka.gui.visualize中的类
-
This class is a container for plottable data.
- PlotData2D(Instances) - 类的构造器 weka.gui.visualize.PlotData2D
-
Construct a new PlotData2D using the supplied instances
- plotTrainingData() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Render the training points on-screen.
- plotTrainingData() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Plots the training data on-screen.
- PLSClassifier - weka.classifiers.functions中的类
-
A wrapper classifier for the PLSFilter, utilizing the PLSFilter's ability to perform predictions.
- PLSClassifier() - 类的构造器 weka.classifiers.functions.PLSClassifier
- PLSFilter - weka.filters.supervised.attribute中的类
-
Runs Partial Least Square Regression over the given instances and computes the resulting beta matrix for prediction.
By default it replaces missing values and centers the data.
For more information see:
Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002). - PLSFilter() - 类的构造器 weka.filters.supervised.attribute.PLSFilter
-
default constructor
- PLURAL_DUMMY - 接口中的静态变量 weka.gui.graphvisualizer.GraphConstants
-
PLURAL_DUMMY node - node with more than one outgoing edge i.e.
- plus(double) - 类中的方法 weka.core.matrix.DoubleVector
-
Adds a value to all the elements
- plus(DiscreteFunction) - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Returns the combined of two discrete functions
- plus(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Adds another vector element by element
- plus(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
C = A + B
- PLUS - 接口中的静态变量 weka.core.mathematicalexpression.sym
- PLUS - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- PLUS_SHAPE - 类中的静态变量 weka.gui.visualize.Plot2D
- plusEquals(double) - 类中的方法 weka.core.matrix.DoubleVector
-
Adds a value to all the elements in place
- plusEquals(DiscreteFunction) - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Returns the combined of two discrete functions.
- plusEquals(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Adds another vector in place element by element
- plusEquals(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
A = A + B
- pmiss - 类中的变量 weka.classifiers.lazy.kstar.KStarCache.TableEntry
-
transformation probability to missing value
- PMMethod - 类中的静态变量 weka.classifiers.functions.pace.MixtureDistribution
-
The probability-measure-based method
- PMML_FILE_EXTENSION - 类中的静态变量 weka.gui.explorer.ClassifierPanel
-
The filename extension that should be used for PMML xml files
- PMMLClassifier - weka.classifiers.pmml.consumer中的类
-
Abstract base class for all PMML classifiers.
- PMMLFactory - weka.core.pmml中的类
-
This class is a factory class for reading/writing PMML models
- PMMLFactory() - 类的构造器 weka.core.pmml.PMMLFactory
- PMMLModel - weka.core.pmml中的接口
-
Interface for all PMML models
- PMMLUtils - weka.core.pmml中的类
-
Utility routines.
- PMMLUtils() - 类的构造器 weka.core.pmml.PMMLUtils
- PNGWriter - weka.gui.visualize中的类
-
This class takes any JComponent and outputs it to a PNG-file.
- PNGWriter() - 类的构造器 weka.gui.visualize.PNGWriter
-
initializes the object
- PNGWriter(JComponent) - 类的构造器 weka.gui.visualize.PNGWriter
-
initializes the object with the given Component
- PNGWriter(JComponent, File) - 类的构造器 weka.gui.visualize.PNGWriter
-
initializes the object with the given Component and filename
- pnorm(double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the cumulative probability of the standard normal.
- pnorm(double, double, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the cumulative probability of a normal distribution.
- pnorm(double, DoubleVector, double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the cumulative probability of a set of normal distributions with different means.
- PointsClosestToFurthestChildren - weka.core.neighboursearch.balltrees中的类
-
Implements the Moore's method to split a node of a ball tree.
For more information please see section 2 of the 1st and 3.2.3 of the 2nd:
Andrew W. - PointsClosestToFurthestChildren() - 类的构造器 weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren
-
Constructor.
- PointsClosestToFurthestChildren(int[], Instances, EuclideanDistance) - 类的构造器 weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren
-
Constructor.
- PoissonEstimator - weka.estimators中的类
-
Simple probability estimator that places a single Poisson distribution over the observed values.
- PoissonEstimator() - 类的构造器 weka.estimators.PoissonEstimator
- POLYGON - 类中的静态变量 weka.gui.visualize.VisualizePanelEvent
- PolyKernel - weka.classifiers.functions.supportVector中的类
-
The polynomial kernel : K(x, y) = <x, y>^p or K(x, y) = (<x, y>+1)^p
- PolyKernel() - 类的构造器 weka.classifiers.functions.supportVector.PolyKernel
-
default constructor - does nothing.
- PolyKernel(Instances, int, double, boolean) - 类的构造器 weka.classifiers.functions.supportVector.PolyKernel
-
Creates a new
PolyKernel
instance. - pop() - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Pops (removes) the first (last added) element in the stack.
- pop() - 类中的方法 weka.core.Queue
-
Pops an object from the front of the queue.
- populationSizeTipText() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns the tip text for this property
- populationSizeTipText() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns the tip text for this property
- populationSizeTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- populationSizeTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- POS - 类中的静态变量 weka.associations.tertius.Literal
- position() - 类中的方法 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Returns the position of the split in the sorted values.
- position() - 接口中的方法 weka.classifiers.trees.m5.SplitEvaluate
-
Returns the position of the split in the sorted values.
- position() - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Returns the position of the split in the sorted values.
- positive() - 类中的方法 weka.associations.tertius.Literal
- positiveDiagonal(PaceMatrix, IntVector) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Sets all diagonal elements to be positive (or nonnegative) without changing the least squares solution
- positiveIndexTipText() - 类中的方法 weka.associations.FPGrowth
-
Tip text for this property suitable for displaying in the GUI.
- positives(int) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- positivesForSubsetOfInterest() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- postProcess() - 类中的方法 weka.experiment.AveragingResultProducer
-
When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
- postProcess() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Perform any postprocessing.
- postProcess() - 类中的方法 weka.experiment.DatabaseResultProducer
-
When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
- postProcess() - 类中的方法 weka.experiment.Experiment
-
Signals that the experiment is finished running, so that cleanup can be done.
- postProcess() - 类中的方法 weka.experiment.LearningRateResultProducer
-
When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
- postProcess() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Perform any postprocessing.
- postProcess() - 类中的方法 weka.experiment.RemoteExperiment
-
overides the one in Experiment
- postProcess() - 接口中的方法 weka.experiment.ResultProducer
-
Perform any postprocessing.
- postProcess(int[]) - 类中的方法 weka.attributeSelection.ASEvaluation
-
Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.
- postProcess(int[]) - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Calls locallyPredictive in order to include locally predictive attributes (if requested).
- postProcess(int[]) - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.
- postProcess(int[]) - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
- postProcess(int[]) - 类中的方法 weka.attributeSelection.OneRAttributeEval
- postProcess(int[]) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
- postProcess(ResultProducer) - 类中的方法 weka.experiment.AveragingResultProducer
-
When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
- postProcess(ResultProducer) - 类中的方法 weka.experiment.CSVResultListener
-
Perform any postprocessing.
- postProcess(ResultProducer) - 类中的方法 weka.experiment.DatabaseResultListener
-
Perform any postprocessing.
- postProcess(ResultProducer) - 类中的方法 weka.experiment.DatabaseResultProducer
-
When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
- postProcess(ResultProducer) - 类中的方法 weka.experiment.InstancesResultListener
-
Perform any postprocessing.
- postProcess(ResultProducer) - 类中的方法 weka.experiment.LearningRateResultProducer
-
When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
- postProcess(ResultProducer) - 接口中的方法 weka.experiment.ResultListener
-
Perform any postprocessing.
- postProcessDistances(double[]) - 接口中的方法 weka.core.DistanceFunction
-
Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
- postProcessDistances(double[]) - 类中的方法 weka.core.EuclideanDistance
-
Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
- postProcessDistances(double[]) - 类中的方法 weka.core.NormalizableDistance
-
Does nothing, derived classes may override it though.
- PostProcessor() - 类的构造器 weka.core.CheckScheme.PostProcessor
- PostProcessor() - 类的构造器 weka.estimators.CheckEstimator.PostProcessor
- PostscriptGraphics - weka.gui.visualize中的类
-
The PostscriptGraphics class extends the Graphics2D class to produce an encapsulated postscript file rather than on-screen display.
- PostscriptGraphics(int, int, OutputStream) - 类的构造器 weka.gui.visualize.PostscriptGraphics
-
Constructor Creates a new PostscriptGraphics object, given dimensions and output file.
- PostscriptWriter - weka.gui.visualize中的类
-
This class takes any Component and outputs it to a Postscript file.
- PostscriptWriter() - 类的构造器 weka.gui.visualize.PostscriptWriter
-
initializes the object
- PostscriptWriter(JComponent) - 类的构造器 weka.gui.visualize.PostscriptWriter
-
initializes the object with the given Component
- PostscriptWriter(JComponent, File) - 类的构造器 weka.gui.visualize.PostscriptWriter
-
initializes the object with the given Component and filename
- potential(int, double, double[], double[], boolean) - 类中的方法 weka.classifiers.rules.RuleStats
-
Calculate the potential to decrease DL of the ruleset, i.e.
- PotentialClassIgnorer - weka.filters.unsupervised.attribute中的类
-
This filter should be extended by other unsupervised attribute filters to allow processing of the class attribute if that's required.
- PotentialClassIgnorer() - 类的构造器 weka.filters.unsupervised.attribute.PotentialClassIgnorer
- POW - 接口中的静态变量 weka.core.mathematicalexpression.sym
- POW - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- precision(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the precision with respect to a particular class.
- PRECISION - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
precision
- PRECISION_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: Precision
- PrecomputedKernelMatrixKernel - weka.classifiers.functions.supportVector中的类
-
This kernel is based on a static kernel matrix that is read from a file.
- PrecomputedKernelMatrixKernel() - 类的构造器 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
- PreConstructedLinearModel - weka.classifiers.trees.m5中的类
-
This class encapsulates a linear regression function.
- PreConstructedLinearModel(double[], double) - 类的构造器 weka.classifiers.trees.m5.PreConstructedLinearModel
-
Constructor
- Predicate - weka.associations.tertius中的类
- Predicate(String, int, boolean) - 类的构造器 weka.associations.tertius.Predicate
- predicted() - 类中的方法 weka.classifiers.evaluation.NominalPrediction
-
Gets the predicted class value.
- predicted() - 类中的方法 weka.classifiers.evaluation.NumericPrediction
-
Gets the predicted class value.
- predicted() - 接口中的方法 weka.classifiers.evaluation.Prediction
-
Gets the predicted class value.
- predictInterval(Instance, double) - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Predicts a confidence interval for the given instance and confidence level.
- predictInterval(Instance, double) - 接口中的方法 weka.classifiers.IntervalEstimator
-
Returns an N*2 array, where N is the number of possible classes, that estimate the boundaries for the confidence interval with a confidence level specified by the second parameter.
- Prediction - weka.classifiers.evaluation中的接口
-
Encapsulates a single evaluatable prediction: the predicted value plus the actual class value.
- PredictionAppender - weka.gui.beans中的类
-
Bean that can can accept batch or incremental classifier events and produce dataset or instance events which contain instances with predictions appended.
- PredictionAppender() - 类的构造器 weka.gui.beans.PredictionAppender
-
Creates a new
PredictionAppender
instance. - PredictionAppenderBeanInfo - weka.gui.beans中的类
-
Bean info class for PredictionAppender.
- PredictionAppenderBeanInfo() - 类的构造器 weka.gui.beans.PredictionAppenderBeanInfo
- PredictionAppenderCustomizer - weka.gui.beans中的类
-
GUI Customizer for the prediction appender bean
- PredictionAppenderCustomizer() - 类的构造器 weka.gui.beans.PredictionAppenderCustomizer
- PredictionNode - weka.classifiers.trees.adtree中的类
-
Class representing a prediction node in an alternating tree.
- PredictionNode(double) - 类的构造器 weka.classifiers.trees.adtree.PredictionNode
-
Creates a new prediction node.
- predictions() - 类中的方法 weka.classifiers.Evaluation
-
Returns the predictions that have been collected.
- PredictiveApriori - weka.associations中的类
-
Class implementing the predictive apriori algorithm to mine association rules.
It searches with an increasing support threshold for the best 'n' rules concerning a support-based corrected confidence value.
For more information see:
Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence. - PredictiveApriori() - 类的构造器 weka.associations.PredictiveApriori
-
Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
- predictiveError(Instances) - 类中的方法 weka.classifiers.trees.LADTree
- prefix() - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns tree in prefix order.
- prefix() - 类中的方法 weka.classifiers.trees.J48
-
Returns tree in prefix order.
- prefix() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns tree in prefix order.
- prefix() - 接口中的方法 weka.core.Matchable
-
Returns a string that describes a tree representing the object in prefix order.
- PREFIX_CLASSIFIER - 类中的静态变量 weka.classifiers.meta.GridSearch
-
the prefix to indicate that the option is for the classifier
- PREFIX_FILTER - 类中的静态变量 weka.classifiers.meta.GridSearch
-
the prefix to indicate that the option is for the filter
- premise() - 类中的方法 weka.associations.RuleItem
-
Gets the premise of a rule
- prePlot(Graphics) - 接口中的方法 weka.gui.visualize.Plot2DCompanion
-
Something to be drawn before the plot itself
- preprocess(Instances, int) - 类中的方法 weka.classifiers.mi.MINND
-
Pre-process the given exemplar according to the other exemplars in the given exemplars.
- preProcess() - 类中的方法 weka.experiment.AveragingResultProducer
-
Prepare to generate results.
- preProcess() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Prepare to generate results.
- preProcess() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Prepare to generate results.
- preProcess() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Prepare to generate results.
- preProcess() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Prepare to generate results.
- preProcess() - 接口中的方法 weka.experiment.ResultProducer
-
Prepare to generate results.
- preProcess(ResultProducer) - 类中的方法 weka.experiment.AveragingResultProducer
-
Prepare for the results to be received.
- preProcess(ResultProducer) - 类中的方法 weka.experiment.CSVResultListener
-
Prepare for the results to be received.
- preProcess(ResultProducer) - 类中的方法 weka.experiment.DatabaseResultListener
-
Prepare for the results to be received.
- preProcess(ResultProducer) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Prepare for the results to be received.
- preProcess(ResultProducer) - 类中的方法 weka.experiment.InstancesResultListener
-
Prepare for the results to be received.
- preProcess(ResultProducer) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Prepare for the results to be received.
- preProcess(ResultProducer) - 接口中的方法 weka.experiment.ResultListener
-
Prepare for the results to be received.
- preprocessData() - 类中的方法 weka.classifiers.mi.CitationKNN
-
Calculates the normalization of each attribute.
- PREPROCESSING_CENTER - 类中的静态变量 weka.filters.supervised.attribute.PLSFilter
-
the type of preprocessing: Center
- PREPROCESSING_NONE - 类中的静态变量 weka.filters.supervised.attribute.PLSFilter
-
the type of preprocessing: None
- PREPROCESSING_STANDARDIZE - 类中的静态变量 weka.filters.supervised.attribute.PLSFilter
-
the type of preprocessing: Standardize
- preprocessingTipText() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns the tip text for this property
- preprocessingTipText() - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Returns the tip text for this property
- PreprocessPanel - weka.gui.explorer中的类
-
This panel controls simple preprocessing of instances.
- PreprocessPanel() - 类的构造器 weka.gui.explorer.PreprocessPanel
-
Creates the instances panel with no initial instances.
- preserveInstancesOrderTipText() - 类中的方法 weka.clusterers.SimpleKMeans
-
Returns the tip text for this property
- previous() - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
- PRICE - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The price of the document.
- PrincipalComponents - weka.attributeSelection中的类
-
Performs a principal components analysis and transformation of the data.
- PrincipalComponents - weka.filters.unsupervised.attribute中的类
-
Performs a principal components analysis and transformation of the data.
Dimensionality reduction is accomplished by choosing enough eigenvectors to account for some percentage of the variance in the original data -- default 0.95 (95%).
Based on code of the attribute selection scheme 'PrincipalComponents' by Mark Hall and Gabi Schmidberger. - PrincipalComponents() - 类的构造器 weka.attributeSelection.PrincipalComponents
- PrincipalComponents() - 类的构造器 weka.filters.unsupervised.attribute.PrincipalComponents
- print() - 类中的方法 weka.classifiers.bayes.net.ADNode
-
print is used for debugging only and shows the ADTree in ASCII graphics
- print() - 类中的方法 weka.core.xml.XMLDocument
-
prints the current DOM document to standard out.
- print(boolean) - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints the given boolean to the streams.
- print(boolean) - 类中的方法 weka.core.Tee
-
prints the given boolean to the streams.
- print(char) - 类中的方法 weka.core.Tee
-
prints the given char to the streams.
- print(char[]) - 类中的方法 weka.core.Tee
-
prints the given char array to the streams.
- print(double) - 类中的方法 weka.core.Tee
-
prints the given double to the streams.
- print(float) - 类中的方法 weka.core.Tee
-
prints the given float to the streams.
- print(int) - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints the given int to the streams.
- print(int) - 类中的方法 weka.core.Tee
-
prints the given int to the streams.
- print(int, int) - 类中的方法 weka.core.matrix.Matrix
-
Print the matrix to stdout.
- print(long) - 类中的方法 weka.core.Tee
-
prints the given long to the streams.
- print(PrintWriter, int, int) - 类中的方法 weka.core.matrix.Matrix
-
Print the matrix to the output stream.
- print(PrintWriter, NumberFormat, int) - 类中的方法 weka.core.matrix.Matrix
-
Print the matrix to the output stream.
- print(Object) - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints the given object to the streams.
- print(Object) - 类中的方法 weka.core.Tee
-
prints the given object to the streams.
- print(String) - 类中的方法 weka.classifiers.bayes.net.VaryNode
-
print is used for debugging only, called from ADNode
- print(String) - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints the given string to the streams.
- print(String) - 类中的方法 weka.core.Tee
-
prints the given string to the streams.
- print(NumberFormat, int) - 类中的方法 weka.core.matrix.Matrix
-
Print the matrix to stdout.
- print_hash_code() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval.hashKey
-
Prints the hash code
- print_hash_code() - 类中的方法 weka.classifiers.rules.DecisionTableHashKey
-
Prints the hash code
- PrintableComponent - weka.gui.visualize中的类
-
This class extends the component which is handed over in the constructor by a print dialog.
- PrintableComponent(JComponent) - 类的构造器 weka.gui.visualize.PrintableComponent
-
initializes the panel.
- PrintableHandler - weka.gui.visualize中的接口
-
This interface is for all JComponent classes that provide the ability to print itself to a file.
- PrintablePanel - weka.gui.visualize中的类
-
This Panel enables the user to print the panel to various file formats.
- PrintablePanel() - 类的构造器 weka.gui.visualize.PrintablePanel
-
initializes the panel
- printAllModels() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Print all the linear models at the learf (debugging purposes)
- printClassifications(Classifier, Instances, ConverterUtils.DataSource, int, Range, boolean, StringBuffer) - 类中的静态方法 weka.classifiers.Evaluation
-
Prints the predictions for the given dataset into a supplied StringBuffer
- printClassifications(Classifier, Instances, ConverterUtils.DataSource, int, Range, StringBuffer) - 类中的静态方法 weka.classifiers.Evaluation
-
Prints the predictions for the given dataset into a String variable.
- printElements() - 类中的方法 weka.classifiers.functions.supportVector.SMOset
-
Prints all the current elements in the set.
- printFeatures() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns a string description of the features selected
- printInsts(int, int) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
For printing indices in some given portion of the master index array.
- printLeafModels() - 类中的方法 weka.classifiers.trees.j48.NBTreeClassifierTree
-
Print the models at the leaves
- printLeafModels() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
print all leaf models
- printList(MiddleOutConstructor.MyIdxList) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
For printing indices in a given point list.
- println() - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints a new line to the streams.
- println() - 类中的方法 weka.core.Tee
-
prints a new line to the streams.
- println(boolean) - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints the given boolean to the streams.
- println(boolean) - 类中的方法 weka.core.Tee
-
prints the given boolean to the streams.
- println(char) - 类中的方法 weka.core.Tee
-
prints the given char to the streams.
- println(char[]) - 类中的方法 weka.core.Tee
-
prints the given char array to the streams.
- println(double) - 类中的方法 weka.core.Tee
-
prints the given double to the streams.
- println(float) - 类中的方法 weka.core.Tee
-
prints the given float to the streams.
- println(int) - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints the given int to the streams.
- println(int) - 类中的方法 weka.core.Tee
-
prints the given int to the streams.
- println(long) - 类中的方法 weka.core.Tee
-
prints the given long to the streams.
- println(Object) - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints the given object to the streams (for Throwables we print the stack trace).
- println(Object) - 类中的方法 weka.core.Tee
-
prints the given object to the streams (for Throwables we print the stack trace).
- println(String) - 类中的方法 weka.core.logging.OutputLogger.OutputPrintStream
-
prints the given string to the streams.
- println(String) - 类中的方法 weka.core.Tee
-
prints the given string to the streams.
- printNewickTipText() - 类中的方法 weka.clusterers.HierarchicalClusterer
- printNodeLinearModel() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
print the linear model at this node
- printSetOfSequences(FastVector) - 类中的静态方法 weka.associations.gsp.Sequence
-
Prints a set of Sequences as String output.
- printStackTrace() - 类中的方法 weka.core.Debug.Random
-
prints the current stacktrace
- printSubset(ScatterSearchV1.Subset) - 类中的方法 weka.attributeSelection.ScatterSearchV1
- Prior - weka.classifiers.bayes.blr中的类
-
This is an interface to plug various priors into the Bayesian Logistic Regression Model.
- Prior() - 类的构造器 weka.classifiers.bayes.blr.Prior
- PriorClass - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Distribution Prior class
- priorClassTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- priorEntropy() - 类中的方法 weka.classifiers.Evaluation
-
Calculate the entropy of the prior distribution
- PriorEstimation - weka.associations中的类
-
Class implementing the prior estimattion of the predictive apriori algorithm for mining association rules.
- PriorEstimation(Instances, int, int, boolean) - 类的构造器 weka.associations.PriorEstimation
-
Constructor
- PriorityQueue - weka.clusterers.forOPTICSAndDBScan.Utils中的类
-
PriorityQueue.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 27, 2004
Time: 5:36:35 PM
$ Revision 1.4 $ - PriorityQueue() - 类的构造器 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue
-
Creates a new PriorityQueue backed on a binary heap.
- PriorityQueueElement - weka.clusterers.forOPTICSAndDBScan.Utils中的类
-
PriorityQueueElement.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 31, 2004
Time: 6:43:18 PM
$ Revision 1.4 $ - PriorityQueueElement(double, Object) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueueElement
- Prism - weka.classifiers.rules中的类
-
Class for building and using a PRISM rule set for classification.
- Prism() - 类的构造器 weka.classifiers.rules.Prism
- prob(int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns relative frequency of class over all bags.
- prob(int, int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns relative frequency of class for given bag.
- PROB_COST_FUNC_NAME - 类中的静态变量 weka.classifiers.evaluation.CostCurve
-
attribute name: Probability Cost Function
- probabilityEstimatesTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- probabilityEstimatesTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- probabilityMatrix(DoubleVector, PaceMatrix) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
- probabilityMatrix(DoubleVector, PaceMatrix) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
- probabilityMatrix(DoubleVector, PaceMatrix) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
- probRound(double, Random) - 类中的静态方法 weka.core.Utils
-
Rounds a double to the next nearest integer value in a probabilistic fashion (e.g.
- probToLogOdds(double) - 类中的静态方法 weka.core.Utils
-
Returns the log-odds for a given probabilitiy.
- PROCEEDINGS - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
The proceedings of a conference.
- process(boolean[][], BayesNet) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
- process(Instances) - 类中的方法 weka.core.CheckScheme.PostProcessor
-
Provides a hook for derived classes to further modify the data.
- processClassifierPrediction(Instance, Classifier, Evaluation, Instances, FastVector, FastVector) - 类中的静态方法 weka.gui.explorer.ClassifierPanel
-
Process a classifier's prediction for an instance and update a set of plotting instances and additional plotting info.
- processColour(String, Color) - 类中的静态方法 weka.gui.visualize.VisualizeUtils
-
Parses a string containing either a named colour or r,g,b values.
- processFile(String) - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
processFile reads a BIFXML file and initializes a Bayes Net
- processFilename(String) - 类中的方法 weka.gui.Loader
-
returns the processed filename, i.e.
- PROCESSING - 类中的静态变量 weka.experiment.TaskStatusInfo
- processKeyString(String) - 类中的静态方法 weka.experiment.DatabaseUtils
-
processes the string in such a way that it can be stored in the database, i.e., it changes backslashes into slashes and doubles single quotes.
- processString(String) - 类中的方法 weka.classifiers.bayes.net.BIFReader
- PRODUCT_RULE - 类中的静态变量 weka.classifiers.meta.Vote
-
combination rule: Product of Probabilities (only nominal classes)
- production_table() - 类中的方法 weka.core.mathematicalexpression.Parser
-
Access to production table.
- production_table() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Access to production table.
- projectionFilterTipText() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns the tip text for this property
- PROPERTIES_FILE - 类中的静态变量 weka.core.Capabilities
-
the properties file for managing the tests
- PROPERTIES_FILE - 类中的静态变量 weka.core.logging.Logger
-
the properties file.
- PROPERTIES_FILE - 类中的静态变量 weka.gui.treevisualizer.TreeVisualizer
-
the props file.
- property - 类中的变量 weka.experiment.PropertyNode
-
Other info about the property
- PROPERTY_FILE - 类中的静态变量 weka.core.Copyright
-
the copyright file
- PROPERTY_FILE - 类中的静态变量 weka.experiment.DatabaseUtils
-
The name of the properties file.
- PROPERTY_FILE - 类中的静态变量 weka.gui.experiment.ExperimenterDefaults
-
The name of the properties file
- PROPERTY_FILE - 类中的静态变量 weka.gui.explorer.ExplorerDefaults
-
The name of the properties file.
- PROPERTY_FILE - 类中的静态变量 weka.gui.LookAndFeel
-
The name of the properties file
- propertyChange(PropertyChangeEvent) - 类中的方法 weka.gui.beans.KnowledgeFlowApp
-
Accept property change events
- propertyChange(PropertyChangeEvent) - 类中的方法 weka.gui.PropertySheetPanel
-
Updates the property sheet panel with a changed property and also passed the event along.
- PropertyDialog - weka.gui中的类
-
Support for PropertyEditors with custom editors: puts the editor into a separate frame.
- PropertyDialog(Dialog, PropertyEditor) - 类的构造器 weka.gui.PropertyDialog
-
Creates the (screen-centered) editor dialog.
- PropertyDialog(Dialog, PropertyEditor, int, int) - 类的构造器 weka.gui.PropertyDialog
-
Creates the editor dialog at the given position.
- PropertyDialog(Frame, PropertyEditor) - 类的构造器 weka.gui.PropertyDialog
-
Creates the (screen-centered) editor dialog.
- PropertyDialog(Frame, PropertyEditor, int, int) - 类的构造器 weka.gui.PropertyDialog
-
Creates the editor dialog at the given position.
- PropertyDialog(PropertyEditor, int, int) - 类的构造器 weka.gui.PropertyDialog
-
已过时。instead of this constructor, one should use the constructors with an explicit owner (either derived from
java.awt.Dialog
or fromjava.awt.Frame
) or, if none available, using(Frame) null
as owner. - PropertyHandler - weka.core.xml中的类
-
This class stores information about properties to ignore or properties that are allowed for a certain class.
- PropertyHandler() - 类的构造器 weka.core.xml.PropertyHandler
-
initializes the handling
- PropertyNode - weka.experiment中的类
-
Stores information on a property of an object: the class of the object with the property; the property descriptor, and the current value.
- PropertyNode(Object) - 类的构造器 weka.experiment.PropertyNode
-
Creates a mostly empty property.
- PropertyNode(Object, PropertyDescriptor, Class) - 类的构造器 weka.experiment.PropertyNode
-
Creates a fully specified property node.
- PropertyPanel - weka.gui中的类
-
Support for drawing a property value in a component.
- PropertyPanel(PropertyEditor) - 类的构造器 weka.gui.PropertyPanel
-
Create the panel with the supplied property editor.
- PropertyPanel(PropertyEditor, boolean) - 类的构造器 weka.gui.PropertyPanel
-
Create the panel with the supplied property editor, optionally ignoring any custom panel the editor can provide.
- PropertyPath - weka.core中的类
-
A helper class for accessing properties in nested objects, e.g., accessing the "getRidge" method of a LinearRegression classifier part of MultipleClassifierCombiner, e.g., Vote.
- PropertyPath() - 类的构造器 weka.core.PropertyPath
- PropertyPath.Path - weka.core中的类
-
Contains a (property) path structure
- PropertyPath.PathElement - weka.core中的类
-
Represents a single element of a property path
- PropertySelectorDialog - weka.gui中的类
-
Allows the user to select any (supported) property of an object, including properties that any of it's property values may have.
- PropertySelectorDialog(Frame, Object) - 类的构造器 weka.gui.PropertySelectorDialog
-
Create the property selection dialog.
- PropertySheetPanel - weka.gui中的类
-
Displays a property sheet where (supported) properties of the target object may be edited.
- PropertySheetPanel() - 类的构造器 weka.gui.PropertySheetPanel
-
Creates the property sheet panel.
- PropositionalToMultiInstance - weka.filters.unsupervised.attribute中的类
-
Converts a propositional dataset into a multi-instance dataset (with relational attribute).
- PropositionalToMultiInstance() - 类的构造器 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
- ProtectedProperties - weka.core中的类
-
Simple class that extends the Properties class so that the properties are unable to be modified.
- ProtectedProperties(Properties) - 类的构造器 weka.core.ProtectedProperties
-
Creates a set of protected properties from a set of normal ones.
- prune() - 类中的方法 weka.classifiers.trees.ft.FTInnerNode
-
Prunes a tree using C4.5 pruning procedure.
- prune() - 类中的方法 weka.classifiers.trees.ft.FTLeavesNode
-
Prunes a tree using C4.5 pruning procedure.
- prune() - 类中的方法 weka.classifiers.trees.ft.FTNode
-
Method for prunning a tree using C4.5 pruning procedure.
- prune() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Abstract Method that prunes a tree using C4.5 pruning procedure.
- prune() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTree
-
Prunes a tree using C4.5's pruning procedure.
- prune() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Prunes a tree using C4.5's pruning procedure.
- prune() - 类中的方法 weka.classifiers.trees.j48.PruneableClassifierTree
-
Prunes a tree.
- prune() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Recursively prune the tree
- prune(double) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Prunes a logistic model tree using the CART pruning scheme, given a cost-complexity parameter alpha.
- prune(double) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Prunes the original tree using the CART pruning scheme, given a cost-complexity parameter alpha.
- prune(double[], double[], Instances) - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Method for performing one fold in the cross-validation of the cost-complexity parameter.
- prune(double[], double[], Instances) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Method for performing one fold in the cross-validation of minimal cost-complexity pruning.
- prune(Instances, boolean) - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Prune all the possible final sequences of the rule using the pruning data.
- PruneableClassifierTree - weka.classifiers.trees.j48中的类
-
Class for handling a tree structure that can be pruned using a pruning set.
- PruneableClassifierTree(ModelSelection, boolean, int, boolean, int) - 类的构造器 weka.classifiers.trees.j48.PruneableClassifierTree
-
Constructor for pruneable tree structure.
- PruneableDecList - weka.classifiers.rules.part中的类
-
Class for handling a partial tree structure that can be pruned using a pruning set.
- PruneableDecList(ModelSelection, int) - 类的构造器 weka.classifiers.rules.part.PruneableDecList
-
Constructor for pruneable partial tree structure.
- pruneItemSets(FastVector, Hashtable) - 类中的静态方法 weka.associations.ItemSet
-
Prunes a set of (k)-item sets using the given (k-1)-item sets.
- pruneItemSets(FastVector, Hashtable) - 类中的静态方法 weka.associations.LabeledItemSet
-
Prunes a set of (k)-item sets using the given (k-1)-item sets.
- pruneRules(List<FPGrowth.AssociationRule>, ArrayList<Attribute>, boolean) - 类中的静态方法 weka.associations.FPGrowth.AssociationRule
- pruneRules(FastVector[], double) - 类中的静态方法 weka.associations.ItemSet
-
Prunes a set of rules.
- pruneToK(Instances, double[], int) - 类中的方法 weka.classifiers.lazy.IBk
-
Prunes the list to contain the k nearest neighbors.
- PRUNETYPE_LOGLIKELIHOOD - 类中的静态变量 weka.classifiers.meta.RacedIncrementalLogitBoost
-
log likelihood pruning
- PRUNETYPE_NONE - 类中的静态变量 weka.classifiers.meta.RacedIncrementalLogitBoost
-
no pruning
- PRUNING_LAMBDA - 类中的静态变量 weka.classifiers.functions.supportVector.StringKernel
-
Pruning method: Lambda See [2] for details.
- PRUNING_NONE - 类中的静态变量 weka.classifiers.functions.supportVector.StringKernel
-
Pruning method: No Pruning
- PRUNING_POSTPRUNING - 类中的静态变量 weka.classifiers.trees.BFTree
-
pruning strategy: post-pruning
- PRUNING_PREPRUNING - 类中的静态变量 weka.classifiers.trees.BFTree
-
pruning strategy: pre-pruning
- PRUNING_UNPRUNED - 类中的静态变量 weka.classifiers.trees.BFTree
-
pruning strategy: un-pruned
- pruningMethodTipText() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the tip text for this property
- pruningStrategyTipText() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the tip text for this property
- pruningTypeTipText() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
- PS - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
A link to a postscript file.
- PSI - 类中的静态变量 weka.core.matrix.Maths
-
The constant 1 / sqrt(2 pi)
- PUBLISHER - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The publisher's name.
- Puk - weka.classifiers.functions.supportVector中的类
-
The Pearson VII function-based universal kernel.
For more information see:
B. - Puk() - 类的构造器 weka.classifiers.functions.supportVector.Puk
-
default constructor - does nothing.
- Puk(Instances, int, double, double) - 类的构造器 weka.classifiers.functions.supportVector.Puk
-
Constructor.
- PURE_INPUT - 类中的静态变量 weka.classifiers.functions.neural.NeuralConnection
-
This unit is a pure input unit.
- PURE_OUTPUT - 类中的静态变量 weka.classifiers.functions.neural.NeuralConnection
-
This unit is a pure output unit.
- push(Object) - 类中的方法 weka.core.Queue
-
Appends an object to the back of the queue.
- push(T) - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Pushes the given element to the stack.
- push(Stack<T>, T) - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Pushes the given element onto the given stack.
- put(Object, Object) - 类中的方法 weka.core.ProtectedProperties
-
Overrides a method to prevent the properties from being modified.
- putAll(Map) - 类中的方法 weka.core.ProtectedProperties
-
Overrides a method to prevent the properties from being modified.
- putResultInTable(String, ResultProducer, Object[], Object[]) - 类中的方法 weka.experiment.DatabaseUtils
-
Executes a database query to insert a result for the supplied key into the database.
Q
- qr() - 类中的方法 weka.core.matrix.Matrix
-
QR Decomposition
- QRDecomposition - weka.core.matrix中的类
-
QR Decomposition.
- QRDecomposition(Matrix) - 类的构造器 weka.core.matrix.QRDecomposition
-
QR Decomposition, computed by Householder reflections.
- queryExecuted(QueryExecuteEvent) - 接口中的方法 weka.gui.sql.event.QueryExecuteListener
-
This method gets called when a query has been executed.
- queryExecuted(QueryExecuteEvent) - 类中的方法 weka.gui.sql.ResultPanel
-
This method gets called when a query has been executed.
- queryExecuted(QueryExecuteEvent) - 类中的方法 weka.gui.sql.SqlViewer
-
This method gets called when a query has been executed.
- QueryExecuteEvent - weka.gui.sql.event中的类
-
An event that is generated when a query is executed.
- QueryExecuteEvent(Object, DbUtils, String, int, ResultSet, Exception) - 类的构造器 weka.gui.sql.event.QueryExecuteEvent
-
constructs the event
- QueryExecuteListener - weka.gui.sql.event中的接口
-
A listener for executing queries.
- QueryPanel - weka.gui.sql中的类
-
Represents a panel for entering an SQL query.
- QueryPanel(JFrame) - 类的构造器 weka.gui.sql.QueryPanel
-
initializes the panel.
- queryTipText() - 类中的方法 weka.core.converters.DatabaseLoader
-
the tip text for this property
- queryTipText() - 类中的方法 weka.experiment.InstanceQuery
-
Returns the tip text for this property
- Queue - weka.core中的类
-
Class representing a FIFO queue.
- Queue() - 类的构造器 weka.core.Queue
- quickSort(double[], double[], int, int) - 类中的静态方法 weka.core.neighboursearch.NearestNeighbourSearch
-
performs quicksort.
- quote(String) - 类中的静态方法 weka.core.Utils
-
Quotes a string if it contains special characters.
R
- R - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
R(i)= BetaVector X x(i) X y(i).
- R_HIGH - 类中的静态变量 weka.clusterers.XMeans
-
Index in ranges for HIGH.
- R_LOW - 类中的静态变量 weka.clusterers.XMeans
-
Index in ranges for LOW.
- R_MAX - 类中的静态变量 weka.core.NormalizableDistance
-
Index in ranges for MAX.
- R_MIN - 类中的静态变量 weka.core.NormalizableDistance
-
Index in ranges for MIN.
- R_WIDTH - 类中的静态变量 weka.clusterers.XMeans
-
Index in ranges for WIDTH.
- R_WIDTH - 类中的静态变量 weka.core.NormalizableDistance
-
Index in ranges for WIDTH.
- RacedIncrementalLogitBoost - weka.classifiers.meta中的类
-
Classifier for incremental learning of large datasets by way of racing logit-boosted committees.
For more information see:
Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall: Racing committees for large datasets. - RacedIncrementalLogitBoost() - 类的构造器 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Constructor.
- RaceSearch - weka.attributeSelection中的类
-
Races the cross validation error of competing attribute subsets.
- RaceSearch() - 类的构造器 weka.attributeSelection.RaceSearch
- raceTypeTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- randEntropy - 类中的变量 weka.classifiers.lazy.kstar.KStarWrapper
-
used/reused to hold the random entropy
- random(int) - 类中的静态方法 weka.core.matrix.DoubleVector
-
Returns a random vector of uniform distribution
- random(int, int) - 类中的静态方法 weka.core.matrix.Matrix
-
Generate matrix with random elements
- Random() - 类的构造器 weka.core.Debug.Random
-
Creates a new random number generator.
- Random(boolean) - 类的构造器 weka.core.Debug.Random
-
Creates a new random number generator.
- Random(long) - 类的构造器 weka.core.Debug.Random
-
Creates a new random number generator using a single long seed.
- Random(long, boolean) - 类的构造器 weka.core.Debug.Random
-
Creates a new random number generator using a single long seed.
- RANDOM - 类中的静态变量 weka.datagenerators.clusterers.BIRCHCluster
-
Constant set for choice of pattern.
- RANDOM - 类中的静态变量 weka.filters.supervised.attribute.ClassOrder
-
The class values are sorted in random order
- randomCARule(int, int, Random) - 类中的方法 weka.associations.PriorEstimation
-
Constructs an item set of certain length randomly.
- RandomCommittee - weka.classifiers.meta中的类
-
Class for building an ensemble of randomizable base classifiers.
- RandomCommittee() - 类的构造器 weka.classifiers.meta.RandomCommittee
-
Constructor.
- RandomForest - weka.classifiers.trees中的类
-
Class for constructing a forest of random trees.
For more information see:
Leo Breiman (2001). - RandomForest() - 类的构造器 weka.classifiers.trees.RandomForest
- Randomizable - weka.core中的接口
-
Interface to something that has random behaviour that is able to be seeded with an integer.
- RandomizableClassifier - weka.classifiers中的类
-
Abstract utility class for handling settings common to randomizable classifiers.
- RandomizableClassifier() - 类的构造器 weka.classifiers.RandomizableClassifier
- RandomizableClusterer - weka.clusterers中的类
-
Abstract utility class for handling settings common to randomizable clusterers.
- RandomizableClusterer() - 类的构造器 weka.clusterers.RandomizableClusterer
- RandomizableDensityBasedClusterer - weka.clusterers中的类
-
Abstract utility class for handling settings common to randomizable clusterers.
- RandomizableDensityBasedClusterer() - 类的构造器 weka.clusterers.RandomizableDensityBasedClusterer
- RandomizableIteratedSingleClassifierEnhancer - weka.classifiers中的类
-
Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.
- RandomizableIteratedSingleClassifierEnhancer() - 类的构造器 weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
- RandomizableMultipleClassifiersCombiner - weka.classifiers中的类
-
Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from multiple classifiers based on a given random number seed.
- RandomizableMultipleClassifiersCombiner() - 类的构造器 weka.classifiers.RandomizableMultipleClassifiersCombiner
- RandomizableSingleClassifierEnhancer - weka.classifiers中的类
-
Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.
- RandomizableSingleClassifierEnhancer() - 类的构造器 weka.classifiers.RandomizableSingleClassifierEnhancer
- RandomizableSingleClustererEnhancer - weka.clusterers中的类
-
Abstract utility class for handling settings common to randomizable clusterers.
- RandomizableSingleClustererEnhancer() - 类的构造器 weka.clusterers.RandomizableSingleClustererEnhancer
- randomize(int[], Random) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Accepts an array of ints and randomises the values in the array, using the random seed.
- randomize(Random) - 类中的方法 weka.core.Instances
-
Shuffles the instances in the set so that they are ordered randomly.
- Randomize - weka.filters.unsupervised.instance中的类
-
Randomly shuffles the order of instances passed through it.
- Randomize() - 类的构造器 weka.filters.unsupervised.instance.Randomize
- RANDOMIZED - 类中的静态变量 weka.datagenerators.clusterers.BIRCHCluster
-
Constant set for input order (default)
- randomizeDataTipText() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns the tip text for this property
- randomizeTipText() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Returns the tip text for this property
- randomNormal(int, int) - 类中的静态方法 weka.classifiers.functions.pace.PaceMatrix
-
Generate matrix with standard-normally distributed random elements
- randomOrderTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.K2
- randomOrderTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.K2
- RandomProjection - weka.filters.unsupervised.attribute中的类
-
Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length (i.e.
- RandomProjection() - 类的构造器 weka.filters.unsupervised.attribute.RandomProjection
- RandomRBF - weka.datagenerators.classifiers.classification中的类
-
RandomRBF data is generated by first creating a random set of centers for each class.
- RandomRBF() - 类的构造器 weka.datagenerators.classifiers.classification.RandomRBF
-
initializes the generator with default values
- randomRule(int, int, Random) - 类中的方法 weka.associations.PriorEstimation
-
Constructs an item set of certain length randomly.
- RandomSearch - weka.attributeSelection中的类
-
RandomSearch :
Performs a Random search in the space of attribute subsets. - RandomSearch() - 类的构造器 weka.attributeSelection.RandomSearch
-
Constructor
- randomSeedTipText() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns the tip text for this property
- randomSeedTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- randomSeedTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- randomSeedTipText() - 类中的方法 weka.classifiers.trees.ADTree
- randomSeedTipText() - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Returns the tip text for this property.
- randomSeedTipText() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns the tip text for this property.
- randomSeedTipText() - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Returns the tip text for this property.
- randomSeedTipText() - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Returns the tip text for this property
- randomSeedTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Returns the tip text for this property
- randomSeedTipText() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns the tip text for this property
- randomSeedTipText() - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Returns the tip text for this property
- randomSeedTipText() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Returns the tip text for this property
- randomSeedTipText() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Returns the tip text for this property
- RandomSplitResultProducer - weka.experiment中的类
-
Generates a single train/test split and calls the appropriate SplitEvaluator to generate some results.
- RandomSplitResultProducer() - 类的构造器 weka.experiment.RandomSplitResultProducer
- RandomSubset - weka.filters.unsupervised.attribute中的类
-
Chooses a random subset of attributes, either an absolute number or a percentage.
- RandomSubset() - 类的构造器 weka.filters.unsupervised.attribute.RandomSubset
- RandomSubSpace - weka.classifiers.meta中的类
-
This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows in complexity.
- RandomSubSpace() - 类的构造器 weka.classifiers.meta.RandomSubSpace
-
Constructor.
- randomTipText() - 类中的方法 weka.datagenerators.DataGenerator
-
Returns the tip text for this property
- RandomTree - weka.classifiers.trees中的类
-
Class for constructing a tree that considers K randomly chosen attributes at each node.
- RandomTree() - 类的构造器 weka.classifiers.trees.RandomTree
- RandomVariates - weka.core中的类
-
Class implementing some simple random variates generator.
- RandomVariates() - 类的构造器 weka.core.RandomVariates
-
Simply the constructor of super class
- RandomVariates(long) - 类的构造器 weka.core.RandomVariates
-
Simply the constructor of super class
- randomWidthFactorTipText() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
- Range - weka.core中的类
-
Class representing a range of cardinal numbers.
- Range() - 类的构造器 weka.core.Range
-
Default constructor.
- Range(String) - 类的构造器 weka.core.Range
-
Constructor to set initial range.
- RANGE_BOUNDS - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
Correct based on min/max observed
- RANGE_NONE - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
no range correction
- rangeCorrectionTipText() - 类中的方法 weka.classifiers.meta.ThresholdSelector
- rangesSet() - 类中的方法 weka.core.NormalizableDistance
-
Check if ranges are set.
- rangesTipText() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Returns the tip text for this property.
- rank() - 类中的方法 weka.core.matrix.Matrix
-
Matrix rank
- rank() - 类中的方法 weka.core.matrix.SingularValueDecomposition
-
Effective numerical matrix rank
- rankAttributes(Instances, SubsetEvaluator, boolean) - 类中的方法 weka.attributeSelection.LFSMethods
- RankEachAttribute() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Rank all the attributes individually acording to their merits
- rankedAttributes() - 类中的方法 weka.attributeSelection.AttributeSelection
-
get the final ranking of the attributes.
- rankedAttributes() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Produces a ranked list of attributes.
- rankedAttributes() - 类中的方法 weka.attributeSelection.RaceSearch
- rankedAttributes() - 接口中的方法 weka.attributeSelection.RankedOutputSearch
-
Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.
- rankedAttributes() - 类中的方法 weka.attributeSelection.Ranker
-
Sorts the evaluated attribute list
- RankedOutputSearch - weka.attributeSelection中的接口
-
Interface for search methods capable of producing a ranked list of attributes.
- Ranker - weka.attributeSelection中的类
-
Ranker :
Ranks attributes by their individual evaluations. - Ranker() - 类的构造器 weka.attributeSelection.Ranker
-
Constructor
- RankSearch - weka.attributeSelection中的类
-
RankSearch :
Uses an attribute/subset evaluator to rank all attributes. - RankSearch() - 类的构造器 weka.attributeSelection.RankSearch
-
Constructor
- rankTipText() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns the tip text for this property
- rawOutputTipText() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns the tip text for this property
- rawOutputTipText() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns the tip text for this property
- RBFKernel - weka.classifiers.functions.supportVector中的类
-
The RBF kernel.
- RBFKernel() - 类的构造器 weka.classifiers.functions.supportVector.RBFKernel
-
default constructor - does nothing.
- RBFKernel(Instances, int, double) - 类的构造器 weka.classifiers.functions.supportVector.RBFKernel
-
Constructor.
- RBFNetwork - weka.classifiers.functions中的类
-
Class that implements a normalized Gaussian radial basisbasis function network.
It uses the k-means clustering algorithm to provide the basis functions and learns either a logistic regression (discrete class problems) or linear regression (numeric class problems) on top of that. - RBFNetwork() - 类的构造器 weka.classifiers.functions.RBFNetwork
- rbind(PaceMatrix) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Returns a new matrix which binds two matrices together with rows.
- rchisq(int, double, Random) - 类中的静态方法 weka.core.matrix.Maths
-
Generates a sample of a Chi-square distribution.
- RDG1 - weka.datagenerators.classifiers.classification中的类
-
A data generator that produces data randomly by producing a decision list.
The decision list consists of rules.
Instances are generated randomly one by one. - RDG1() - 类的构造器 weka.datagenerators.classifiers.classification.RDG1
-
initializes the generator with default values
- read() - 类中的方法 weka.core.xml.XMLSerializationMethodHandler
-
returns the handler for read methods
- read(BufferedReader) - 类中的静态方法 weka.core.matrix.Matrix
-
Read a matrix from a stream.
- read(BufferedReader) - 类中的方法 weka.core.Stopwords
-
Generates a new Stopwords object from the reader.
- read(File) - 类中的方法 weka.core.Stopwords
-
Generates a new Stopwords object from the given file
- read(File) - 类中的静态方法 weka.core.xml.KOML
-
reads the XML-serialized object from the given file
- read(File) - 类中的方法 weka.core.xml.XMLDocument
-
parses the given file and returns a DOM document.
- read(File) - 类中的方法 weka.core.xml.XMLSerialization
-
parses the given file and returns a DOM document
- read(File) - 类中的静态方法 weka.core.xml.XStream
-
reads the XML-serialized object from the given file
- read(InputStream) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSource
-
convencience method for loading a dataset in batch mode from a stream.
- read(InputStream) - 类中的静态方法 weka.core.SerializationHelper
-
deserializes from the given stream and returns the object from it.
- read(InputStream) - 类中的静态方法 weka.core.xml.KOML
-
reads the XML-serialized object from a stream
- read(InputStream) - 类中的方法 weka.core.xml.XMLDocument
-
parses the given stream and returns a DOM document.
- read(InputStream) - 类中的方法 weka.core.xml.XMLSerialization
-
parses the given stream and returns a DOM document
- read(InputStream) - 类中的静态方法 weka.core.xml.XStream
-
reads the XML-serialized object from the given input stream
- read(Reader) - 类中的方法 weka.core.xml.XMLDocument
-
parses the given reader and returns a DOM document.
- read(Reader) - 类中的方法 weka.core.xml.XMLSerialization
-
parses the given reader and returns a DOM document
- read(Reader) - 类中的静态方法 weka.core.xml.XStream
-
reads the XML-serialized object from the given Reader
- read(String) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSource
-
convencience method for loading a dataset in batch mode.
- read(String) - 类中的静态方法 weka.core.SerializationHelper
-
deserializes the given file and returns the object from it.
- read(String) - 类中的方法 weka.core.Stopwords
-
Generates a new Stopwords object from the given file
- read(String) - 类中的静态方法 weka.core.xml.KOML
-
reads the XML-serialized object from the given file
- read(String) - 类中的方法 weka.core.xml.XMLDocument
-
parses the given XML string (can be XML or a filename) and returns a DOM Document.
- read(String) - 类中的方法 weka.core.xml.XMLSerialization
-
parses the given XML string (can be XML or a filename) and returns an Object generated from the representation
- read(String) - 类中的静态方法 weka.core.xml.XStream
-
reads the XML-serialized object from the given file
- read(String) - 类中的静态方法 weka.experiment.Experiment
-
Loads an experiment from a file.
- read(Loader) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSource
-
convencience method for loading a dataset in batch mode.
- readAll(InputStream) - 类中的静态方法 weka.core.SerializationHelper
-
deserializes from the given stream and returns the object from it.
- readAll(String) - 类中的静态方法 weka.core.SerializationHelper
-
deserializes the given file and returns the objects from it.
- readBeanConnection(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the BeanConnection from the given DOM node.
- readBeanInstance(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the BeanInstance from the given DOM node.
- readBeanVisual(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the BeanVisual from the given DOM node.
- readBIF(InputStream) - 类中的方法 weka.gui.graphvisualizer.GraphVisualizer
-
BIF reader
Reads a graph description in XMLBIF03 from an InputStrem - readBIF(String) - 类中的方法 weka.gui.graphvisualizer.GraphVisualizer
-
BIF reader
Reads a graph description in XMLBIF03 from a string - readBIFFromFile(String) - 类中的方法 weka.classifiers.bayes.net.GUI
-
BIF reader
Reads a graph description in XMLBIF03 from an file with name sFileName - readBooleanFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the primitive from the given DOM node.
- readByteFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the primitive from the given DOM node.
- readCharFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the primitive from the given DOM node.
- readCollection(Element) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
builds the Collection from the given DOM node.
- readColor(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the Color from the given DOM node.
- readColorUIResource(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the ColorUIResource from the given DOM node.
- readCostMatrixOld(Element) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
builds the Matrix (old) from the given DOM node.
- readDefaultListModel(Element) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
builds the DefaultListModel from the given DOM node.
- readDimension(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the Dimension from the given DOM node.
- readDOT(Reader) - 类中的方法 weka.gui.graphvisualizer.GraphVisualizer
-
Dot reader
Reads a graph description in DOT format from a string - readDoubleFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the primitive from the given DOM node.
- readFloatFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the primitive from the given DOM node.
- readFont(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the Font from the given DOM node.
- readFontUIResource(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the FontUIResource from the given DOM node.
- readFromXML(Object, String, Element) - 类中的方法 weka.core.xml.XMLSerialization
-
adds the specific node to the object via a set method
- readFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the object from the given DOM node.
- readInstance(Reader) - 类中的方法 weka.core.Instances
-
已过时。instead of using this method in conjunction with the
readInstance(Reader)
method, one should use theArffLoader
orDataSource
class instead. - readInstance(Instances) - 类中的方法 weka.core.converters.ArffLoader.ArffReader
-
Reads a single instance using the tokenizer and returns it.
- readInstance(Instances, boolean) - 类中的方法 weka.core.converters.ArffLoader.ArffReader
-
Reads a single instance using the tokenizer and returns it.
- readIntFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the primitive from the given DOM node.
- readLoader(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the Loader from the given DOM node.
- readLongFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the primitive from the given DOM node.
- readMap(Element) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
builds the Map from the given DOM node.
- readMatrix(Element) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
builds the Matrix from the given DOM node.
- readMatrixOld(Element) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
builds the Matrix (old) from the given DOM node.
- readMetaBean(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the MetaBean from the given DOM node.
- readOldFormat(Reader) - 类中的方法 weka.classifiers.CostMatrix
-
Loads a cost matrix in the old format from a reader.
- readPoint(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the Point from the given DOM node.
- readProperties(String) - 类中的静态方法 weka.core.Utils
-
Reads properties that inherit from three locations.
- readPropertyNode(Element) - 类中的方法 weka.experiment.xml.XMLExperiment
-
builds the PropertyNode from the given DOM node.
- readSaver(Element) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
builds the Saver from the given DOM node.
- readShortFromXML(Element) - 类中的方法 weka.core.xml.XMLSerialization
-
builds the primitive from the given DOM node.
- realCount - 类中的变量 weka.core.AttributeStats
-
The number of real-like values (i.e.
- recall(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the recall with respect to a particular class.
- RECALL - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
recall
- RECALL_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: Recall
- RECTANGLE - 类中的静态变量 weka.gui.visualize.VisualizePanelEvent
- redo() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
redo the last edit action performed on the network.
- reduce_table() - 类中的方法 weka.core.mathematicalexpression.Parser
-
Access to
reduce_goto
table. - reduce_table() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Access to
reduce_goto
table. - reducedErrorPruningTipText() - 类中的方法 weka.classifiers.rules.PART
-
Returns the tip text for this property
- reducedErrorPruningTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- reduceDimensionality(Instance) - 类中的方法 weka.attributeSelection.AttributeSelection
-
reduce the dimensionality of a single instance to include only those attributes chosen by the last run of attribute selection.
- reduceDimensionality(Instances) - 类中的方法 weka.attributeSelection.AttributeSelection
-
reduce the dimensionality of a set of instances to include only those attributes chosen by the last run of attribute selection.
- reduceDL(double, boolean) - 类中的方法 weka.classifiers.rules.RuleStats
-
Try to reduce the DL of the ruleset by testing removing the rules one by one in reverse order and update all the stats
- reduceMatrix(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Reduces a matrix by deleting all zero rows and columns.
- ReferenceInstances - weka.classifiers.trees.adtree中的类
-
Simple class that extends the Instances class making it possible to create subsets of instances that reference their source set.
- ReferenceInstances(Instances, int) - 类的构造器 weka.classifiers.trees.adtree.ReferenceInstances
-
Creates an empty set of instances.
- refine(ArrayList) - 类中的方法 weka.associations.tertius.Rule
-
Refine a rule by adding literal from a set of predictes.
- refresh() - 类中的方法 weka.gui.arffviewer.ArffViewer
-
validates and repaints the frame
- refresh() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
validates and repaints the frame
- refreshFreqTipText() - 类中的方法 weka.gui.beans.StripChart
-
GUI Tip text
- register(Object, Class, String) - 类中的方法 weka.core.xml.XMLSerializationMethodHandler
-
adds read and write methods for the given class, i.e., read&;lt;name> and write<name> ("name" is prefixed by read and write)
- registerEditors() - 类中的静态方法 weka.gui.GenericObjectEditor
-
registers all the editors in Weka.
- RegOptimizer - weka.classifiers.functions.supportVector中的类
-
Base class implementation for learning algorithm of SMOreg Valid options are:
- RegOptimizer() - 类的构造器 weka.classifiers.functions.supportVector.RegOptimizer
-
the default constructor
- regOptimizerTipText() - 类中的方法 weka.classifiers.functions.SMOreg
-
Returns the tip text for this property
- regression(Matrix, double) - 类中的方法 weka.core.matrix.Matrix
-
Performs a (ridged) linear regression.
- regression(Matrix, double[], double) - 类中的方法 weka.core.matrix.Matrix
-
Performs a weighted (ridged) linear regression.
- regression(Matrix, double) - 类中的方法 weka.core.Matrix
-
已过时。Performs a (ridged) linear regression.
- regression(Matrix, double[], double) - 类中的方法 weka.core.Matrix
-
已过时。Performs a weighted (ridged) linear regression.
- Regression - weka.classifiers.pmml.consumer中的类
-
Class implementing import of PMML Regression model.
- Regression(Element, Instances, MiningSchema) - 类的构造器 weka.classifiers.pmml.consumer.Regression
-
Constructs a new PMML Regression.
- RegressionByDiscretization - weka.classifiers.meta中的类
-
A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized.
- RegressionByDiscretization() - 类的构造器 weka.classifiers.meta.RegressionByDiscretization
-
Default constructor.
- RegressionGenerator - weka.datagenerators中的类
-
Abstract class for data generators for regression classifiers.
- RegressionGenerator() - 类的构造器 weka.datagenerators.RegressionGenerator
-
initializes the generator with default values
- RegressionSplitEvaluator - weka.experiment中的类
-
A SplitEvaluator that produces results for a classification scheme on a numeric class attribute.
- RegressionSplitEvaluator() - 类的构造器 weka.experiment.RegressionSplitEvaluator
-
No args constructor.
- RegSMO - weka.classifiers.functions.supportVector中的类
-
Implementation of SMO for support vector regression as described in :
A.J. - RegSMO() - 类的构造器 weka.classifiers.functions.supportVector.RegSMO
-
default constructor
- RegSMOImproved - weka.classifiers.functions.supportVector中的类
-
Learn SVM for regression using SMO with Shevade, Keerthi, et al.
- RegSMOImproved() - 类的构造器 weka.classifiers.functions.supportVector.RegSMOImproved
- relabelTipText() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the tip text for this property
- RELAGGS - weka.filters.unsupervised.attribute中的类
-
A propositionalization filter inspired by the RELAGGS algorithm.
It processes all relational attributes that fall into the user defined range (all others are skipped, i.e., not added to the output). - RELAGGS() - 类的构造器 weka.filters.unsupervised.attribute.RELAGGS
- relation() - 类中的方法 weka.core.Attribute
-
Returns the header info for a relation-valued attribute, null if the attribute is not relation-valued.
- relation(int) - 类中的方法 weka.core.Attribute
-
Returns a value of a relation-valued attribute.
- RELATION_NAME - 类中的静态变量 weka.classifiers.evaluation.CostCurve
-
The name of the relation used in cost curve datasets
- RELATION_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
The name of the relation used in threshold curve datasets
- RELATIONAL - 类中的静态变量 weka.core.Attribute
-
Constant set for relation-valued attributes.
- RELATIONAL_ATTRIBUTES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle relational attributes
- RELATIONAL_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle relational classes
- RelationalLocator - weka.core中的类
-
This class locates and records the indices of relational attributes,
- RelationalLocator(Instances) - 类的构造器 weka.core.RelationalLocator
-
Initializes the RelationalLocator with the given data.
- RelationalLocator(Instances, int[]) - 类的构造器 weka.core.RelationalLocator
-
Initializes the RelationalLocator with the given data.
- RelationalLocator(Instances, int, int) - 类的构造器 weka.core.RelationalLocator
-
Initializes the RelationalLocator with the given data.
- relationalValue(int) - 类中的方法 weka.core.Instance
-
Returns the relational value of a relational attribute.
- relationalValue(Attribute) - 类中的方法 weka.core.Instance
-
Returns the relational value of a relational attribute.
- relationForTableNameTipText() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the tip text fo this property.
- relationName() - 类中的方法 weka.core.Instances
-
Returns the relation's name.
- relationNameTipText() - 类中的方法 weka.datagenerators.DataGenerator
-
Returns the tip text for this property
- relativeAbsoluteError() - 类中的方法 weka.classifiers.Evaluation
-
Returns the relative absolute error.
- relativeDL(int, double, boolean) - 类中的方法 weka.classifiers.rules.RuleStats
-
The description length (DL) of the ruleset relative to if the rule in the given position is deleted, which is obtained by:
MDL if the rule exists - MDL if the rule does not exist
Note the minimal possible DL of the ruleset is calculated(i.e. - ReliefFAttributeEval - weka.attributeSelection中的类
-
ReliefFAttributeEval :
Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class. - ReliefFAttributeEval() - 类的构造器 weka.attributeSelection.ReliefFAttributeEval
-
Constructor
- RemoteBoundaryVisualizerSubTask - weka.gui.boundaryvisualizer中的类
-
Class that encapsulates a sub task for distributed boundary visualization.
- RemoteBoundaryVisualizerSubTask() - 类的构造器 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
- RemoteEngine - weka.experiment中的类
-
A general purpose server for executing Task objects sent via RMI.
- RemoteEngine(String) - 类的构造器 weka.experiment.RemoteEngine
-
Constructor
- RemoteExperiment - weka.experiment中的类
-
Holds all the necessary configuration information for a distributed experiment.
- RemoteExperiment() - 类的构造器 weka.experiment.RemoteExperiment
-
Construct a new RemoteExperiment using an empty Experiment as base Experiment
- RemoteExperiment(Experiment) - 类的构造器 weka.experiment.RemoteExperiment
-
Construct a new RemoteExperiment using a base Experiment
- RemoteExperimentEvent - weka.experiment中的类
-
Class encapsulating information on progress of a remote experiment
- RemoteExperimentEvent(boolean, boolean, boolean, String) - 类的构造器 weka.experiment.RemoteExperimentEvent
-
Constructor
- RemoteExperimentListener - weka.experiment中的接口
-
Interface for classes that want to listen for updates on RemoteExperiment progress
- remoteExperimentStatus(RemoteExperimentEvent) - 接口中的方法 weka.experiment.RemoteExperimentListener
-
Called when progress has been made in a remote experiment
- RemoteExperimentSubTask - weka.experiment中的类
-
Class to encapsulate an experiment as a task that can be executed on a remote host.
- RemoteExperimentSubTask() - 类的构造器 weka.experiment.RemoteExperimentSubTask
- RemoteResult - weka.gui.boundaryvisualizer中的类
-
Class that encapsulates a result (and progress info) for part of a distributed boundary visualization.
- RemoteResult(int, int) - 类的构造器 weka.gui.boundaryvisualizer.RemoteResult
-
Creates a new
RemoteResult
instance. - remove() - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
- remove() - 类中的方法 weka.associations.tertius.SimpleLinkedList.LinkedListIterator
- remove() - 类中的方法 weka.core.Trie.TrieIterator
-
ignored
- remove() - 类中的方法 weka.gui.beans.BeanConnection
-
Remove this connection
- remove(int) - 类中的方法 weka.core.Tee
-
removes the given PrintStream from the list.
- remove(int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Removes the element at the specified position in this list.
- remove(PrintStream) - 类中的方法 weka.core.Tee
-
removes the given PrintStream from the list.
- remove(Class) - 类中的方法 weka.core.xml.MethodHandler
-
removes the method for the specified class from its internal list.
- remove(Object) - 类中的方法 weka.core.ProtectedProperties
-
Overrides a method to prevent the properties from being modified.
- remove(Object) - 类中的方法 weka.core.Trie
-
Removes a single instance of the specified element from this collection, if it is present.
- remove(String) - 类中的方法 weka.core.Stopwords
-
removes the word from the stopword list
- remove(String) - 类中的方法 weka.core.Trie.TrieNode
-
Removes a suffix from the trie.
- remove(String) - 类中的方法 weka.core.xml.MethodHandler
-
removes the method for the property specified by the display name from its internal list.
- Remove - weka.filters.unsupervised.attribute中的类
-
A filter that removes a range of attributes from the dataset.
- Remove() - 类的构造器 weka.filters.unsupervised.attribute.Remove
-
Constructor so that we can initialize the Range variable properly.
- REMOVE_CHILDREN - 类中的静态变量 weka.gui.treevisualizer.TreeDisplayEvent
- REMOVE_POINT_RADIUS - 类中的静态变量 weka.gui.boundaryvisualizer.BoundaryPanel
-
The distance we can click away from a point in the GUI and still remove it.
- removeActionListener(ActionListener) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Remove a listener
- removeAll(Collection<?>) - 类中的方法 weka.core.Trie
-
Removes all this collection's elements that are also contained in the specified collection
- removeAllBeansFromContainer(JComponent) - 类中的静态方法 weka.gui.beans.BeanInstance
-
Removes all beans from containing component
- removeAllElements() - 类中的方法 weka.core.FastVector
-
Removes all components from this vector and sets its size to zero.
- removeAllElements() - 类中的方法 weka.core.Queue
-
Removes all objects from the queue m_Tail.m_Next.
- removeAllInputs() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
This function will remove all the inputs to this unit.
- removeAllInputs() - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
This function will remove all the inputs to this unit.
- removeAllInstances() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Deletes all training instances from our dataset.
- removeAllMissingColsTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- removeAllOutputs() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
This function will remove all outputs to this unit.
- removeAllowed(Class, String) - 类中的方法 weka.core.xml.PropertyHandler
-
removes the given property (display name) for the specified class from the list of allowed properties.
- removeAllPlots() - 类中的方法 weka.gui.visualize.Plot2D
-
Clears all plots
- removeAllPlots() - 类中的方法 weka.gui.visualize.VisualizePanel
-
Removes all the plots.
- removeBatchClassifierListener(BatchClassifierListener) - 类中的方法 weka.gui.beans.Classifier
-
Remove a batch classifier listener
- removeBatchClustererListener(BatchClustererListener) - 类中的方法 weka.gui.beans.Clusterer
-
Remove a batch clusterer listener
- removeBean(JComponent) - 类中的方法 weka.gui.beans.BeanInstance
-
Remove this bean from the list of beans and from the containing component
- removeCancelListener(ActionListener) - 类中的方法 weka.gui.GenericObjectEditor.GOEPanel
-
This is used to remove an action listener from the cancel button.
- removeCapabilitiesFilter() - 类中的方法 weka.gui.GenericObjectEditor
-
Removes the current Capabilities filter.
- removeCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - 类中的方法 weka.gui.explorer.Explorer
-
Removes the specified listener from the set of listeners if it is present.
- removeChangeListener(ChangeListener) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
Removes a ChangeListener from the panel
- removeChangeListener(ChangeListener) - 类中的方法 weka.gui.arffviewer.ArffTable
-
Removes a ChangeListener from the panel
- removeChartListener(ChartListener) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Remove a chart listener
- removeChildFrame(Container) - 类中的方法 weka.gui.GUIChooser
-
tries to remove the child frame, it returns true if it could do such.
- removeChildFrame(Container) - 类中的方法 weka.gui.Main
-
tries to remove the child frame, it returns true if it could do such.
- removeClassColumnTipText() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Returns the tip text for this property
- removeConnectionListener(ConnectionListener) - 类中的方法 weka.gui.sql.ConnectionPanel
-
removes the given listener from the list of listeners.
- removeConnectionListener(ConnectionListener) - 类中的方法 weka.gui.sql.SqlViewer
-
removes the given listener from the list of listeners.
- removeConnections(BeanInstance) - 类中的静态方法 weka.gui.beans.BeanConnection
-
Remove all connections for a bean.
- removeDataFormatListener(DataFormatListener) - 类中的方法 weka.gui.beans.ClassAssigner
- removeDataFormatListener(DataFormatListener) - 类中的方法 weka.gui.beans.ClassValuePicker
- removeDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Remove a listener
- removeDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.ClassAssigner
- removeDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.ClassValuePicker
- removeDataSourceListener(DataSourceListener) - 接口中的方法 weka.gui.beans.DataSource
-
Remove a data source listener
- removeDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.DataVisualizer
-
Remove a listener
- removeDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.Filter
-
Remove a data source listener
- removeDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
- removeDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.Loader
-
Remove a listener
- removeDataSourceListener(DataSourceListener) - 类中的方法 weka.gui.beans.PredictionAppender
-
Remove a datasource listener
- removedPercentageTipText() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns the tip text for this property
- removeElement(Object) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Removes the first (lowest-indexed) occurrence of the argument from this list.
- removeElementAt(int) - 类中的方法 weka.core.FastVector
-
Deletes an element from this vector.
- removeFirst() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- RemoveFolds - weka.filters.unsupervised.instance中的类
-
This filter takes a dataset and outputs a specified fold for cross validation.
- RemoveFolds() - 类的构造器 weka.filters.unsupervised.instance.RemoveFolds
- RemoveFrequentValues - weka.filters.unsupervised.instance中的类
-
Determines which values (frequent or infrequent ones) of an (nominal) attribute are retained and filters the instances accordingly.
- RemoveFrequentValues() - 类的构造器 weka.filters.unsupervised.instance.RemoveFrequentValues
- removeGraphListener(GraphListener) - 类中的方法 weka.gui.beans.Associator
-
Remove a graph listener
- removeGraphListener(GraphListener) - 类中的方法 weka.gui.beans.Classifier
-
Remove a graph listener
- removeGraphListener(GraphListener) - 类中的方法 weka.gui.beans.Clusterer
-
Remove a graph listener
- removeHistoryChangedListener(HistoryChangedListener) - 类中的方法 weka.gui.sql.ConnectionPanel
-
removes the given listener from the list of listeners.
- removeHistoryChangedListener(HistoryChangedListener) - 类中的方法 weka.gui.sql.QueryPanel
-
removes the given listener from the list of listeners.
- removeHistoryChangedListener(HistoryChangedListener) - 类中的方法 weka.gui.sql.SqlViewer
-
removes the given listener from the list of listeners.
- removeIgnored(Class, String) - 类中的方法 weka.core.xml.PropertyHandler
-
removes the given display name from the ignore list of the class.
- removeIgnored(String) - 类中的方法 weka.core.xml.PropertyHandler
-
removes the given display name from the ignore list.
- removeIncrementalClassifierListener(IncrementalClassifierListener) - 类中的方法 weka.gui.beans.Classifier
-
Remove an incremental classifier listener
- removeInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Remove an instance listener
- removeInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.ClassAssigner
- removeInstanceListener(InstanceListener) - 接口中的方法 weka.gui.beans.DataSource
-
Remove an instance listener
- removeInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.Filter
-
Remove an instance listener
- removeInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
- removeInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.Loader
-
Remove an instance listener
- removeInstanceListener(InstanceListener) - 类中的方法 weka.gui.beans.PredictionAppender
-
Remove an instance listener
- removeInstanceListener(InstanceListener) - 类中的方法 weka.gui.streams.InstanceJoiner
- removeInstanceListener(InstanceListener) - 类中的方法 weka.gui.streams.InstanceLoader
- removeInstanceListener(InstanceListener) - 接口中的方法 weka.gui.streams.InstanceProducer
- removeLast() - 类中的方法 weka.classifiers.rules.RuleStats
-
Remove the last rule in the ruleset as well as it's stats.
- removeLayoutCompleteEventListener(LayoutCompleteEventListener) - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
Method to remove a LayoutCompleteEventListener.
- removeLayoutCompleteEventListener(LayoutCompleteEventListener) - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
This method removes a LayoutCompleteEventListener from the LayoutEngine.
- removeLinkAt(int) - 类中的方法 weka.attributeSelection.BestFirst.LinkedList2
-
removes an element (Link) at a specific index from the list.
- removeLinkAt(int) - 类中的方法 weka.attributeSelection.LFSMethods.LinkedList2
-
removes an element (Link) at a specific index from the list.
- RemoveMisclassified - weka.filters.unsupervised.instance中的类
-
A filter that removes instances which are incorrectly classified.
- RemoveMisclassified() - 类的构造器 weka.filters.unsupervised.instance.RemoveMisclassified
- removeNotify() - 类中的方法 weka.gui.PropertyPanel
-
Cleans up when the panel is destroyed.
- removeOkListener(ActionListener) - 类中的方法 weka.gui.GenericObjectEditor.GOEPanel
-
This is used to remove an action listener from the ok button.
- removeOldClassTipText() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns the tip text for this property.
- RemovePercentage - weka.filters.unsupervised.instance中的类
-
A filter that removes a given percentage of a dataset.
- RemovePercentage() - 类的构造器 weka.filters.unsupervised.instance.RemovePercentage
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.AssociatorCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.BeanVisual
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.ClassAssignerCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.ClassifierCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.ClassValuePickerCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.ClustererCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.CrossValidationFoldMakerCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.FilterCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.LoaderCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.PredictionAppenderCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.SaverCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.SerializedModelSaverCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.StripChartCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.beans.TrainTestSplitMakerCustomizer
-
Remove a property change listener
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.CostMatrixEditor
-
Removes an object from the list of those that wish to be informed when the cost matrix changes.
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.experiment.SetupPanel
-
Removes a PropertyChangeListener.
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.experiment.SimpleSetupPanel
-
Removes a PropertyChangeListener.
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Removes a PropertyChangeListener.
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.GenericArrayEditor
-
Removes a PropertyChangeListener.
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.GenericObjectEditor
-
Removes a PropertyChangeListener.
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.PropertySheetPanel
-
Removes a PropertyChangeListener.
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.SetInstancesPanel
-
Removes a PropertyChangeListener.
- removePropertyChangeListener(PropertyChangeListener) - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Removes an object from the list of those that wish to be informed when the date format changes.
- removePropertyChangeListener(String, PropertyChangeListener) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Remove a property change listener from this bean
- removePropertyChangeListener(String, PropertyChangeListener) - 类中的方法 weka.gui.beans.DataVisualizer
-
Remove a property change listener from this bean
- removePropertyChangeListener(String, PropertyChangeListener) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Remove a property change listener from this bean
- removePropertyChangeListener(String, PropertyChangeListener) - 类中的方法 weka.gui.beans.TextViewer
-
Remove a property change listener from this bean
- removePropertyChangeListenersSubFlow(PropertyChangeListener) - 类中的方法 weka.gui.beans.MetaBean
- removeQueryExecuteListener(QueryExecuteListener) - 类中的方法 weka.gui.sql.QueryPanel
-
removes the given listener from the list of listeners.
- removeQueryExecuteListener(QueryExecuteListener) - 类中的方法 weka.gui.sql.SqlViewer
-
removes the given listener from the list of listeners.
- RemoveRange - weka.filters.unsupervised.instance中的类
-
A filter that removes a given range of instances of a dataset.
- RemoveRange() - 类的构造器 weka.filters.unsupervised.instance.RemoveRange
- removeRedundant(RuleItem) - 类中的方法 weka.associations.RuleGeneration
-
Method that removes redundant rules out of the list of the best rules.
- removeResult(String) - 类中的方法 weka.gui.ResultHistoryPanel
-
Removes one of the result buffers from the history.
- removeResultChangedListener(ResultChangedListener) - 类中的方法 weka.gui.sql.ResultPanel
-
removes the given listener from the list of listeners
- removeResultChangedListener(ResultChangedListener) - 类中的方法 weka.gui.sql.SqlViewer
-
removes the given listener from the list of listeners.
- removeSubstring(String, String) - 类中的静态方法 weka.core.Utils
-
Removes all occurrences of a string from another string.
- removeTableModelListener(TableModelListener) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
removes a listener from the list that is notified each time a change to the data model occurs
- removeTableModelListener(TableModelListener) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
removes a listener from the list that is notified each time a change to the data model occurs
- removeTableModelListener(TableModelListener) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
removes a listener from the list that is notified each time a change to the data model occurs.
- removeTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Remove a listener for test sets
- removeTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Remove a test set listener
- removeTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.ClassAssigner
- removeTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.Filter
-
Remove a test set listener
- removeTestSetListener(TestSetListener) - 类中的方法 weka.gui.beans.PredictionAppender
-
Remove a test set listener
- removeTestSetListener(TestSetListener) - 接口中的方法 weka.gui.beans.TestSetProducer
-
Remove a listener for test set events
- removeTextListener(TextListener) - 类中的方法 weka.gui.beans.Associator
-
Remove a text listener
- removeTextListener(TextListener) - 类中的方法 weka.gui.beans.Classifier
-
Remove a text listener
- removeTextListener(TextListener) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Remove a text listener
- removeTextListener(TextListener) - 类中的方法 weka.gui.beans.Clusterer
-
Remove a text listener
- removeTextListener(TextListener) - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Remove a text listener
- removeTextListener(TextListener) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Remove a text listener
- removeTextListener(TextListener) - 类中的方法 weka.gui.beans.TextViewer
-
Remove a text listener
- removeThresholdDataListener(ThresholdDataListener) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Remove a Threshold data listener
- removeTrainingInstanceFromMouseLocation(int, int) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Removes a single training instance from our dataset, if there is one that is close enough to the specified mouse location.
- removeTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Remove a training set listener
- removeTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Remove a training set listener
- removeTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.ClassAssigner
- removeTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.Filter
-
Remove a training set listener
- removeTrainingSetListener(TrainingSetListener) - 类中的方法 weka.gui.beans.PredictionAppender
-
Remove a training set listener
- removeTrainingSetListener(TrainingSetListener) - 接口中的方法 weka.gui.beans.TrainingSetProducer
-
Remove a training set listener
- RemoveType - weka.filters.unsupervised.attribute中的类
-
Removes attributes of a given type.
- RemoveType() - 类的构造器 weka.filters.unsupervised.attribute.RemoveType
- removeUnusedTipText() - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Returns the tip text for this property.
- RemoveUseless - weka.filters.unsupervised.attribute中的类
-
This filter removes attributes that do not vary at all or that vary too much.
- RemoveUseless() - 类的构造器 weka.filters.unsupervised.attribute.RemoveUseless
- removeVariable(String) - 类中的方法 weka.core.Environment
-
Remove a named variable from the map.
- removeVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Remove a vetoable change listener from this bean
- removeVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- removeVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.DataVisualizer
-
Remove a vetoable change listener from this bean
- removeVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.GraphViewer
-
Remove a vetoable change listener from this bean
- removeVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Remove a vetoable change listener from this bean
- removeVetoableChangeListener(String, VetoableChangeListener) - 类中的方法 weka.gui.beans.TextViewer
-
Remove a vetoable change listener from this bean
- removeVisualizableErrorListener(VisualizableErrorListener) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Remove a visualizable error listener
- RemoveWithValues - weka.filters.unsupervised.instance中的类
-
Filters instances according to the value of an attribute.
- RemoveWithValues() - 类的构造器 weka.filters.unsupervised.instance.RemoveWithValues
-
Default constructor
- renameAttribute() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
renames the current attribute
- renameAttribute() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
renames the current selected Attribute
- renameAttribute(int, String) - 类中的方法 weka.core.Instances
-
Renames an attribute.
- renameAttribute(Attribute, String) - 类中的方法 weka.core.Instances
-
Renames an attribute.
- renameAttributeAt(int, String) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
renames the attribute at the given col index
- renameAttributeAt(int, String) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
renames the attribute at the given col index
- renameAttributeValue(int, int, String) - 类中的方法 weka.core.Instances
-
Renames the value of a nominal (or string) attribute value.
- renameAttributeValue(Attribute, String, String) - 类中的方法 weka.core.Instances
-
Renames the value of a nominal (or string) attribute value.
- renameNodeValue(int, String, String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
change the name of a value of a node
- Reorder - weka.filters.unsupervised.attribute中的类
-
A filter that generates output with a new order of the attributes.
- Reorder() - 类的构造器 weka.filters.unsupervised.attribute.Reorder
- RepeatedHillClimber - weka.classifiers.bayes.net.search.global中的类
-
This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.
- RepeatedHillClimber - weka.classifiers.bayes.net.search.local中的类
-
This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.
- RepeatedHillClimber() - 类的构造器 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
- RepeatedHillClimber() - 类的构造器 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
- repeatLiteralsTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- replaceAllBy(Stack<T>) - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Replace all elements in the stack with the elements of another given stack.
- replaceMissingTipText() - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Returns the tip text for this property
- replaceMissingValues(double[]) - 类中的方法 weka.core.BinarySparseInstance
-
Does nothing, since we don't support missing values.
- replaceMissingValues(double[]) - 类中的方法 weka.core.Instance
-
Replaces all missing values in the instance with the values contained in the given array.
- replaceMissingValues(double[]) - 类中的方法 weka.core.SparseInstance
-
Replaces all missing values in the instance with the values contained in the given array.
- ReplaceMissingValues - weka.filters.unsupervised.attribute中的类
-
Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.
- ReplaceMissingValues() - 类的构造器 weka.filters.unsupervised.attribute.ReplaceMissingValues
- replaceMissingValuesTipText() - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Returns the tip text for this property
- replaceMissingWithMAX_VALUE(double[]) - 类中的静态方法 weka.core.Utils
-
Replaces all "missing values" in the given array of double values with MAX_VALUE.
- replaceSubstring(String, String, String) - 类中的静态方法 weka.core.Utils
-
Replaces with a new string, all occurrences of a string from another string.
- replot() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Quickly replot the display using cached probability estimates
- reportFrequencyTipText() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns the tip text for this property
- REPTree - weka.classifiers.trees中的类
-
Fast decision tree learner.
- REPTree() - 类的构造器 weka.classifiers.trees.REPTree
- repulsionTipText() - 类中的方法 weka.clusterers.CLOPE
-
Returns the tip text for this property
- resample(Random) - 类中的方法 weka.core.Instances
-
Creates a new dataset of the same size using random sampling with replacement.
- Resample - weka.filters.supervised.instance中的类
-
Produces a random subsample of a dataset using either sampling with replacement or without replacement.
The original dataset must fit entirely in memory. - Resample - weka.filters.unsupervised.instance中的类
-
Produces a random subsample of a dataset using either sampling with replacement or without replacement.
- Resample() - 类的构造器 weka.filters.supervised.instance.Resample
- Resample() - 类的构造器 weka.filters.unsupervised.instance.Resample
- resampleWithWeights(Random) - 类中的方法 weka.core.Instances
-
Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.
- resampleWithWeights(Random, boolean[]) - 类中的方法 weka.core.Instances
-
Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.
- resampleWithWeights(Random, double[]) - 类中的方法 weka.core.Instances
-
Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
- resampleWithWeights(Random, double[], boolean[]) - 类中的方法 weka.core.Instances
-
Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
- ReservoirSample - weka.filters.unsupervised.instance中的类
-
Produces a random subsample of a dataset using the reservoir sampling Algorithm "R" by Vitter.
- ReservoirSample() - 类的构造器 weka.filters.unsupervised.instance.ReservoirSample
- reset() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this to reset the unit for another run.
- reset() - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Call this to reset the value and error for this unit, ready for the next run.
- reset() - 类中的方法 weka.classifiers.functions.SPegasos
-
Reset the classifier.
- reset() - 类中的方法 weka.core.converters.AbstractFileLoader
-
Resets the loader ready to read a new data set
- reset() - 类中的方法 weka.core.converters.AbstractLoader
-
Default implementation sets retrieval mode to NONE
- reset() - 类中的方法 weka.core.converters.ArffLoader
-
Resets the Loader ready to read a new data set or the same data set again.
- reset() - 类中的方法 weka.core.converters.C45Loader
-
Resets the Loader ready to read a new data set or the same data set again.
- reset() - 类中的方法 weka.core.converters.ConverterUtils.DataSource
-
resets the loader.
- reset() - 类中的方法 weka.core.converters.CSVLoader
-
Resets the Loader ready to read a new data set or the same data set again.
- reset() - 类中的方法 weka.core.converters.DatabaseLoader
-
Resets the Loader ready to read a new data set
- reset() - 类中的方法 weka.core.converters.LibSVMLoader
-
Resets the Loader ready to read a new data set.
- reset() - 接口中的方法 weka.core.converters.Loader
-
Resets the Loader object ready to begin loading.
- reset() - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Resets the Loader ready to read a new data set
- reset() - 类中的方法 weka.core.converters.SVMLightLoader
-
Resets the Loader ready to read a new data set.
- reset() - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Resets the loader ready to read a new data set
- reset() - 类中的方法 weka.core.converters.XRFFLoader
-
Resets the Loader ready to read a new data set
- reset() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Resets all internal fields/counters.
- reset() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Resets all internal fields/counters.
- reset() - 类中的静态方法 weka.gui.beans.BeanConnection
-
Reset the list of connections
- reset(JComponent) - 类中的静态方法 weka.gui.beans.BeanInstance
-
Reset the list of beans
- resetAttIndex(boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Resets the boolean value in AttIndexes array
- resetAttIndexTo(LBR.Indexes) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Resets the boolean value in AttIndexes array based on another set of Indexes
- resetDatasetBasedOn(LBR.Indexes) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Resets the boolean values in Attribute and Instance array to reflect an empty dataset withthe same attributes set as in the incoming Indexes Object
- resetDistribution(Instances) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Sets distribution associated with model.
- resetDistribution(Instances) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Sets distribution associated with model.
- resetDistribution(Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Sets distribution associated with model.
- resetInstanceIndex(boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Resets the boolean value in the Instance Indexes array to a specified value
- resetOptions() - 类中的方法 weka.associations.Apriori
-
Resets the options to the default values.
- resetOptions() - 类中的方法 weka.associations.FPGrowth
-
Reset all options to their default values.
- resetOptions() - 类中的方法 weka.associations.PredictiveApriori
-
Resets the options to the default values.
- resetOptions() - 类中的方法 weka.associations.Tertius
-
Resets the options to the default values.
- resetOptions() - 类中的方法 weka.core.converters.AbstractFileSaver
-
resets the options
- resetOptions() - 类中的方法 weka.core.converters.AbstractSaver
-
resets the options
- resetOptions() - 类中的方法 weka.core.converters.ArffSaver
-
Resets the Saver
- resetOptions() - 类中的方法 weka.core.converters.C45Saver
-
Resets the Saver
- resetOptions() - 类中的方法 weka.core.converters.CSVSaver
-
Resets the Saver
- resetOptions() - 类中的方法 weka.core.converters.DatabaseSaver
-
Resets the Saver ready to save a new data set.
- resetOptions() - 类中的方法 weka.core.converters.LibSVMSaver
-
Resets the Saver
- resetOptions() - 类中的方法 weka.core.converters.SerializedInstancesSaver
-
Resets the Saver.
- resetOptions() - 类中的方法 weka.core.converters.SVMLightSaver
-
Resets the Saver.
- resetOptions() - 类中的方法 weka.core.converters.XRFFSaver
-
Resets the Saver
- resetStructure() - 类中的方法 weka.core.converters.AbstractSaver
-
Resets the structure (header information of the instances)
- resetStructure() - 类中的方法 weka.core.converters.DatabaseLoader
-
Resets the structure of instances
- resetTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- resetWriter() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Sets the writer to null.
- resetWriter() - 类中的方法 weka.core.converters.SerializedInstancesSaver
-
Resets the writer, setting writer and objectstream to null.
- ResidualModelSelection - weka.classifiers.trees.lmt中的类
-
Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals.
- ResidualModelSelection(int) - 类的构造器 weka.classifiers.trees.lmt.ResidualModelSelection
-
Constructor to create ResidualModelSelection object.
- ResidualSplit - weka.classifiers.trees.lmt中的类
-
Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals of the LogitBoost algorithm.
- ResidualSplit(int) - 类的构造器 weka.classifiers.trees.lmt.ResidualSplit
-
Creates a split object
- restoreBeans() - 类中的方法 weka.gui.beans.MetaBean
- restoreWeights() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this to have the connection restore from the saved weights.
- restoreWeights() - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Call this to have the connection restore from the saved weights.
- restoreWindows() - 类中的方法 weka.gui.Main
-
restores all windows.
- resultChanged(ResultChangedEvent) - 接口中的方法 weka.gui.sql.event.ResultChangedListener
-
This method gets called when a query has been executed.
- resultChanged(ResultChangedEvent) - 类中的方法 weka.gui.sql.SqlViewer
-
This method gets called when a query has been executed.
- resultChanged(ResultChangedEvent) - 类中的方法 weka.gui.sql.SqlViewerDialog
-
This method gets called when a query has been executed.
- ResultChangedEvent - weka.gui.sql.event中的类
-
An event that is generated when a different Result is activated in the ResultPanel.
- ResultChangedEvent(Object, String, String, String, String) - 类的构造器 weka.gui.sql.event.ResultChangedEvent
-
constructs the event
- ResultChangedListener - weka.gui.sql.event中的接口
-
A listener that is notified if another Result is activated in the ResultPanel.
- ResultHistoryPanel - weka.gui中的类
-
A component that accepts named stringbuffers and displays the name in a list box.
- ResultHistoryPanel(JTextComponent) - 类的构造器 weka.gui.ResultHistoryPanel
-
Create the result history object
- ResultHistoryPanel.RKeyAdapter - weka.gui中的类
-
Extension of KeyAdapter that implements Serializable.
- ResultHistoryPanel.RMouseAdapter - weka.gui中的类
-
Extension of MouseAdapter that implements Serializable.
- ResultListener - weka.experiment中的接口
-
Interface for objects able to listen for results obtained by a ResultProducer
- ResultMatrix - weka.experiment中的类
-
This matrix is a container for the datasets and classifier setups and their statistics.
- ResultMatrix() - 类的构造器 weka.experiment.ResultMatrix
-
initializes the matrix as 1x1 matrix
- ResultMatrix(int, int) - 类的构造器 weka.experiment.ResultMatrix
-
initializes the matrix with the given dimensions
- ResultMatrix(ResultMatrix) - 类的构造器 weka.experiment.ResultMatrix
-
initializes the matrix with the values from the given matrix
- ResultMatrixCSV - weka.experiment中的类
-
This matrix is a container for the datasets and classifier setups and their statistics.
- ResultMatrixCSV() - 类的构造器 weka.experiment.ResultMatrixCSV
-
initializes the matrix as 1x1 matrix
- ResultMatrixCSV(int, int) - 类的构造器 weka.experiment.ResultMatrixCSV
-
initializes the matrix with the given dimensions
- ResultMatrixCSV(ResultMatrix) - 类的构造器 weka.experiment.ResultMatrixCSV
-
initializes the matrix with the values from the given matrix
- ResultMatrixGnuPlot - weka.experiment中的类
-
This matrix is a container for the datasets and classifier setups and their statistics.
- ResultMatrixGnuPlot() - 类的构造器 weka.experiment.ResultMatrixGnuPlot
-
initializes the matrix as 1x1 matrix
- ResultMatrixGnuPlot(int, int) - 类的构造器 weka.experiment.ResultMatrixGnuPlot
-
initializes the matrix with the given dimensions
- ResultMatrixGnuPlot(ResultMatrix) - 类的构造器 weka.experiment.ResultMatrixGnuPlot
-
initializes the matrix with the values from the given matrix
- ResultMatrixHTML - weka.experiment中的类
-
This matrix is a container for the datasets and classifier setups and their statistics.
- ResultMatrixHTML() - 类的构造器 weka.experiment.ResultMatrixHTML
-
initializes the matrix as 1x1 matrix
- ResultMatrixHTML(int, int) - 类的构造器 weka.experiment.ResultMatrixHTML
-
initializes the matrix with the given dimensions
- ResultMatrixHTML(ResultMatrix) - 类的构造器 weka.experiment.ResultMatrixHTML
-
initializes the matrix with the values from the given matrix
- ResultMatrixLatex - weka.experiment中的类
-
This matrix is a container for the datasets and classifier setups and their statistics.
- ResultMatrixLatex() - 类的构造器 weka.experiment.ResultMatrixLatex
-
initializes the matrix as 1x1 matrix
- ResultMatrixLatex(int, int) - 类的构造器 weka.experiment.ResultMatrixLatex
-
initializes the matrix with the given dimensions
- ResultMatrixLatex(ResultMatrix) - 类的构造器 weka.experiment.ResultMatrixLatex
-
initializes the matrix with the values from the given matrix
- ResultMatrixPlainText - weka.experiment中的类
-
This matrix is a container for the datasets and classifier setups and their statistics.
- ResultMatrixPlainText() - 类的构造器 weka.experiment.ResultMatrixPlainText
-
initializes the matrix as 1x1 matrix
- ResultMatrixPlainText(int, int) - 类的构造器 weka.experiment.ResultMatrixPlainText
-
initializes the matrix with the given dimensions
- ResultMatrixPlainText(ResultMatrix) - 类的构造器 weka.experiment.ResultMatrixPlainText
-
initializes the matrix with the values from the given matrix
- ResultMatrixSignificance - weka.experiment中的类
-
This matrix is a container for the datasets and classifier setups and their statistics.
- ResultMatrixSignificance() - 类的构造器 weka.experiment.ResultMatrixSignificance
-
initializes the matrix as 1x1 matrix
- ResultMatrixSignificance(int, int) - 类的构造器 weka.experiment.ResultMatrixSignificance
-
initializes the matrix with the given dimensions
- ResultMatrixSignificance(ResultMatrix) - 类的构造器 weka.experiment.ResultMatrixSignificance
-
initializes the matrix with the values from the given matrix
- ResultPanel - weka.gui.sql中的类
-
Represents a panel for displaying the results of a query in table format.
- ResultPanel(JFrame) - 类的构造器 weka.gui.sql.ResultPanel
-
initializes the panel
- ResultProducer - weka.experiment中的接口
-
This interface defines the methods required for an object that produces results for different randomizations of a dataset.
- resultProducerTipText() - 类中的方法 weka.experiment.AveragingResultProducer
-
Returns the tip text for this property
- resultProducerTipText() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Returns the tip text for this property
- resultProducerTipText() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns the tip text for this property
- ResultSetHelper - weka.gui.sql中的类
-
Represents an extended JTable, containing a table model based on a ResultSet and the corresponding query.
- ResultSetHelper(ResultSet) - 类的构造器 weka.gui.sql.ResultSetHelper
-
initializes the helper, with unlimited number of rows.
- ResultSetHelper(ResultSet, int) - 类的构造器 weka.gui.sql.ResultSetHelper
-
initializes the helper, with the given maximum number of rows (less than 1 means unlimited).
- resultsetKey() - 类中的方法 weka.experiment.PairedTTester
-
Creates a key that maps resultset numbers to their descriptions.
- resultsetKey() - 接口中的方法 weka.experiment.Tester
-
Creates a key that maps resultset numbers to their descriptions.
- ResultSetTable - weka.gui.sql中的类
-
Represents an extended JTable, containing a table model based on a ResultSet and the corresponding query.
- ResultSetTable(String, String, String, String, ResultSetTableModel) - 类的构造器 weka.gui.sql.ResultSetTable
-
initializes the table
- ResultSetTableCellRenderer - weka.gui.sql中的类
-
Handles the background colors for missing values differently than the DefaultTableCellRenderer.
- ResultSetTableCellRenderer() - 类的构造器 weka.gui.sql.ResultSetTableCellRenderer
-
initializes the Renderer with a standard color
- ResultSetTableCellRenderer(Color, Color) - 类的构造器 weka.gui.sql.ResultSetTableCellRenderer
-
initializes the Renderer with the given colors
- ResultSetTableModel - weka.gui.sql中的类
-
The model for an SQL ResultSet.
- ResultSetTableModel(ResultSet) - 类的构造器 weka.gui.sql.ResultSetTableModel
-
initializes the model, retrieves all rows.
- ResultSetTableModel(ResultSet, int) - 类的构造器 weka.gui.sql.ResultSetTableModel
-
initializes the model, retrieves only the given amount of rows (0 means all).
- ResultsPanel - weka.gui.experiment中的类
-
This panel controls simple analysis of experimental results.
- ResultsPanel() - 类的构造器 weka.gui.experiment.ResultsPanel
-
Creates the results panel with no initial experiment.
- ResultVectorTableModel - weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI中的类
-
ResultVectorTableModel.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht
Date: Sep 12, 2004
Time: 9:23:31 PM
$ Revision 1.4 $ - ResultVectorTableModel(FastVector) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.ResultVectorTableModel
-
Constructs a default
DefaultTableModel
which is a table of zero columns and zero rows. - retainAll(Collection<?>) - 类中的方法 weka.core.Trie
-
Retains only the elements in this collection that are contained in the specified collection
- retrieveDir() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Gets the directory
- retrieveDir() - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- retrieveDir() - 接口中的方法 weka.core.converters.Saver
-
Gets the driectory of the output file This method is used in the KnowledgeFlow GUI.
- retrieveFile() - 类中的方法 weka.core.converters.AbstractFileLoader
-
get the File specified as the source
- retrieveFile() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Gets the destination file.
- retrieveFile() - 类中的方法 weka.core.converters.ArffLoader
-
get the File specified as the source
- retrieveFile() - 接口中的方法 weka.core.converters.FileSourcedConverter
-
Return the current source file/ destination file
- retrieveInstances() - 类中的方法 weka.experiment.InstanceQuery
-
Makes a database query using the query set through the -Q option to convert a table into a set of instances
- retrieveInstances(String) - 类中的方法 weka.experiment.InstanceQuery
-
Makes a database query to convert a table into a set of instances
- retrieveURL() - 类中的方法 weka.core.converters.ArffLoader
-
Return the current url
- retrieveURL() - 类中的方法 weka.core.converters.LibSVMLoader
-
Return the current url.
- retrieveURL() - 类中的方法 weka.core.converters.SVMLightLoader
-
Return the current url.
- retrieveURL() - 接口中的方法 weka.core.converters.URLSourcedLoader
-
Return the current url
- retrieveURL() - 类中的方法 weka.core.converters.XRFFLoader
-
Return the current url
- returnLeaves(FastVector[]) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Return a list containing all the leaves in the tree
- rev() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the reverse vector
- REVERSED - 接口中的静态变量 weka.gui.graphvisualizer.GraphConstants
-
Types of Edges
- reversedArcs(BayesNet) - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
Count nr of reversed arcs from other network compared to current network
- revertNewLines(String) - 类中的静态方法 weka.core.Utils
-
Reverts \r and \n in a string into carriage returns and new lines.
- REVISION - 类中的静态变量 weka.core.Version
-
the revision
- RevisionHandler - weka.core中的接口
-
For classes that should return their source control revision.
- RevisionUtils - weka.core中的类
-
Contains utility functions for handling revisions.
- RevisionUtils() - 类的构造器 weka.core.RevisionUtils
- RevisionUtils.Type - weka.core中的Enum Class
-
Enumeration of source control types.
- ridgeTipText() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Returns the tip text for this property
- ridgeTipText() - 类中的方法 weka.classifiers.functions.Logistic
-
Returns the tip text for this property
- ridgeTipText() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns the tip text for this property
- ridgeTipText() - 类中的方法 weka.classifiers.mi.MILR
-
Returns the tip text for this property
- Ridor - weka.classifiers.rules中的类
-
An implementation of a RIpple-DOwn Rule learner.
It generates a default rule first and then the exceptions for the default rule with the least (weighted) error rate. - Ridor() - 类的构造器 weka.classifiers.rules.Ridor
- RIGHT_PARENTHESES - 类中的变量 weka.experiment.ResultMatrix
-
the right parentheses for enumerating cols/rows
- rightNode() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the right child of this node
- rightSide(int, Instances) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Prints the condition satisfied by instances in a subset.
- rightSide(int, Instances) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Prints the condition satisfied by instances in a subset.
- rightSide(int, Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Prints left side of condition satisfied by instances in subset index.
- rightSide(int, Instances) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
Prints condition satisfied by instances in subset index.
- rightSide(int, Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Does nothing because no condition has to be satisfied.
- rightSide(int, Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Prints the condition satisfied by instances in a subset.
- rightSide(int, Instances) - 类中的方法 weka.classifiers.trees.j48.NoSplit
-
Does nothing because no condition has to be satisfied.
- rightSide(int, Instances) - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Prints the condition satisfied by instances in a subset.
- RINT - 接口中的静态变量 weka.core.mathematicalexpression.sym
- RINT - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- RipperRule() - 类的构造器 weka.classifiers.rules.JRip.RipperRule
-
Constructor
- RKeyAdapter() - 类的构造器 weka.gui.ResultHistoryPanel.RKeyAdapter
- rmCoveredBySuccessives(Instances, FastVector, int) - 类中的静态方法 weka.classifiers.rules.RuleStats
-
Static utility function to count the data covered by the rules after the given index in the given rules, and then remove them.
- RMouseAdapter() - 类的构造器 weka.gui.ResultHistoryPanel.RMouseAdapter
- rnorm(int, double, double, Random) - 类中的静态方法 weka.core.matrix.Maths
-
Generates a sample of a normal distribution.
- rocAnalysisTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- rocToString() - 类中的方法 weka.associations.tertius.Rule
-
Return a String giving the TP-rate and FP-rate of this rule.
- ROOT_FINDER_ACCURACY - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
- ROOT_FINDER_MAX_ITER - 接口中的静态变量 weka.classifiers.lazy.kstar.KStarConstants
-
How close the root finder for numeric and nominal have to get
- ROOT_NODE - 类中的静态变量 weka.core.xml.XMLOptions
-
the root node.
- ROOT_NODE - 类中的静态变量 weka.core.xml.XMLSerialization
-
the root node of the XML document
- rootMeanPriorSquaredError() - 类中的方法 weka.classifiers.Evaluation
-
Returns the root mean prior squared error.
- rootMeanSquaredError() - 类中的方法 weka.classifiers.Evaluation
-
Returns the root mean squared error.
- rootRelativeSquaredError() - 类中的方法 weka.classifiers.Evaluation
-
Returns the root relative squared error if the class is numeric.
- rotate(double) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- rotate(double, double, double) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- RotationForest - weka.classifiers.meta中的类
-
Class for construction a Rotation Forest.
- RotationForest() - 类的构造器 weka.classifiers.meta.RotationForest
-
Constructor.
- round(double) - 类中的静态方法 weka.core.Utils
-
Rounds a double to the next nearest integer value.
- roundDouble(double, int) - 类中的静态方法 weka.core.Utils
-
Rounds a double to the given number of decimal places.
- RPAREN - 接口中的静态变量 weka.core.mathematicalexpression.sym
- RPAREN - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- rsolve(PaceMatrix, IntVector, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Solves upper-triangular equation
R x = b
On output, the solution is stored in b - Rule - weka.associations.tertius中的类
-
Class representing a rule with a body and a head.
- Rule - weka.classifiers.rules中的类
-
Abstract class of generic rule
- Rule - weka.classifiers.trees.m5中的类
-
Generates a single m5 tree or rule
- Rule() - 类的构造器 weka.classifiers.rules.Rule
- Rule() - 类的构造器 weka.classifiers.trees.m5.Rule
-
Constructor declaration
- Rule(boolean, int, boolean, boolean, boolean, boolean) - 类的构造器 weka.associations.tertius.Rule
-
Constructor for a rule when the counter-instances are not stored, giving all the constraints applied to this rule.
- Rule(Instances, boolean, int, boolean, boolean, boolean, boolean) - 类的构造器 weka.associations.tertius.Rule
-
Constructor for a rule when the counter-instances are stored, giving all the constraints applied to this rule.
- RuleGeneration - weka.associations中的类
-
Class implementing the rule generation procedure of the predictive apriori algorithm.
- RuleGeneration(ItemSet) - 类的构造器 weka.associations.RuleGeneration
-
Constructor
- RuleItem - weka.associations中的类
-
Class for storing an (class) association rule.
- RuleItem() - 类的构造器 weka.associations.RuleItem
-
Constructor for an empty RuleItem
- RuleItem(ItemSet, ItemSet, int, int, double[], Hashtable) - 类的构造器 weka.associations.RuleItem
-
Constructor
- RuleItem(RuleItem) - 类的构造器 weka.associations.RuleItem
-
Constructor that generates a RuleItem out of a given one
- RuleNode - weka.classifiers.trees.m5中的类
-
Constructs a node for use in an m5 tree or rule
- RuleNode(double, double, RuleNode) - 类的构造器 weka.classifiers.trees.m5.RuleNode
-
Creates a new
RuleNode
instance. - rulesMustContainTipText() - 类中的方法 weka.associations.FPGrowth
-
Returns the tip text for this property
- RuleStats - weka.classifiers.rules中的类
-
This class implements the statistics functions used in the propositional rule learner, from the simpler ones like count of true/false positive/negatives, filter data based on the ruleset, etc.
- RuleStats() - 类的构造器 weka.classifiers.rules.RuleStats
-
Default constructor
- RuleStats(Instances, FastVector) - 类的构造器 weka.classifiers.rules.RuleStats
-
Constructor that provides ruleset and data
- run() - 类中的方法 weka.associations.Tertius
-
Run the search.
- run() - 类中的方法 weka.gui.beans.FlowRunner
-
Launch all loaded KnowledgeFlow
- RUN_FIELD_NAME - 类中的静态变量 weka.experiment.CrossValidationResultProducer
-
The name of the key field containing the run number
- RUN_FIELD_NAME - 类中的静态变量 weka.experiment.RandomSplitResultProducer
-
The name of the key field containing the run number
- runCommand(String) - 类中的方法 weka.gui.SimpleCLIPanel
-
Executes a simple cli command.
- runExperiment() - 类中的方法 weka.experiment.Experiment
-
Runs all iterations of the experiment, continuing past errors.
- runExperiment() - 类中的方法 weka.experiment.RemoteExperiment
-
Overides runExperiment in Experiment
- runFileLoader(AbstractFileLoader, String[]) - 类中的静态方法 weka.core.converters.AbstractFileLoader
-
runs the given loader with the provided options
- runFileSaver(AbstractFileSaver, String[]) - 类中的静态方法 weka.core.converters.AbstractFileSaver
-
runs the given saver with the specified options
- RunNumberPanel - weka.gui.experiment中的类
-
This panel controls configuration of lower and upper run numbers in an experiment.
- RunNumberPanel() - 类的构造器 weka.gui.experiment.RunNumberPanel
-
Creates the panel with no initial experiment.
- RunNumberPanel(Experiment) - 类的构造器 weka.gui.experiment.RunNumberPanel
-
Creates the panel with the supplied initial experiment.
- RunPanel - weka.gui.experiment中的类
-
This panel controls the running of an experiment.
- RunPanel() - 类的构造器 weka.gui.experiment.RunPanel
-
Creates the run panel with no initial experiment.
- RunPanel(Experiment) - 类的构造器 weka.gui.experiment.RunPanel
-
Creates the panel with the supplied initial experiment.
- runsTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- runsTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
- runsTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- runsTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
- runsTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- runsTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
- runsTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- runsTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
- runTokenizer(Tokenizer, String[]) - 类中的静态方法 weka.core.tokenizers.Tokenizer
-
initializes the given tokenizer with the given options and runs the tokenizer over all the remaining strings in the options array.
S
- s_fileFormatsAvailable - 类中的静态变量 weka.gui.beans.SerializedModelSaver
-
Available file formats.
- s_startupListeners - 类中的静态变量 weka.gui.beans.KnowledgeFlowApp
- sameClauseAs(Rule) - 类中的方法 weka.associations.tertius.Rule
-
Test if this rule and another rule correspond to the same clause.
- sameClauseTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- SAMPLE_SIZE_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: Sample Size
- sampleSizePercentTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- sampleSizePercentTipText() - 类中的方法 weka.filters.supervised.instance.Resample
-
Returns the tip text for this property.
- sampleSizePercentTipText() - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Returns the tip text for this property
- sampleSizeTipText() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns the tip text for this property
- sampleSizeTipText() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns the tip text for this property
- sampleSizeTipText() - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Returns the tip text for this property
- satisfies(Instance) - 类中的方法 weka.associations.tertius.AttributeValueLiteral
- satisfies(Instance) - 类中的方法 weka.associations.tertius.Literal
- save(StringBuffer) - 类中的方法 weka.gui.SaveBuffer
-
Save a buffer
- saveBatch() - 类中的方法 weka.gui.beans.Saver
-
Saves instances in batch mode
- saveBinary(File, Object, Instances) - 类中的静态方法 weka.gui.beans.SerializedModelSaver
-
Save a model in binary form.
- SaveBuffer - weka.gui中的类
-
This class handles the saving of StringBuffers to files.
- SaveBuffer(Logger, Component) - 类的构造器 weka.gui.SaveBuffer
-
Constructor
- saveComponent() - 类中的方法 weka.gui.visualize.PrintableComponent
-
displays a save dialog for saving the panel to a file.
- saveComponent() - 接口中的方法 weka.gui.visualize.PrintableHandler
-
displays a save dialog for saving the component to a file.
- saveComponent() - 类中的方法 weka.gui.visualize.PrintablePanel
-
displays a save dialog for saving the panel to a file.
- saveFile() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
saves the current data into a file
- saveFileAs() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
saves the current data into a new file
- saveInstanceDataTipText() - 类中的方法 weka.classifiers.trees.ADTree
- saveInstanceDataTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- saveInstanceDataTipText() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the tip text for this property
- saveInstanceDataTipText() - 类中的方法 weka.clusterers.Cobweb
-
Returns the tip text for this property
- saveInstancesTipText() - 类中的方法 weka.classifiers.trees.M5P
-
Returns the tip text for this property
- saveInstancesToFile(AbstractFileSaver, Instances) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
saves the data with the specified saver
- saveKOML(File, Object, Instances) - 类中的静态方法 weka.gui.beans.SerializedModelSaver
-
Save a model in KOML deep object serialized XML form.
- saveLayout(OutputStream) - 类中的方法 weka.gui.beans.KnowledgeFlowApp
-
Save the knowledge flow into the OutputStream passed at input.
- saveModel() - 类中的方法 weka.gui.beans.Classifier
- saveModel() - 类中的方法 weka.gui.beans.Clusterer
- Saver - weka.gui.beans中的类
-
Saves data sets using weka.core.converter classes
- Saver - weka.core.converters中的接口
-
Interface to something that can save Instances to an output destination in some format.
- Saver() - 类的构造器 weka.gui.beans.Saver
-
Contsructor
- SAVER_DIALOG - 类中的静态变量 weka.gui.ConverterFileChooser
-
the saver dialog
- SaverBeanInfo - weka.gui.beans中的类
-
Bean info class for the saver bean
- SaverBeanInfo() - 类的构造器 weka.gui.beans.SaverBeanInfo
- SaverCustomizer - weka.gui.beans中的类
-
GUI Customizer for the saver bean
- SaverCustomizer() - 类的构造器 weka.gui.beans.SaverCustomizer
-
Constructor
- saveSize() - 类中的方法 weka.gui.sql.SqlViewer
-
obtains the size of the panel and saves it in the history.
- saveToFile(String, Object) - 类中的静态方法 weka.core.Debug
-
writes the serialized object to the speicified file
- saveWeights() - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this to have the connection save the current weights.
- saveWeights() - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Call this to have the connection save the current weights.
- saveWorkingInstancesToFileQ() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Queries the user for a file to save instances as, then saves the instances in a background process.
- saveXStream(File, Object, Instances) - 类中的静态方法 weka.gui.beans.SerializedModelSaver
-
Save a model in XStream deep object serialized XML form.
- scalarMultiply(double) - 类中的方法 weka.core.AlgVector
-
Computes the scalar product of this vector with a scalar
- scale(double, double) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- scale(int) - 类中的方法 weka.gui.beans.BeanVisual
-
Reduce this BeanVisual's icon size by the given factor
- scaleTipText() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns the tip text for this property.
- Scanner - weka.core.mathematicalexpression中的类
-
A scanner for mathematical expressions.
- Scanner - weka.filters.unsupervised.instance.subsetbyexpression中的类
-
A scanner for evaluating whether an Instance is to be included in a subset or not.
- Scanner(InputStream) - 类的构造器 weka.core.mathematicalexpression.Scanner
-
Creates a new scanner.
- Scanner(InputStream) - 类的构造器 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Creates a new scanner.
- Scanner(InputStream, SymbolFactory) - 类的构造器 weka.core.mathematicalexpression.Scanner
- Scanner(InputStream, SymbolFactory) - 类的构造器 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
- Scanner(Reader) - 类的构造器 weka.core.mathematicalexpression.Scanner
-
Creates a new scanner There is also a java.io.InputStream version of this constructor.
- Scanner(Reader) - 类的构造器 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Creates a new scanner There is also a java.io.InputStream version of this constructor.
- ScatterPlotMatrix - weka.gui.beans中的类
-
Bean that encapsulates weka.gui.visualize.MatrixPanel for displaying a scatter plot matrix.
- ScatterPlotMatrix() - 类的构造器 weka.gui.beans.ScatterPlotMatrix
- ScatterPlotMatrixBeanInfo - weka.gui.beans中的类
-
Bean info class for the scatter plot matrix bean
- ScatterPlotMatrixBeanInfo() - 类的构造器 weka.gui.beans.ScatterPlotMatrixBeanInfo
- ScatterSearchV1 - weka.attributeSelection中的类
-
Class for performing the Sequential Scatter Search.
- ScatterSearchV1() - 类的构造器 weka.attributeSelection.ScatterSearchV1
- ScatterSearchV1.Subset - weka.attributeSelection中的类
- SCHOOL - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The name of the school where a thesis was written.
- Scoreable - weka.classifiers.bayes.net.search.local中的接口
-
Interface for allowing to score a classifier
- scoreTypeTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
- scrollToVisible(int, int) - 类中的方法 weka.gui.JTableHelper
-
Assumes table is contained in a JScrollPane.
- scrollToVisible(JTable, int, int) - 类中的静态方法 weka.gui.JTableHelper
-
Assumes table is contained in a JScrollPane.
- search() - 类中的方法 weka.associations.Tertius
-
Search in the space of hypotheses the rules that have the highest confirmation.
- search() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
searches for a string in the cells
- search() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
searches for a string in the cells
- search(Vector, String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Helper function to search for the given target string in a given vector in which the elements' value may hopefully is equal to the target.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.ASSearch
-
Searches the attribute subset/ranking space.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.BestFirst
-
Searches the attribute subset space by best first search
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
Searches the attribute subset space using an exhaustive search.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.GeneticSearch
-
Searches the attribute subset space using a genetic algorithm.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Searches the attribute subset space by forward selection.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Searches the attribute subset space by linear forward selection
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.RaceSearch
-
Searches the attribute subset space by racing cross validation errors of competing subsets
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.RandomSearch
-
Searches the attribute subset space randomly.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.Ranker
-
Kind of a dummy search algorithm.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.RankSearch
-
Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Searches the attribute subset space using Scatter Search.
- search(ASEvaluation, Instances) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Searches the attribute subset space by subset size forward selection
- search(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
search determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
- search(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- search(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
search determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
- search(BayesNet, Instances) - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- SearchAlgorithm - weka.classifiers.bayes.net.search中的类
-
This is the base class for all search algorithms for learning Bayes networks.
- SearchAlgorithm() - 类的构造器 weka.classifiers.bayes.net.search.SearchAlgorithm
-
c'tor
- searchAlgorithmTipText() - 类中的方法 weka.classifiers.bayes.BayesNet
- searchBackwardsTipText() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns the tip text for this property
- searchFinish() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Signals end of the nearest neighbour search.
- searchFinish() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Signals end of the nearest neighbour search.
- SEARCHPATH_ALL - 类中的静态变量 weka.classifiers.trees.ADTree
-
search mode: Expand all paths
- SEARCHPATH_HEAVIEST - 类中的静态变量 weka.classifiers.trees.ADTree
-
search mode: Expand the heaviest path
- SEARCHPATH_RANDOM - 类中的静态变量 weka.classifiers.trees.ADTree
-
search mode: Expand a random path
- SEARCHPATH_ZPURE - 类中的静态变量 weka.classifiers.trees.ADTree
-
search mode: Expand the best z-pure path
- searchPathTipText() - 类中的方法 weka.classifiers.trees.ADTree
- searchPercentTipText() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns the tip text for this property
- searchPoints(int, int, boolean) - 类中的方法 weka.gui.visualize.Plot2D
-
Pops up a window displaying attribute information on any instances at a point+-plotting_point_size (in panel coordinates)
- searchStart() - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
Signals start of the nearest neighbour search.
- searchStart() - 类中的方法 weka.core.neighboursearch.TreePerformanceStats
-
Signals start of the nearest neighbour search.
- searchTerminationTipText() - 类中的方法 weka.attributeSelection.BestFirst
-
Returns the tip text for this property
- searchTerminationTipText() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the tip text for this property
- searchTipText() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Returns the tip text for this property
- searchTipText() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns the tip text for this property
- searchTipText() - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Returns the tip text for this property
- secondInstanceProduced(InstanceEvent) - 类中的方法 weka.gui.streams.InstanceJoiner
- secondInstanceProduced(InstanceEvent) - 接口中的方法 weka.gui.streams.SerialInstanceListener
- secondValueIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
- secondValueIndexTipText() - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
- seedTipText() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Returns a string for this option suitable for display in the gui as a tip text
- seedTipText() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- seedTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
- seedTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- seedTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- seedTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
- seedTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- seedTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- seedTipText() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.RandomizableClassifier
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.RandomizableMultipleClassifiersCombiner
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.RandomizableSingleClassifierEnhancer
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.rules.JRip
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.rules.PART
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.trees.RandomForest
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.trees.RandomTree
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.clusterers.Cobweb
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.clusterers.RandomizableClusterer
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.clusterers.RandomizableDensityBasedClusterer
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.clusterers.RandomizableSingleClustererEnhancer
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Returns the tip text for this property.
- seedTipText() - 类中的方法 weka.datagenerators.DataGenerator
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Returns the tip text for this property.
- seedTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Returns the tip text for this property
- seedTipText() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Tip text for this property
- seedTipText() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Tip text for this property
- select(int, int[], int, int, int) - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Implements computation of the kth-smallest element according to Manber's "Introduction to Algorithms".
- select(int, int[], int, int, int) - 类中的方法 weka.core.neighboursearch.kdtrees.MedianOfWidestDimension
-
Implements computation of the kth-smallest element according to Manber's "Introduction to Algorithms".
- select(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Executes a SQL SELECT query that returns a ResultSet.
- SelectAttributes(ASEvaluation, String[]) - 类中的静态方法 weka.attributeSelection.AttributeSelection
-
Perform attribute selection with a particular evaluator and a set of options specifying search method and input file etc.
- SelectAttributes(ASEvaluation, String[], Instances) - 类中的静态方法 weka.attributeSelection.AttributeSelection
-
Perform attribute selection with a particular evaluator and a set of options specifying search method and options for the search method and evaluator.
- SelectAttributes(Instances) - 类中的方法 weka.attributeSelection.AttributeSelection
-
Perform attribute selection on the supplied training instances.
- selectAttributesCVSplit(Instances) - 类中的方法 weka.attributeSelection.AttributeSelection
-
Select attributes for a split of the data.
- selectedAttributes() - 类中的方法 weka.attributeSelection.AttributeSelection
-
get the final selected set of attributes.
- SelectedTag - weka.core中的类
-
Represents a selected value from a finite set of values, where each value is a Tag (i.e.
- SelectedTag(int, Tag[]) - 类的构造器 weka.core.SelectedTag
-
Creates a new
SelectedTag
instance. - SelectedTag(String, Tag[]) - 类的构造器 weka.core.SelectedTag
-
Creates a new
SelectedTag
instance. - SelectedTagEditor - weka.gui中的类
-
A PropertyEditor that uses tags, where the tags are obtained from a weka.core.SelectedTag object.
- SelectedTagEditor() - 类的构造器 weka.gui.SelectedTagEditor
- SELECTION_GREEDY - 类中的静态变量 weka.classifiers.functions.LinearRegression
-
Attribute selection method: Greedy method
- SELECTION_M5 - 类中的静态变量 weka.classifiers.functions.LinearRegression
-
Attribute selection method: M5 method
- SELECTION_NONE - 类中的静态变量 weka.classifiers.functions.LinearRegression
-
Attribute selection method: No attribute selection
- selectionThresholdTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- selectModel(Instances) - 类中的方法 weka.classifiers.trees.j48.BinC45ModelSelection
-
Selects C4.5-type split for the given dataset.
- selectModel(Instances) - 类中的方法 weka.classifiers.trees.j48.C45ModelSelection
-
Selects C4.5-type split for the given dataset.
- selectModel(Instances) - 类中的方法 weka.classifiers.trees.j48.ModelSelection
-
Selects a model for the given dataset.
- selectModel(Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeModelSelection
-
Selects NBTree-type split for the given dataset.
- selectModel(Instances) - 类中的方法 weka.classifiers.trees.lmt.ResidualModelSelection
-
Method not in use
- selectModel(Instances, double[][], double[][]) - 类中的方法 weka.classifiers.trees.lmt.ResidualModelSelection
-
Selects split based on residuals for the given dataset.
- selectModel(Instances, Instances) - 类中的方法 weka.classifiers.trees.j48.BinC45ModelSelection
-
Selects C4.5-type split for the given dataset.
- selectModel(Instances, Instances) - 类中的方法 weka.classifiers.trees.j48.C45ModelSelection
-
Selects C4.5-type split for the given dataset.
- selectModel(Instances, Instances) - 类中的方法 weka.classifiers.trees.j48.ModelSelection
-
Selects a model for the given train data using the given test data
- selectModel(Instances, Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeModelSelection
-
Selects NBTree-type split for the given dataset.
- selectModel(Instances, Instances) - 类中的方法 weka.classifiers.trees.lmt.ResidualModelSelection
-
Method not in use
- SEND_INSTANCES - 类中的静态变量 weka.gui.treevisualizer.TreeDisplayEvent
-
Command to remove instances from this node and send them to the VisualizePanel.
- separable(DoubleVector, int, int, double) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Return true if a value can be considered for mixture estimation separately from the data indexed between i0 and i1
- separable(DoubleVector, int, int, double) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
- separable(DoubleVector, int, int, double) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
- seq(int, int) - 类中的静态方法 weka.core.matrix.IntVector
-
Generates an IntVector that stores all integers inclusively between two integers.
- Sequence - weka.associations.gsp中的类
-
Class representing a sequence of elements/itemsets.
- Sequence() - 类的构造器 weka.associations.gsp.Sequence
-
Constructor.
- Sequence(int) - 类的构造器 weka.associations.gsp.Sequence
-
Constructor accepting an int value as parameter to set the support count.
- Sequence(FastVector) - 类的构造器 weka.associations.gsp.Sequence
-
Constructor accepting a set of elements as parameter.
- SequentialDatabase - weka.clusterers.forOPTICSAndDBScan.Databases中的类
-
SequentialDatabase.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 20, 2004
Time: 1:23:38 PM
$ Revision 1.4 $ - SequentialDatabase(Instances) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Constructs a new sequential database and holds the original instances
- SERFileFilter - weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI中的类
-
SERFileFilter.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht
Date: Sep 15, 2004
Time: 6:54:56 PM
$ Revision 1.4 $ - SERFileFilter(String, String) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERFileFilter
- SERIAL_VERSION_UID - 类中的静态变量 weka.core.SerializationHelper
-
the field name of serialVersionUID.
- SerialInstanceListener - weka.gui.streams中的接口
-
Defines an interface for objects able to produce two output streams of instances.
- SerializationHelper - weka.core中的类
-
A helper class for determining serialVersionUIDs and checking whether classes contain one and/or need one.
- SerializationHelper() - 类的构造器 weka.core.SerializationHelper
- serialize(Object) - 类中的静态方法 weka.core.xml.XStream
-
Serializes the supplied object xml
- SERIALIZED_OBJ_FILE_EXTENSION - 类中的静态变量 weka.core.Instances
-
The filename extension that should be used for bin.
- SerializedClassifier - weka.classifiers.misc中的类
-
A wrapper around a serialized classifier model.
- SerializedClassifier() - 类的构造器 weka.classifiers.misc.SerializedClassifier
- serializedClassifierFileTipText() - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Returns the tip text for this property.
- SerializedInstancesLoader - weka.core.converters中的类
-
Reads a source that contains serialized Instances.
- SerializedInstancesLoader() - 类的构造器 weka.core.converters.SerializedInstancesLoader
- SerializedInstancesSaver - weka.core.converters中的类
-
Serializes the instances to a file with extension bsi.
- SerializedInstancesSaver() - 类的构造器 weka.core.converters.SerializedInstancesSaver
-
Constructor.
- SerializedModelSaver - weka.gui.beans中的类
-
A bean that saves serialized models
- SerializedModelSaver() - 类的构造器 weka.gui.beans.SerializedModelSaver
-
Constructor.
- SerializedModelSaverBeanInfo - weka.gui.beans中的类
-
Bean info class for the serialized model saver bean
- SerializedModelSaverBeanInfo() - 类的构造器 weka.gui.beans.SerializedModelSaverBeanInfo
- SerializedModelSaverCustomizer - weka.gui.beans中的类
-
GUI Customizer for the SerializedModelSaver bean
- SerializedModelSaverCustomizer() - 类的构造器 weka.gui.beans.SerializedModelSaverCustomizer
-
Constructor
- SerializedObject - weka.core中的类
-
Class for storing an object in serialized form in memory.
- SerializedObject(Object) - 类的构造器 weka.core.SerializedObject
-
Creates a new serialized object (without compression).
- SerializedObject(Object, boolean) - 类的构造器 weka.core.SerializedObject
-
Creates a new serialized object.
- serializePMMLModel(PMMLModel, File) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Serialize a
PMMLModel
object that encapsulates a PMML model - serializePMMLModel(PMMLModel, OutputStream) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Serialize a
PMMLModel
object that encapsulates a PMML model - serializePMMLModel(PMMLModel, String) - 类中的静态方法 weka.core.pmml.PMMLFactory
-
Serialize a
PMMLModel
object that encapsulates a PMML model - SerialUIDChanger - weka.core.xml中的类
-
This class enables one to change the UID of a serialized object and therefore not losing the data stored in the binary format.
- SerialUIDChanger() - 类的构造器 weka.core.xml.SerialUIDChanger
- SERIES - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The name of a series or set of books.
- SERObject - weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI中的类
-
SERObject.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht
Date: Sep 15, 2004
Time: 9:43:00 PM
$ Revision 1.4 $ - SERObject(FastVector, int, int, double, int, boolean, String, String, int, String) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERObject
- set(double) - 类中的方法 weka.core.matrix.DoubleVector
-
Set all elements to a value
- set(int) - 类中的方法 weka.core.matrix.IntVector
-
Sets the value of an element.
- set(int, double) - 类中的方法 weka.core.matrix.DoubleVector
-
Set a single element.
- set(int, int) - 类中的方法 weka.core.matrix.IntVector
-
Sets a single element.
- set(int, int, double) - 类中的方法 weka.core.matrix.DoubleVector
-
Set some elements to a value
- set(int, int, double) - 类中的方法 weka.core.matrix.Matrix
-
Set a single element.
- set(int, int, double[], int) - 类中的方法 weka.core.matrix.DoubleVector
-
Set some elements using a 2-D array
- set(int, int, int[], int) - 类中的方法 weka.core.matrix.IntVector
-
Sets the values of elements from an int array.
- set(int, int, DoubleVector, int) - 类中的方法 weka.core.matrix.DoubleVector
-
Set some elements using a DoubleVector.
- set(int, int, IntVector, int) - 类中的方法 weka.core.matrix.IntVector
-
Sets the values of elements from another IntVector.
- set(int, Object) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Replaces the element at the specified position in this list with the specified element.
- set(int, T) - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Sets the ith element in the stack.
- set(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Set the elements using a DoubleVector
- set(IntVector) - 类中的方法 weka.core.matrix.IntVector
-
Sets the values of elements from another IntVector.
- setAcuity(double) - 类中的方法 weka.clusterers.Cobweb
-
set the acuity.
- setAdditionalMeasures(String[]) - 类中的方法 weka.experiment.AveragingResultProducer
-
Set a list of method names for additional measures to look for in SplitEvaluators.
- setAdditionalMeasures(String[]) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Set a list of method names for additional measures to look for in Classifiers.
- setAdditionalMeasures(String[]) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Set a list of method names for additional measures to look for in SplitEvaluators.
- setAdditionalMeasures(String[]) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Set a list of method names for additional measures to look for in SplitEvaluators.
- setAdditionalMeasures(String[]) - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Set a list of method names for additional measures to look for in Classifiers.
- setAdditionalMeasures(String[]) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Set a list of method names for additional measures to look for in SplitEvaluators.
- setAdditionalMeasures(String[]) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Set a list of method names for additional measures to look for in SplitEvaluators.
- setAdditionalMeasures(String[]) - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Set a list of method names for additional measures to look for in Classifiers.
- setAdditionalMeasures(String[]) - 接口中的方法 weka.experiment.ResultProducer
-
Sets a list of method names for additional measures to look for in SplitEvaluators.
- setAdditionalMeasures(String[]) - 接口中的方法 weka.experiment.SplitEvaluator
-
Sets a list of method names for additional measures to look for in SplitEvaluators.
- setAdjustWeights(boolean) - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Sets whether the instance weights will be adjusted to maintain total weight per class.
- setAdvanceDataSetFirst(boolean) - 类中的方法 weka.experiment.Experiment
-
Set the value of m_AdvanceDataSetFirst.
- setAlgorithm(SelectedTag) - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Sets the type of algorithm to use
- setAlgorithm(SelectedTag) - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Sets the type of algorithm to use
- setAlgorithmType(SelectedTag) - 类中的方法 weka.classifiers.mi.MILR
-
Sets the algorithm type.
- setAllowUnclassifiedInstances(boolean) - 类中的方法 weka.classifiers.trees.RandomTree
-
Set the value of AllowUnclassifiedInstances.
- setAlpha(double) - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
Set prior used in probability table estimation
- setAlpha(double) - 类中的方法 weka.classifiers.functions.Winnow
-
Set the value of Alpha.
- setAmplitude(double) - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Sets the amplitude multiplier.
- setAnimated() - 类中的方法 weka.gui.beans.BeanVisual
-
Set the animated version of the icon
- setAppendPredictedProbabilities(boolean) - 类中的方法 weka.gui.beans.PredictionAppender
-
Set whether to append predicted probabilities rather than class value (for discrete class data sets)
- setAppropriateSize() - 类中的方法 weka.classifiers.bayes.net.GUI
-
Sets the preferred size for m_GraphPanel GraphPanel to the minimum size that is neccessary to display the graph.
- setArffFile(String) - 类中的方法 weka.gui.streams.InstanceLoader
- setArffFile(String) - 类中的方法 weka.gui.streams.InstanceSavePanel
- setArtificialSize(double) - 类中的方法 weka.classifiers.meta.Decorate
-
Sets factor that determines number of artificial examples to generate.
- setAssociatedConnections(Vector) - 类中的方法 weka.gui.beans.MetaBean
- setAssociator(Associator) - 类中的方法 weka.associations.CheckAssociator
-
Set the associator to test.
- setAssociator(Associator) - 类中的方法 weka.associations.SingleAssociatorEnhancer
-
Set the base associator.
- setAssociator(Associator) - 类中的方法 weka.gui.beans.Associator
-
Set the associator for this wrapper
- setAsText(String) - 类中的方法 weka.gui.CostMatrixEditor
-
Some objects can be represented as text, but a cost matrix cannot.
- setAsText(String) - 类中的方法 weka.gui.GenericArrayEditor
-
Returns null as we don't support getting/setting values as text.
- setAsText(String) - 类中的方法 weka.gui.GenericObjectEditor
-
Returns null as we don't support getting/setting values as text.
- setAsText(String) - 类中的方法 weka.gui.SelectedTagEditor
-
Sets the current property value as text.
- setAsText(String) - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Sets the date format string.
- setAttIndex(int, boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Changes the boolean value at the specified index in the AttIndexes array
- setAttList_Irr(boolean[]) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Sets the array that defines which of the attributes are seen to be irrelevant.
- setAttribute(int) - 类中的方法 weka.gui.AttributeSummaryPanel
-
Sets the attribute that statistics will be displayed for.
- setAttribute(int) - 类中的方法 weka.gui.AttributeVisualizationPanel
-
Tells the panel which attribute to visualize.
- setAttributeEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Set the attribute evaluator to use
- setAttributeEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.RaceSearch
-
Set the attribute evaluator to use for generating the ranking.
- setAttributeEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.RankSearch
-
Set the attribute evaluator to use for generating the ranking.
- setAttributeID(int) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Set the index of Attibute Identifying the instances
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Sets index of the attribute used.
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Sets index of the attribute used.
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Sets index of the attribute used.
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Sets the index of the attribute used.
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Sets index of the attribute used.
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Sets index of the attribute used.
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Sets index of the attribute used.
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Sets index of the attribute used.
- setAttributeIndex(String) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Sets index of the attribute used.
- setAttributeIndexes(String) - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Sets index of the attribute used.
- setAttributeIndices(String) - 接口中的方法 weka.core.DistanceFunction
-
Sets the range of attributes to use in the calculation of the distance.
- setAttributeIndices(String) - 类中的方法 weka.core.NormalizableDistance
-
Sets the range of attributes to use in the calculation of the distance.
- setAttributeIndices(String) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Set which attributes are to be copied (or kept if invert is true)
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Set which attributes are to be copied (or kept if invert is true)
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Set which attributes are to be deleted (or kept if invert is true)
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Sets which attributes are to be used for interquartile calculations and outlier/extreme value detection (only numeric attributes among the selection will be used).
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Sets which attributes are to be acted on.
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Sets the columns to use, e.g., first-last or first-3,5-last
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Sets which attributes are to be "nominalized" (only numeric attributes among the selection will be transformed).
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Set which attributes are to be transformed (or kept if invert is true).
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Set which attributes are to be deleted (or kept if invert is true)
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Set which attributes are to be copied (or kept if invert is true)
- setAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets which attributes are to be worked on.
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Set which attributes are to be copied (or kept if invert is true)
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Set which attributes are to be copied (or kept if invert is true)
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Set which attributes are to be deleted (or kept if invert is true)
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Sets which attributes are to be used for interquartile calculations and outlier/extreme value detection (only numeric attributes among the selection will be used).
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Sets which attributes are to be transoformed to nominal.
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Set which attributes are to be transformed (or kept if invert is true)
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Set which attributes are to be deleted (or kept if invert is true)
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Set which attributes are to be copied (or kept if invert is true)
- setAttributeIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets which attributes are to be processed.
- setAttributeName(String) - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Set the new attribute's name.
- setAttributeName(String) - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Set the new attribute's name
- setAttributeNamePrefix(String) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Set the attribute name prefix.
- setAttributeRange(String) - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Sets range of indices of the attributes used.
- setAttributeSelectionMethod(SelectedTag) - 类中的方法 weka.classifiers.functions.LinearRegression
-
Sets the method used to select attributes for use in the linear regression.
- setAttributeType(SelectedTag) - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Sets the type of attribute to generate.
- setAttributeType(SelectedTag) - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Sets the attribute type to be deleted by the filter.
- setAttributeTypes(Hashtable) - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Sets the attribute - attribute-type relation to use.
- setAttrIndexRange(String) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets which attributes are used in the cluster attributes among the selection will be discretized.
- setAtts(int[], boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Changes the boolean value at the specified index in the InstIndexes array
- setAttsToEliminatePerIteration(int) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Set the constant rate of attribute elimination per iteration
- setAutoBuild(boolean) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
This will set whether the network is automatically built or if it is left up to the user.
- setAutoKeyGeneration(boolean) - 类中的方法 weka.core.converters.DatabaseSaver
-
En/Dis-ables the automatic generation of a primary key.
- setBackground(Color) - 类中的方法 weka.gui.visualize.BMPWriter
-
sets the background color to use in creating the JPEG
- setBackground(Color) - 类中的方法 weka.gui.visualize.JPEGWriter
-
sets the background color to use in creating the JPEG.
- setBackground(Color) - 类中的方法 weka.gui.visualize.PNGWriter
-
sets the background color to use in creating the JPEG
- setBackground(Color) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- setBagSizePercent(int) - 类中的方法 weka.classifiers.meta.Bagging
-
Sets the size of each bag, as a percentage of the training set size.
- setBagSizePercent(int) - 类中的方法 weka.classifiers.meta.MetaCost
-
Sets the size of each bag, as a percentage of the training set size.
- setBalanceClass(boolean) - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Sets whether the class is balanced.
- setBalanced(boolean) - 类中的方法 weka.classifiers.functions.Winnow
-
Set the value of Balanced.
- setBallSplitter(BallSplitter) - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Sets the ball splitting algorithm to be used by the TopDown constructor.
- setBallTreeConstructor(BallTreeConstructor) - 类中的方法 weka.core.neighboursearch.BallTree
-
Sets the BallTreeConstructor for building the BallTree (default TopDownConstructor).
- setBase(double) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Sets the base to use for expansion constant.
- setBaseExperiment(Experiment) - 类中的方法 weka.experiment.RemoteExperiment
-
Set the base experiment.
- setBeanContext(BeanContext) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Set a bean context for this bean
- setBeanContext(BeanContext) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- setBeanContext(BeanContext) - 类中的方法 weka.gui.beans.DataVisualizer
-
Set a bean context for this bean
- setBeanContext(BeanContext) - 类中的方法 weka.gui.beans.GraphViewer
-
Set a bean context for this bean
- setBeanContext(BeanContext) - 类中的方法 weka.gui.beans.Loader
-
Set a bean context for this bean
- setBeanContext(BeanContext) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Set a bean context for this bean
- setBeanContext(BeanContext) - 类中的方法 weka.gui.beans.TextViewer
-
Set a bean context for this bean
- setBeanInstances(Vector, JComponent) - 类中的静态方法 weka.gui.beans.BeanInstance
-
Describe
setBeanInstances
method here. - setBeta(double) - 类中的方法 weka.classifiers.functions.Winnow
-
Set the value of Beta.
- setBias(double) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Sets bias term value (default 1) No bias term is added if value < 0
- setBias(double) - 类中的方法 weka.classifiers.misc.VFI
-
Set the value of the exponential bias towards more confident intervals
- setBiasToUniformClass(double) - 类中的方法 weka.filters.supervised.instance.Resample
-
Sets the bias towards a uniform class.
- setBIFFile(String) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Set name of network in BIF file to compare with
- setBIFFile(String) - 类中的方法 weka.classifiers.bayes.net.search.fixed.FromFile
-
Set name of network in BIF file to read structure from
- setBinarizeNumericAttributes(boolean) - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Binarize numeric attributes.
- setBinarizeNumericAttributes(boolean) - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Binarize numeric attributes.
- setBinaryAttributesNominal(boolean) - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Sets if binary attributes are to be treates as nominal ones.
- setBinaryAttributesNominal(boolean) - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Sets if binary attributes are to be treates as nominal ones.
- setBinarySplits(boolean) - 类中的方法 weka.classifiers.rules.PART
-
Set the value of binarySplits.
- setBinarySplits(boolean) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of binarySplits.
- setBinarySplits(boolean) - 类中的方法 weka.classifiers.trees.J48graft
-
Set the value of binarySplits.
- setBins(int) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Sets the number of bins to divide each selected numeric attribute into
- setBins(int) - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Ignored
- setBinSplit(boolean) - 类中的方法 weka.classifiers.trees.FT
-
Set the value of binarySplits.
- setBinValue(double) - 类中的方法 weka.clusterers.XMeans
-
Sets the distance value between true and false of binary attributes.
- setBlendFactor(int) - 类中的方法 weka.classifiers.lazy.kstar.KStarNumericAttribute
-
Set the blending factor
- setBlendMethod(int) - 类中的方法 weka.classifiers.lazy.kstar.KStarNumericAttribute
-
Set the blending method
- setBooleanCols(Range) - 类中的方法 weka.datagenerators.ClusterGenerator
-
Sets which attributes are boolean.
- setBooleanIndices(String) - 类中的方法 weka.datagenerators.ClusterGenerator
-
Sets which attributes are boolean
- setBuildLogisticModels(boolean) - 类中的方法 weka.classifiers.functions.SMO
-
Set the value of buildLogisticModels.
- setBuildLogisticModels(boolean) - 类中的方法 weka.classifiers.mi.MISMO
-
Set the value of buildLogisticModels.
- setBuildRegressionTree(boolean) - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Set the value of regressionTree.
- setC(double) - 类中的方法 weka.classifiers.functions.SMO
-
Set the value of C.
- setC(double) - 类中的方法 weka.classifiers.functions.SMOreg
-
Set the value of C.
- setC(double) - 类中的方法 weka.classifiers.mi.MISMO
-
Set the value of C.
- setC(double) - 类中的方法 weka.classifiers.mi.MISVM
-
Set the value of C.
- setCacheKeyName(String) - 类中的方法 weka.experiment.DatabaseResultListener
-
Set the value of CacheKeyName.
- setCacheSize(double) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets cache memory size in MB (default 40)
- setCacheSize(int) - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Sets the size of the cache to use (a prime number)
- setCacheSize(int) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Sets the size of the cache to use (a prime number)
- setCalcOutOfBag(boolean) - 类中的方法 weka.classifiers.meta.Bagging
-
Set whether the out of bag error is calculated.
- setCalculateStdDevs(boolean) - 类中的方法 weka.experiment.AveragingResultProducer
-
Set the value of CalculateStdDevs.
- setCanChangeClassInDialog(boolean) - 类中的方法 weka.gui.GenericObjectEditor
-
Sets whether the user can change the class in the dialog.
- setCapabilities(Capabilities) - 类中的方法 weka.core.FindWithCapabilities
-
Uses the given Capabilities for the search.
- setCapabilities(Capabilities) - 类中的方法 weka.gui.GenericObjectEditor.CapabilitiesFilterDialog
-
sets the initial capabilities.
- setCapabilitiesFilter(Capabilities) - 类中的方法 weka.gui.ConverterFileChooser
-
sets the capabilities that the savers must have.
- setCapabilitiesFilter(Capabilities) - 类中的方法 weka.gui.GenericObjectEditor
-
Sets the capabilities to use for filtering.
- setCapacity(int) - 类中的方法 weka.core.FastVector
-
Sets the vector's capacity to the given value.
- setCapacity(int) - 类中的方法 weka.core.matrix.DoubleVector
-
Sets the capacity of the vector
- setCapacity(int) - 类中的方法 weka.core.matrix.IntVector
-
Sets the capacity of the vector
- setCar(boolean) - 类中的方法 weka.associations.Apriori
-
Sets class association rule mining
- setCar(boolean) - 类中的方法 weka.associations.PredictiveApriori
-
Sets class association rule mining
- setCardinality(int) - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Sets the cardinality of the attributes (incl class attribute)
- setCell(int, int, Object) - 类中的方法 weka.classifiers.CostMatrix
-
Set the value of a particular cell in the matrix
- setCenter(double) - 类中的方法 weka.gui.treevisualizer.Node
-
Set the value of center.
- setCenterData(boolean) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Set whether to center (rather than standardize) the data.
- setCenterData(boolean) - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Set whether to center (rather than standardize) the data.
- setCenteredLocation() - 类中的方法 weka.gui.arffviewer.ArffViewer
-
positions the window at the center of the screen
- setChanged(boolean) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
can only reset the changed state to FALSE
- setChar(Character) - 类中的方法 weka.core.Trie.TrieNode
-
sets the character this node represents
- setCharSet(String) - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Set the character set to use when reading text files (an empty string indicates that the default character set will be used).
- setChecked(int, boolean) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
sets the checked state of the element at the given index
- setChecked(int, boolean) - 类中的方法 weka.gui.CheckBoxList
-
sets the checked state of the element at the given index
- setCheckErrorRate(boolean) - 类中的方法 weka.classifiers.rules.JRip
-
Sets whether to check for error rate is in stopping criterion
- setChecksTurnedOff(boolean) - 类中的方法 weka.classifiers.functions.SMO
-
Disables or enables the checks (which could be time-consuming).
- setChecksTurnedOff(boolean) - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Disables or enables the checks (which could be time-consuming).
- setChecksTurnedOff(boolean) - 类中的方法 weka.classifiers.mi.MISMO
-
Disables or enables the checks (which could be time-consuming).
- setChecksTurnedOff(boolean) - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Disables or enables the checks (which could be time-consuming).
- setChildForBranch(int, PredictionNode) - 类中的方法 weka.classifiers.trees.adtree.Splitter
-
Sets the child for a branch of the split.
- setChildForBranch(int, PredictionNode) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Sets the child for a branch of the split.
- setChildForBranch(int, PredictionNode) - 类中的方法 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Sets the child for a branch of the split.
- setCindex(int) - 类中的方法 weka.gui.visualize.AttributePanel
-
Set the index of the attribute by which to colour the data.
- setCindex(int) - 类中的方法 weka.gui.visualize.ClassPanel
-
Set the index of the attribute to display coloured labels for
- setCindex(int) - 类中的方法 weka.gui.visualize.Plot2D
-
Set the index of the attribute to use for colouring
- setCindex(int) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the colouring index of the data
- setCindex(int, double, double) - 类中的方法 weka.gui.visualize.AttributePanel
-
Set the index of the attribute by which to colour the data.
- setClass(Attribute) - 类中的方法 weka.core.Instances
-
Sets the class attribute.
- setClassColumn(String) - 类中的方法 weka.gui.beans.ClassAssigner
- setClassFlag(boolean) - 类中的方法 weka.datagenerators.ClusterGenerator
-
Sets the class flag, if class flag is set, the cluster is listed as class atrribute in an extra attribute.
- setClassForIRStatistics(int) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Set the value of ClassForIRStatistics.
- setClassification(boolean) - 类中的方法 weka.associations.Tertius
-
Set the value of classification.
- setClassifier(Classifier) - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Set the classifier to use for accuracy estimation
- setClassifier(Classifier) - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Set the classifier to use for accuracy estimation
- setClassifier(Classifier) - 类中的方法 weka.classifiers.BVDecompose
-
Set the classifiers being analysed
- setClassifier(Classifier) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Set the classifiers being analysed
- setClassifier(Classifier) - 类中的方法 weka.classifiers.CheckClassifier
-
Set the classifier for boosting.
- setClassifier(Classifier) - 类中的方法 weka.classifiers.CheckSource
-
Sets the classifier to use for the comparison.
- setClassifier(Classifier) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the base learner.
- setClassifier(Classifier) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Set the base learner.
- setClassifier(Classifier) - 类中的方法 weka.classifiers.SingleClassifierEnhancer
-
Set the base learner.
- setClassifier(Classifier) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Sets the classifier.
- setClassifier(Classifier) - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Sets the classifier.
- setClassifier(Classifier) - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Sets the classifier to classify instances with.
- setClassifier(Classifier) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Sets the classifier to classify instances with.
- setClassifier(Classifier) - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Set the classifier
- setClassifier(Classifier) - 类中的方法 weka.gui.beans.IncrementalClassifierEvent
- setClassifier(Classifier) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set the classifier to use.
- setClassifier(Classifier) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Set a classifier to use
- setClassifier(Classifier) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the classifier to use
- setClassifierName(String) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Set the Classifier to use, given it's class name.
- setClassifierName(String) - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Set the Classifier to use, given it's class name.
- setClassifiers(Classifier[]) - 类中的方法 weka.classifiers.meta.MultiScheme
-
Sets the list of possible classifers to choose from.
- setClassifiers(Classifier[]) - 类中的方法 weka.classifiers.MultipleClassifiersCombiner
-
Sets the list of possible classifers to choose from.
- setClassifierTemplate(Classifier) - 类中的方法 weka.gui.beans.Classifier
-
Set the classifier for this wrapper
- setClassifyIterations(int) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Sets the number of times an instance is classified
- setClassIndex(int) - 类中的方法 weka.associations.Apriori
-
Sets the class index
- setClassIndex(int) - 接口中的方法 weka.associations.CARuleMiner
-
Sets the class index for the class association rule miner
- setClassIndex(int) - 类中的方法 weka.associations.FilteredAssociator
-
Sets the class index
- setClassIndex(int) - 类中的方法 weka.associations.PredictiveApriori
-
Sets the class index
- setClassIndex(int) - 类中的方法 weka.associations.Tertius
-
Set the value of classIndex.
- setClassIndex(int) - 类中的方法 weka.classifiers.BVDecompose
-
Sets index of attribute to discretize on
- setClassIndex(int) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Sets index of attribute to discretize on
- setClassIndex(int) - 类中的方法 weka.classifiers.CheckSource
-
Sets the class index of the dataset.
- setClassIndex(int) - 类中的方法 weka.core.Instances
-
Sets the class index of the set.
- setClassIndex(int) - 类中的方法 weka.core.TestInstances
-
sets the class index (0-based)
- setClassIndex(int) - 类中的方法 weka.filters.CheckSource
-
Sets the class index of the dataset.
- setClassIndex(int) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Sets the attribute on which misclassifications are based.
- setClassIndex(String) - 类中的方法 weka.core.converters.LibSVMSaver
-
Sets index of the class attribute.
- setClassIndex(String) - 类中的方法 weka.core.converters.SVMLightSaver
-
Sets index of the class attribute.
- setClassIndex(String) - 类中的方法 weka.core.converters.XRFFSaver
-
Sets index of the class attribute.
- setClassIndex(String) - 类中的方法 weka.core.FindWithCapabilities
-
sets the class index, -1 for none, first and last are also valid.
- setClassIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
sets the class index.
- setClassMissing() - 类中的方法 weka.core.Instance
-
Sets the class value of an instance to be "missing".
- setClassname(String) - 类中的方法 weka.core.AllJavadoc
-
sets the classname of the class to generate the Javadoc for
- setClassname(String) - 类中的方法 weka.core.Javadoc
-
sets the classname of the class to generate the Javadoc for
- setClassname(String) - 类中的方法 weka.core.ListOptions
-
sets the classname of the class to generate the Javadoc for
- setClassName(String) - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Sets the class containing the transformation method.
- setClassOrder(int) - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Set the wanted class order
- setClassType(int) - 类中的方法 weka.core.TestInstances
-
sets the class attribute type
- setClassType(Class) - 类中的方法 weka.gui.GenericObjectEditor
-
Sets the class of values that can be edited.
- setClassValue(double) - 类中的方法 weka.core.Instance
-
Sets the class value of an instance to the given value (internal floating-point format).
- setClassValue(String) - 类中的方法 weka.core.Instance
-
Sets the class value of an instance to the given value.
- setClassValue(String) - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Sets the index of the class value to which SMOTE should be applied.
- setClassValue(String) - 类中的方法 weka.gui.beans.ClassValuePicker
-
Set the class value index considered to be the "positive" class value.
- setClearEachDataset(boolean) - 类中的方法 weka.gui.streams.InstanceViewer
- setClip(int, int, int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- setClip(Shape) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- setCloseTo(double) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Set the "close to" number.
- setCloseToDefault(double) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Set the "close to" default.
- setCloseToTolerance(double) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Set the "close to" Tolerance.
- setClusterDefinitions(ClusterDefinition[]) - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
sets the clusters to use
- setClusterer(Clusterer) - 类中的方法 weka.attributeSelection.UnsupervisedSubsetEvaluator
-
Set the clusterer to use
- setClusterer(Clusterer) - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Set the base clusterer.
- setClusterer(Clusterer) - 类中的方法 weka.clusterers.CheckClusterer
-
Set the clusterer for testing.
- setClusterer(Clusterer) - 类中的方法 weka.clusterers.ClusterEvaluation
-
set the clusterer
- setClusterer(Clusterer) - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Sets the clusterer to wrap.
- setClusterer(Clusterer) - 类中的方法 weka.clusterers.SingleClustererEnhancer
-
Set the base clusterer.
- setClusterer(Clusterer) - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Sets the clusterer to assign clusters with.
- setClusterer(Clusterer) - 类中的方法 weka.gui.beans.Clusterer
-
Set the clusterer for this wrapper
- setClusterer(DensityBasedClusterer) - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Sets the clusterer.
- setClustererName(String) - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Set the Clusterer to use, given it's class name.
- setClusteringSeed(int) - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Set the random seed to be passed on to K-means.
- setClusterLabel(int) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Sets the clusterID (cluster), to which this DataObject belongs to
- setClusterLabel(int) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Sets the clusterID (cluster), to which this DataObject belongs to
- setClusterLabel(int) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Sets the clusterID (cluster), to which this DataObject belongs to
- setClusterSubType(SelectedTag) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets the cluster sub type.
- setClusterType(SelectedTag) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets the cluster type.
- setCoef0(double) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets coef (default 0)
- setColHidden(int, boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets the hidden status of the column (if the index is valid)
- setColName(int, String) - 类中的方法 weka.experiment.ResultMatrix
-
sets the name of the column (if the index is valid)
- setColNameWidth(int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the width for the column names (0 = optimal)
- setColor(Color) - 类中的方法 weka.gui.treevisualizer.Node
-
Set the value of color.
- setColor(Color) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Set current pen color.
- setColOrder(int[]) - 类中的方法 weka.experiment.ResultMatrix
-
sets the ordering of the columns, null means default
- setColoringIndex(int) - 类中的方法 weka.gui.AttributeVisualizationPanel
-
Set the coloring (class) index for the plot
- setColoringIndex(int) - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Set the coloring index for the attribute summary plots
- setColors(FastVector) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set a vector of Color objects for the classes
- setColourIndex(int) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Sets the index used for colouring.
- setColours(FastVector) - 类中的方法 weka.gui.visualize.AttributePanel
-
Sets a list of colours to use for colouring data points
- setColours(FastVector) - 类中的方法 weka.gui.visualize.ClassPanel
-
Set a list of colours to use for colouring labels
- setColours(FastVector) - 类中的方法 weka.gui.visualize.Plot2D
-
Set a list of colours to use when colouring points according to class values or cluster numbers
- setColumn(int, double[]) - 类中的方法 weka.core.Matrix
-
已过时。Sets a column of the matrix to the given column.
- setColumnDimension(int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Set the column dimenion of the matrix
- setCombination(SelectedTag) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Set the kind of combination
- setCombinationRule(SelectedTag) - 类中的方法 weka.classifiers.meta.Vote
-
Sets the combination rule to use.
- setComplexityParameter(double) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Set the value of C for SMO
- setComponent(JComponent) - 类中的方法 weka.gui.visualize.JComponentWriter
-
sets the component to print to an output format
- setComposite(Composite) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- setCompressOutput(boolean) - 类中的方法 weka.core.converters.ArffSaver
-
Sets whether to compress the output.
- setCompressOutput(boolean) - 类中的方法 weka.core.converters.XRFFSaver
-
Sets whether to compress the output.
- setConfidenceFactor(float) - 类中的方法 weka.classifiers.rules.PART
-
Set the value of CF.
- setConfidenceFactor(float) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of CF.
- setConfidenceFactor(float) - 类中的方法 weka.classifiers.trees.J48graft
-
Set the value of CF.
- setConfirmationThreshold(double) - 类中的方法 weka.associations.Tertius
-
Set the value of confirmationThreshold.
- setConfirmationValues(int) - 类中的方法 weka.associations.Tertius
-
Set the value of confirmationValues.
- setConfirmExit(boolean) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
whether to present a MessageBox on Exit or not
- setConfirmExit(boolean) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
whether to present a MessageBox on Exit or not
- setConnections(Vector) - 类中的静态方法 weka.gui.beans.BeanConnection
-
Describe
setConnections
method here. - setConnectPoints(boolean[]) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set whether consecutive points should be connected by lines
- setConnectPoints(FastVector) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set whether consecutive points should be connected by lines
- setConsequent(double) - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Sets the internal representation of the class label to be predicted
- setConservativeForwardSelection(boolean) - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Set whether attributes should continue to be added during a forward search as long as merit does not decrease
- setContainChildBalls(boolean) - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Sets whether if a parent ball should completely enclose its two child balls.
- setConvertNominal(boolean) - 类中的方法 weka.classifiers.trees.LMT
-
Set the value of convertNominal.
- setConvertNominalToBinary(boolean) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Whether to turn on conversion of nominal attributes to binary.
- setCoreConvertersOnly(boolean) - 类中的方法 weka.gui.ConverterFileChooser
-
Whether to display only the hardocded core converters.
- setCoreDistance(double) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Sets a new coreDistance for this dataObject
- setCoreDistance(double) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Sets a new coreDistance for this dataObject
- setCoreDistance(double) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Sets a new coreDistance for this dataObject
- setCoreDistanceColor(Color) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Sets a new color for the coreDistance
- setCost(double) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Sets the cost parameter C (default 1)
- setCost(double) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1)
- setCostMatrix(CostMatrix) - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Sets the misclassification cost matrix.
- setCostMatrix(CostMatrix) - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Sets the misclassification cost matrix.
- setCostMatrix(CostMatrix) - 类中的方法 weka.classifiers.meta.MetaCost
-
Sets the misclassification cost matrix.
- setCostMatrixSource(SelectedTag) - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Sets the source location of the cost matrix.
- setCostMatrixSource(SelectedTag) - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Sets the source location of the cost matrix.
- setCostMatrixSource(SelectedTag) - 类中的方法 weka.classifiers.meta.MetaCost
-
Sets the source location of the cost matrix.
- setCount(int, double) - 类中的方法 weka.experiment.ResultMatrix
-
sets the count for the row (if the index is valid)
- setCounter(int) - 类中的方法 weka.associations.ItemSet
-
Sets the counter
- setCountWidth(int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the width for the counts (0 = optimal)
- setCreatorApplication(Document) - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Set the name of the application (if specified) that created this model
- setCreatorApplication(Document) - 接口中的方法 weka.core.pmml.PMMLModel
-
Set the name of the application (if specified) that created this.
- setCriticalValue(int) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Sets the critical value
- setCrossoverProb(double) - 类中的方法 weka.attributeSelection.GeneticSearch
-
set the probability of crossover
- setCrossVal(int) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Sets the number of folds for cross validation (1 = leave one out)
- setCrossValidate(boolean) - 类中的方法 weka.classifiers.lazy.IBk
-
Sets whether hold-one-out cross-validation will be used to select the best k value.
- setCurrentFilename(String) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
sets the filename of the current tab
- setCurrentInstance(Instance) - 类中的方法 weka.gui.beans.IncrementalClassifierEvent
-
Set the current instance for this event
- setCurveData(PlotData2D, Attribute) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Set the threshold curve data to use.
- setCustomColour(Color) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set a custom colour to use for this plot.
- setCustomHeight(int) - 类中的方法 weka.gui.visualize.JComponentWriter
-
sets the custom height to use
- setCustomName(String) - 类中的方法 weka.gui.beans.Associator
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 接口中的方法 weka.gui.beans.BeanCommon
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.ClassAssigner
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.Classifier
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.ClassValuePicker
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.Clusterer
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.Filter
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.Loader
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.MetaBean
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.PredictionAppender
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.Saver
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.StripChart
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.TestSetMaker
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.TextViewer
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.TrainingSetMaker
-
Set a custom (descriptive) name for this bean
- setCustomName(String) - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Set a custom (descriptive) name for this bean
- setCustomWidth(int) - 类中的方法 weka.gui.visualize.JComponentWriter
-
sets the custom width to use
- setCutoff(double) - 类中的方法 weka.clusterers.Cobweb
-
set the cutoff
- setCutOffFactor(double) - 类中的方法 weka.clusterers.XMeans
-
Sets a new cutoff factor.
- setCVisible(boolean) - 类中的方法 weka.gui.treevisualizer.Node
-
Sets all the children of this node either to visible or invisible
- setCVParameters(Object[]) - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Set method for CVParameters.
- setCVType(SelectedTag) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
set cross validation strategy to be used in searching for networks.
- setData(Instances) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Assuming a network structure is defined and we want to learn from data, the data set must be put if correct order first and possibly discretized/missing values filled in before proceeding to CPT learning.
- setData(Instances) - 类中的方法 weka.classifiers.rules.RuleStats
-
Set the data of the stats, overwriting the old one if any
- setDatabase_distanceType(String) - 类中的方法 weka.clusterers.DBSCAN
-
Sets a new distance-type
- setDatabase_distanceType(String) - 类中的方法 weka.clusterers.OPTICS
-
Sets a new distance-type
- setDatabase_Type(String) - 类中的方法 weka.clusterers.DBSCAN
-
Sets a new database-type
- setDatabase_Type(String) - 类中的方法 weka.clusterers.OPTICS
-
Sets a new database-type
- setDatabaseOutput(File) - 类中的方法 weka.clusterers.OPTICS
-
Sets the the file to save the generated database to.
- setDatabaseURL(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Set the value of DatabaseURL.
- setDataFileName(String) - 类中的方法 weka.classifiers.BVDecompose
-
Sets the name of the data file used for the decomposition
- setDataFileName(String) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Sets the name of the dataset file.
- setDataGenerator(DataGenerator) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set the data generator to use for generating new instances
- setDataGenerator(DataGenerator) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the density estimator to use
- setDataPoint(double[]) - 类中的方法 weka.gui.beans.ChartEvent
-
Set the data point
- setDataSeqID(int) - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Sets the attribute representing the data sequence ID.
- setDataset(File) - 类中的方法 weka.classifiers.CheckSource
-
Sets the dataset to use for testing.
- setDataset(File) - 类中的方法 weka.filters.CheckSource
-
Sets the dataset to use for testing.
- setDataset(Instances) - 类中的方法 weka.core.Instance
-
Sets the reference to the dataset.
- setDatasetFormat(Instances) - 类中的方法 weka.datagenerators.DataGenerator
-
Sets the format of the dataset that is to be generated.
- setDatasetKeyColumns(Range) - 类中的方法 weka.experiment.PairedTTester
-
Set the value of DatasetKeyColumns.
- setDatasetKeyColumns(Range) - 接口中的方法 weka.experiment.Tester
-
Set the value of DatasetKeyColumns.
- setDatasetKeyFromDialog() - 类中的方法 weka.gui.experiment.ResultsPanel
- setDatasets(DefaultListModel) - 类中的方法 weka.experiment.Experiment
-
Set the datasets to use in the experiment
- setDatasets(DefaultListModel) - 类中的方法 weka.experiment.RemoteExperiment
-
Set the datasets to use in the experiment
- setDataType(int) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
sets what kind of data is to be read/written
- setDateAttributes(String) - 类中的方法 weka.core.converters.CSVLoader
-
Set the attribute range to be forced to type date.
- setDateFormat(String) - 类中的方法 weka.core.converters.CSVLoader
-
Set the format to use for parsing date values.
- setDateFormat(String) - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Set the date format, complying to ISO-8601.
- setDateFormat(String) - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Sets the output date format.
- setDateFormat(SimpleDateFormat) - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Sets the output date format.
- setDB(boolean) - 类中的方法 weka.gui.beans.Loader
- setDebug(boolean) - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Set debugging mode.
- setDebug(boolean) - 类中的方法 weka.attributeSelection.RaceSearch
-
Set whether verbose output should be generated.
- setDebug(boolean) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Set whether verbose output should be generated.
- setDebug(boolean) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
- setDebug(boolean) - 类中的方法 weka.classifiers.BVDecompose
-
Sets debugging mode
- setDebug(boolean) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Sets debugging mode
- setDebug(boolean) - 类中的方法 weka.classifiers.Classifier
-
Set debugging mode.
- setDebug(boolean) - 类中的方法 weka.classifiers.functions.LeastMedSq
-
sets whether or not debugging output shouild be printed
- setDebug(boolean) - 类中的方法 weka.classifiers.functions.LinearRegression
-
Controls whether debugging output will be printed
- setDebug(boolean) - 类中的方法 weka.classifiers.functions.Logistic
-
Sets whether debugging output will be printed.
- setDebug(boolean) - 类中的方法 weka.classifiers.functions.PaceRegression
-
Controls whether debugging output will be printed
- setDebug(boolean) - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Enables or disables the output of debug information (if the derived kernel supports that)
- setDebug(boolean) - 类中的方法 weka.classifiers.meta.MultiScheme
-
Set debugging mode
- setDebug(boolean) - 类中的方法 weka.classifiers.rules.JRip
-
Sets whether debug information is output to the console
- setDebug(boolean) - 类中的方法 weka.clusterers.EM
-
Set debug mode - verbose output
- setDebug(boolean) - 类中的方法 weka.clusterers.HierarchicalClusterer
-
Set debugging mode.
- setDebug(boolean) - 类中的方法 weka.clusterers.sIB
-
Set debug mode - verbose output
- setDebug(boolean) - 类中的方法 weka.core.Check
-
Set debugging mode
- setDebug(boolean) - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Sets whether to print some debug information.
- setDebug(boolean) - 类中的方法 weka.core.Debug.Random
-
sets whether to print the generated random values or not
- setDebug(boolean) - 类中的方法 weka.core.Optimization
-
Set whether in debug mode
- setDebug(boolean) - 类中的方法 weka.datagenerators.DataGenerator
-
Sets the debug flag.
- setDebug(boolean) - 类中的方法 weka.estimators.CheckEstimator
-
Set debugging mode
- setDebug(boolean) - 类中的方法 weka.estimators.Estimator
-
Set debugging mode.
- setDebug(boolean) - 类中的方法 weka.experiment.DatabaseUtils
-
Sets whether there should be printed some debugging output to stderr or not.
- setDebug(boolean) - 类中的方法 weka.filters.SimpleFilter
-
Sets the debugging mode
- setDebug(boolean) - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Set debug mode.
- setDebug(boolean) - 类中的方法 weka.gui.SimpleCLIPanel.CommandlineCompletion
-
sets debug mode on/off.
- setDebug(boolean) - 类中的方法 weka.gui.streams.InstanceCounter
- setDebug(boolean) - 类中的方法 weka.gui.streams.InstanceJoiner
- setDebug(boolean) - 类中的方法 weka.gui.streams.InstanceLoader
- setDebug(boolean) - 类中的方法 weka.gui.streams.InstanceSavePanel
- setDebug(boolean) - 类中的方法 weka.gui.streams.InstanceTable
- setDebug(boolean) - 类中的方法 weka.gui.streams.InstanceViewer
- setDebugLevel(int) - 类中的方法 weka.clusterers.XMeans
-
Sets the debug level.
- setDebugVectorsFile(File) - 类中的方法 weka.clusterers.XMeans
-
Sets the file that has the random vectors stored.
- setDecay(boolean) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- setDecimals(int) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Set the number of decimals to round to.
- setDefaultValue() - 类中的方法 weka.gui.GenericObjectEditor
-
Sets the current object to be the default, taken as the first item in the chooser.
- setDefaultWeight(double) - 类中的方法 weka.classifiers.functions.Winnow
-
Set the value of defaultWeight.
- setDegree(int) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets the degree of the kernel
- setDegreesOfFreedom(int) - 类中的方法 weka.experiment.PairedStats
-
Sets the degrees of freedom (if calibration is required).
- setDeleteEmptyBins(boolean) - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Sets the number of bins to divide each selected numeric attribute into
- setDelimiters(String) - 类中的方法 weka.core.tokenizers.CharacterDelimitedTokenizer
-
Set the value of delimiters.
- setDelta(double) - 类中的方法 weka.associations.Apriori
-
Set the value of delta.
- setDelta(double) - 类中的方法 weka.associations.FPGrowth
-
Set the value of delta.
- setDelta(double) - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Sets the m_fDelta.
- setDelta(double) - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Sets the m_fDelta.
- setDensityBasedClusterer(DensityBasedClusterer) - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Set the clusterer for use in filtering
- setDescendantPopulationSize(int) - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- setDescendantPopulationSize(int) - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- setDescendents(ArrayList, C45PruneableClassifierTreeG) - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
add the grafted nodes at originalLeaf's position in tree.
- setDesign(boolean) - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Set whether the appearance of this bean should be design or application
- setDesignatedClass(SelectedTag) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Sets the method to determine which class value to optimize.
- setDesiredSize(int) - 类中的方法 weka.classifiers.meta.Decorate
-
Sets the desired size of the committee.
- setDesiredWeightOfInstancesPerInterval(double) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Set the DesiredWeightOfInstancesPerInterval value.
- setDestination() - 类中的方法 weka.core.converters.DatabaseSaver
-
Sets the database url using the DatabaseUtils file.
- setDestination(File) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Sets the destination file (and directories if necessary).
- setDestination(File) - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- setDestination(File) - 接口中的方法 weka.core.converters.Saver
-
Resets the Saver object and sets the destination to be the supplied File object.
- setDestination(OutputStream) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Sets the destination output stream.
- setDestination(OutputStream) - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- setDestination(OutputStream) - 类中的方法 weka.core.converters.ArffSaver
-
Sets the destination output stream.
- setDestination(OutputStream) - 接口中的方法 weka.core.converters.Saver
-
Resets the Saver object and sets the destination to be the supplied InputStream.
- setDestination(OutputStream) - 类中的方法 weka.core.converters.SerializedInstancesSaver
-
Sets the destination output stream.
- setDestination(OutputStream) - 类中的方法 weka.core.converters.XRFFSaver
-
Sets the destination output stream.
- setDestination(String) - 类中的方法 weka.core.converters.DatabaseSaver
-
Sets the database url.
- setDestination(String, String, String) - 类中的方法 weka.core.converters.DatabaseSaver
-
Sets the database url.
- setDetectionPerAttribute(boolean) - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Set whether an Outlier/ExtremeValue attribute pair is generated for each numeric attribute ("true") or just one pair for all numeric attributes together ("false").
- setDir(String) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Sets the directory where the instances should be stored
- setDir(String) - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- setDir(String) - 接口中的方法 weka.core.converters.Saver
-
Sets the directory of the output file.
- setDir(String) - 类中的方法 weka.core.Javadoc
-
sets the dir containing the file that is to be updated.
- setDirAndPrefix(String, String) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Sets the directory and the file prefix.
- setDirAndPrefix(String, String) - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- setDirAndPrefix(String, String) - 接口中的方法 weka.core.converters.Saver
-
Sets the file prefix and the directory.
- setDirection(SelectedTag) - 类中的方法 weka.attributeSelection.BestFirst
-
Set the search direction
- setDirectory(File) - 类中的方法 weka.core.converters.TextDirectoryLoader
-
sets the source directory
- setDirectory(File) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Set the directory that the model(s) will be saved into.
- setDiscretizeBin(int) - 类中的方法 weka.classifiers.mi.MIBoost
-
Set the number of bins in discretization
- setDisplayConnectors(boolean) - 类中的方法 weka.gui.beans.BeanVisual
-
Turn on/off the connector points
- setDisplayConnectors(boolean, Color) - 类中的方法 weka.gui.beans.BeanVisual
-
Turn on/off the connector points
- setDisplayedFromDialog() - 类中的方法 weka.gui.experiment.ResultsPanel
- setDisplayedResultsets(int[]) - 类中的方法 weka.experiment.PairedTTester
-
Sets the indicies of the datasets to display (
null
means all). - setDisplayedResultsets(int[]) - 接口中的方法 weka.experiment.Tester
-
Sets the indicies of the datasets to display (
null
means all). - setDisplayModelInOldFormat(boolean) - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Set whether to display model output in the old, original format.
- setDisplayModelInOldFormat(boolean) - 类中的方法 weka.clusterers.EM
-
Set whether to display model output in the old, original format.
- setDisplayRules(boolean) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Sets whether rules are to be printed
- setDisplayStdDevs(boolean) - 类中的方法 weka.clusterers.SimpleKMeans
-
Sets whether standard deviations and nominal count Should be displayed in the clustering output
- setDistanceF(DistanceFunction) - 类中的方法 weka.clusterers.XMeans
-
gets the "binary" distance value.
- setDistanceFunction(DistanceFunction) - 类中的方法 weka.clusterers.HierarchicalClusterer
- setDistanceFunction(DistanceFunction) - 类中的方法 weka.clusterers.SimpleKMeans
-
sets the distance function to use for instance comparison.
- setDistanceFunction(DistanceFunction) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Sets the distance function to use for nearest neighbour search.
- setDistanceFunction(DistanceFunction) - 类中的方法 weka.core.neighboursearch.KDTree
-
sets the distance function to use for nearest neighbour search.
- setDistanceFunction(DistanceFunction) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
sets the distance function to use for nearest neighbour search.
- setDistanceIsBranchLength(boolean) - 类中的方法 weka.clusterers.HierarchicalClusterer
- setDistanceWeighting(SelectedTag) - 类中的方法 weka.classifiers.lazy.IBk
-
Sets the distance weighting method used.
- setDistMult(double) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the distance multiplier.
- setDistribution(int, double[][]) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
specify distribution of a node
- setDistribution(String, double[][]) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
specify distribution of a node
- setDistribution(SelectedTag) - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Sets the distribution to use for calculating the random matrix
- setDistributionSpread(double) - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Sets the value for the distribution spread
- setDocType(String) - 类中的方法 weka.core.xml.XMLDocument
-
sets the DOCTYPE-String to use in the XML output.
- setDocument(Document) - 类中的方法 weka.core.xml.XMLDocument
-
sets the DOM document to use.
- setDoNotOperateOnPerClassBasis(boolean) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Set the DoNotOperateOnPerClassBasis value.
- setDoNotReplaceMissingValues(boolean) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Whether to turn off automatic replacement of missing values.
- setDoNotReplaceMissingValues(boolean) - 类中的方法 weka.classifiers.functions.LibSVM
-
Whether to turn off automatic replacement of missing values.
- setDoNotWeightBags(boolean) - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Sets whether bags are weighted
- setDontFilterAfterFirstBatch(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Set whether to apply the filter to instances that arrive once the first (training) batch has been seen.
- setDontNormalize(boolean) - 类中的方法 weka.classifiers.functions.SPegasos
-
Turn normalization off/on.
- setDontNormalize(boolean) - 类中的方法 weka.core.NormalizableDistance
-
Sets whether if the attribute values are to be normalized in distance calculation.
- setDontReplaceMissing(boolean) - 类中的方法 weka.classifiers.functions.SPegasos
-
Turn global replacement of missing values off/on.
- setDontReplaceMissingValues(boolean) - 类中的方法 weka.clusterers.SimpleKMeans
-
Sets whether missing values are to be replaced
- setElement(int, double) - 类中的方法 weka.core.AlgVector
-
Sets an element of the matrix to the given value.
- setElement(int, int, double) - 类中的方法 weka.classifiers.CostMatrix
-
Set the value of a cell as a double
- setElement(int, int, double) - 类中的方法 weka.core.Matrix
-
已过时。Sets an element of the matrix to the given value.
- setElementAt(Object, int) - 类中的方法 weka.core.FastVector
-
Sets the element at the given index.
- setElementAt(Object, int) - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Sets the component at the specified index of this list to be the specified object.
- setElements(double[]) - 类中的方法 weka.core.AlgVector
-
Sets the elements of the vector to values of the given array.
- setEliminateColinearAttributes(boolean) - 类中的方法 weka.classifiers.functions.LinearRegression
-
Set the value of EliminateColinearAttributes.
- setEnabled(boolean) - 类中的方法 weka.core.Debug
-
sets whether the logging is enabled or not
- setEnabled(boolean) - 类中的方法 weka.core.Memory
-
sets whether the memory management is enabled
- setEnabled(boolean) - 类中的方法 weka.gui.GenericObjectEditor
-
Sets whether the editor is "enabled", meaning that the current values will be painted.
- setEnabled(boolean) - 类中的方法 weka.gui.PropertyPanel
-
Passes on enabled/disabled status to the custom panel (if one is set).
- setEnclosureCharacters(String) - 类中的方法 weka.core.converters.CSVLoader
-
Set the character(s) to use/recognize as string enclosures
- setEntropicAutoBlend(boolean) - 类中的方法 weka.classifiers.lazy.KStar
-
Set whether entropic blending is to be used.
- setEnumerateColNames(boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets whether the column names are prefixed with "(x)" where "x" is the index
- setEnumerateRowNames(boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets whether to the row names or numbers instead are enumerateed
- setEnvironment(Environment) - 类中的方法 weka.core.converters.AbstractFileLoader
-
Set the environment variables to use.
- setEnvironment(Environment) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Set the environment variables to use.
- setEnvironment(Environment) - 接口中的方法 weka.core.EnvironmentHandler
-
Set environment variables to use.
- setEnvironment(Environment) - 类中的方法 weka.gui.beans.FlowRunner
-
Set the environment variables to use.
- setEnvironment(Environment) - 类中的方法 weka.gui.beans.KnowledgeFlowApp
-
Set the environment variables to use.
- setEnvironment(Environment) - 类中的方法 weka.gui.beans.Loader
-
Set environment variables to use.
- setEnvironment(Environment) - 类中的方法 weka.gui.beans.Saver
-
Set environment variables to use.
- setEnvironment(Environment) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Set environment variables to use.
- setEpochs(int) - 类中的方法 weka.classifiers.functions.SPegasos
-
Set the number of epochs to use
- setEps(double) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Sets tolerance of termination criterion (default 0.001)
- setEps(double) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets tolerance of termination criterion (default 0.001)
- setEpsilon(double) - 类中的方法 weka.classifiers.functions.SMO
-
Set the value of epsilon.
- setEpsilon(double) - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Set the value of epsilon.
- setEpsilon(double) - 类中的方法 weka.classifiers.mi.MISMO
-
Set the value of epsilon.
- setEpsilon(double) - 类中的方法 weka.clusterers.DBSCAN
-
Sets a new value for epsilon
- setEpsilon(double) - 类中的方法 weka.clusterers.OPTICS
-
Sets a new value for epsilon
- setEpsilonParameter(double) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Set the value of P for SMO
- setEpsilonParameter(double) - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Set the value of epsilon parameter of the epsilon insensitive loss function.
- setErrorOnProbabilities(boolean) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Set the value of errorOnProbabilities.
- setErrorOnProbabilities(boolean) - 类中的方法 weka.classifiers.trees.FT
-
Set the value of errorOnProbabilities.
- setErrorOnProbabilities(boolean) - 类中的方法 weka.classifiers.trees.LMT
-
Set the value of errorOnProbabilities.
- setEstimator(BayesNetEstimator) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Set the Estimator Algorithm used in calculating the CPTs
- setEstimator(SelectedTag) - 类中的方法 weka.classifiers.functions.PaceRegression
-
Sets the estimator.
- setEstimator(Estimator) - 类中的方法 weka.estimators.CheckEstimator
-
Set the estimator for boosting.
- setEuclideanDistanceFunction(EuclideanDistance) - 类中的方法 weka.core.neighboursearch.balltrees.BallSplitter
-
Sets the distance function used to (or to be used to) build the tree.
- setEuclideanDistanceFunction(EuclideanDistance) - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Sets the distance function to use to build the tree.
- setEuclideanDistanceFunction(EuclideanDistance) - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Sets the EuclideanDistance object to use for splitting nodes.
- setEvaluation(SelectedTag) - 类中的方法 weka.classifiers.meta.GridSearch
-
Sets the criterion to use for evaluating the classifier performance.
- setEvaluationMeasure(SelectedTag) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Sets the performance evaluation measure to use for selecting attributes for the decision table
- setEvaluationMode(SelectedTag) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Sets the evaluation mode used.
- setEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.AttributeSelection
-
set the attribute/subset evaluator
- setEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Set the evaluator to test.
- setEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Set the base evaluator.
- setEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.CostSensitiveAttributeEval
-
Set the base evaluator.
- setEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.CostSensitiveSubsetEval
-
Set the base evaluator.
- setEvaluator(ASEvaluation) - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Sets the attribute evaluator
- setEvaluator(ASEvaluation) - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
set attribute/subset evaluator
- setEvalUsingTrainingData(boolean) - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Use the training data to evaluate attributes rather than cross validation
- setEvidence(int, int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
set evidence state of a node.
- setEvidence(int, int) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
- setEvidence(int, int) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
- setExclusive(boolean) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Sets whether exclusive expressions for nominal attributes splits are considered
- setExecutionSlots(int) - 类中的方法 weka.gui.beans.Classifier
-
Set the number of execution slots (threads) to use to train models with.
- setExecutionStatus(int) - 类中的方法 weka.experiment.TaskStatusInfo
-
Set the execution status of this Task.
- setExitIfNoWindowsOpen(boolean) - 类中的静态方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Sets whether System.exit gets called when no more windows are open.
- setExitOnClose(boolean) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
whether to do a System.exit(0) on close
- setExitOnClose(boolean) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
whether to do a System.exit(0) on close
- setExpectedResultsPerAverage(int) - 类中的方法 weka.experiment.AveragingResultProducer
-
Set the value of ExpectedResultsPerAverage.
- setExperiment(Experiment) - 类中的方法 weka.experiment.RemoteExperimentSubTask
-
Set the experiment for this sub task
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.AlgorithmListPanel
-
Tells the panel to act on a new experiment.
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.DatasetListPanel
-
Tells the panel to act on a new experiment.
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.DistributeExperimentPanel
-
Sets the experiment to be configured.
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.GeneratorPropertyIteratorPanel
-
Sets the experiment which will have the custom properties edited.
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.ResultsPanel
-
Tells the panel to use a new experiment.
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.RunNumberPanel
-
Sets the experiment to be configured.
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.RunPanel
-
Sets the experiment the panel operates on.
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.SetupPanel
-
Sets the experiment to configure.
- setExperiment(Experiment) - 类中的方法 weka.gui.experiment.SimpleSetupPanel
-
Sets the experiment to configure.
- setExperiment(RemoteExperiment) - 类中的方法 weka.gui.experiment.HostListPanel
-
Tells the panel to act on a new experiment.
- setExplicitPropsFile(boolean) - 类中的方法 weka.gui.GenericPropertiesCreator
-
if FALSE, the locating of a props-file of the Utils-class is used, otherwise it's tried to load the specified file
- setExplorer(Explorer) - 类中的方法 weka.gui.explorer.AssociationsPanel
-
Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
- setExplorer(Explorer) - 类中的方法 weka.gui.explorer.AttributeSelectionPanel
-
Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
- setExplorer(Explorer) - 类中的方法 weka.gui.explorer.ClassifierPanel
-
Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
- setExplorer(Explorer) - 类中的方法 weka.gui.explorer.ClustererPanel
-
Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
- setExplorer(Explorer) - 接口中的方法 weka.gui.explorer.Explorer.ExplorerPanel
-
Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
- setExplorer(Explorer) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
- setExplorer(Explorer) - 类中的方法 weka.gui.explorer.VisualizePanel
-
Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
- setExponent(double) - 类中的方法 weka.classifiers.functions.supportVector.NormalizedPolyKernel
-
Sets the exponent value (must be different from 1.0).
- setExponent(double) - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Sets the exponent value.
- setExponent(double) - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Set the value of exponent.
- setExpression(String) - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Sets the mathematical expression to generate y out of x.
- setExpression(String) - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Set the expression to apply
- setExpression(String) - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Set the expression to apply
- setExpression(String) - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Sets the expression used for filtering.
- setExtremeValuesAsOutliers(boolean) - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Set whether extreme values are also tagged as outliers.
- setExtremeValuesFactor(double) - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Sets the factor for determining the thresholds for extreme values.
- setFalseNegative(double) - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Sets the number of positive instances predicted as negative
- setFalsePositive(double) - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Sets the number of negative instances predicted as positive
- setFastRegression(boolean) - 类中的方法 weka.classifiers.trees.LMT
-
Set the value of fastRegression.
- setFieldDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.DerivedFieldMetaInfo
-
Upadate the field definitions for this derived field
- setFieldDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.Discretize
-
Set the field definitions for this Expression to use
- setFieldDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.Expression
-
Set the field definitions for this Expression to use
- setFieldDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.FieldRef
- setFieldDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.NormContinuous
-
Set the field definitions for this Expression to use
- setFieldDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.NormDiscrete
-
Set the field definitions for this Expression to use
- setFile(File) - 类中的方法 weka.core.converters.AbstractFileLoader
-
sets the source File
- setFile(File) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Sets the destination file.
- setFile(File) - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- setFile(File) - 类中的方法 weka.core.converters.ArffLoader
-
sets the source File
- setFile(File) - 类中的方法 weka.core.converters.ArffSaver
-
Sets the destination file.
- setFile(File) - 接口中的方法 weka.core.converters.FileSourcedConverter
-
Set the file to load from/ to save in
- setFile(File) - 接口中的方法 weka.core.converters.Saver
-
Sets the output file
- setFile(File) - 类中的方法 weka.core.converters.XRFFSaver
-
Sets the destination file.
- setFile(File) - 类中的方法 weka.gui.visualize.JComponentWriter
-
sets the file to store the output in
- setFileFormat(Tag) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Set the file format to use for saving.
- setFileMustExist(boolean) - 类中的方法 weka.gui.ConverterFileChooser
-
Whether the selected file must exst (only open dialog).
- setFilename(int, String) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
sets the filename of the specified panel
- setFilename(String) - 类中的方法 weka.core.FindWithCapabilities
-
Sets the dataset filename to base the capabilities on.
- setFilename(String) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
sets the filename
- setFilePrefix(String) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Sets the file name prefix
- setFilePrefix(String) - 类中的方法 weka.core.converters.AbstractSaver
-
Default implementation throws an IOException.
- setFilePrefix(String) - 接口中的方法 weka.core.converters.Saver
-
Sets the file prefix.
- setFillWithMissing(boolean) - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Sets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).
- setFilter(Filter) - 类中的方法 weka.associations.FilteredAssociator
-
Sets the filter
- setFilter(Filter) - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Set the filter to use
- setFilter(Filter) - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Set the filter to use
- setFilter(Filter) - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Set the PLS filter (only used for setup).
- setFilter(Filter) - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Sets the filter
- setFilter(Filter) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the kernel filter (only used for setup).
- setFilter(Filter) - 类中的方法 weka.clusterers.FilteredClusterer
-
Sets the filter.
- setFilter(Filter) - 类中的方法 weka.filters.CheckSource
-
Sets the filter to use for the comparison.
- setFilter(Filter) - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Set the preprocessing filter (only used for setup).
- setFilter(Filter) - 类中的方法 weka.gui.beans.Filter
-
Set the filter to be wrapped by this bean
- setFilterAfterFirstBatch(boolean) - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Set whether to apply the filter to instances that arrive once the first (training) batch has been seen.
- setFilterAttributes(String) - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Sets the String containing the attributes which are used for output filtering.
- setFilters(Filter[]) - 类中的方法 weka.filters.MultiFilter
-
Sets the list of possible filters to choose from.
- setFilters(Filter[]) - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Sets the list of possible filters to choose from.
- setFilterType(SelectedTag) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
The filtering mode to pass to SMO
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Sets how the training data will be transformed.
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.functions.SMO
-
Sets how the training data will be transformed.
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.functions.SMOreg
-
Sets how the training data will be transformed.
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.mi.MDD
-
Sets how the training data will be transformed.
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.mi.MIDD
-
Sets how the training data will be transformed.
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.mi.MIEMDD
-
Sets how the training data will be transformed.
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Sets how the training data will be transformed.
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.mi.MISMO
-
Sets how the training data will be transformed.
- setFilterType(SelectedTag) - 类中的方法 weka.classifiers.mi.MISVM
-
Sets how the training data will be transformed.
- setFindAllRulesForSupportLevel(boolean) - 类中的方法 weka.associations.FPGrowth
-
If true then turn off the iterative support reduction method of finding x rules that meet the minimum support and metric thresholds and just return all the rules that meet the lower bound on minimum support and the minimum metric.
- setFindNumBins(boolean) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Set the value of FindNumBins.
- setFindNumBins(boolean) - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Set the value of FindNumBins.
- setFirstValueIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Sets index of the first value used.
- setFirstValueIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Sets index of the first value used.
- setFlow(Vector) - 类中的方法 weka.gui.beans.KnowledgeFlowApp
-
Set the flow for the KnowledgeFlow to edit.
- setFlows(Vector) - 类中的方法 weka.gui.beans.FlowRunner
-
Set the vector holding the flows(s) to run
- setFocus() - 类中的方法 weka.gui.sql.ConnectionPanel
-
sets the focus in a designated control.
- setFocus() - 类中的方法 weka.gui.sql.InfoPanel
-
sets the focus in a designated control
- setFocus() - 类中的方法 weka.gui.sql.QueryPanel
-
sets the focus in a designated control.
- setFocus() - 类中的方法 weka.gui.sql.ResultPanel
-
sets the focus in a designated control
- setFold(int) - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Selects a fold.
- setFold(int) - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Selects a fold.
- setFoldColumn(int) - 类中的方法 weka.experiment.PairedTTester
-
Set the value of FoldColumn.
- setFoldColumn(int) - 接口中的方法 weka.experiment.Tester
-
Set the value of FoldColumn.
- setFolds(int) - 类中的方法 weka.attributeSelection.AttributeSelection
-
set the number of folds for cross validation
- setFolds(int) - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Set the number of folds to use for cross validation
- setFolds(int) - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Set the number of folds to use for accuracy estimation
- setFolds(int) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
the number of folds to use
- setFolds(int) - 类中的方法 weka.classifiers.rules.JRip
-
Sets the number of folds to use
- setFolds(int) - 类中的方法 weka.classifiers.rules.Ridor
- setFolds(int) - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Set the number of folds for the cross validation
- setFoldsType(SelectedTag) - 类中的方法 weka.attributeSelection.RaceSearch
-
Set the xfold type
- setFont(Font) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Set current font.
- setFormat(String) - 类中的方法 weka.core.Debug.Timestamp
-
sets the format for the timestamp
- setForwardSelectionMethod(SelectedTag) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Set the search direction
- setFrequencyLimit(int) - 类中的方法 weka.classifiers.bayes.AODE
-
Sets the frequency limit
- setFrequencyLimit(int) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Sets the frequency limit
- setFrequencyThreshold(double) - 类中的方法 weka.associations.Tertius
-
Set the value of frequencyThreshold.
- setFunction(SelectedTag) - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Sets the function for generating the data.
- setFunctionValue(int, double) - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Sets a particular function value
- setGamma(double) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets gamma (default = 1/no of attributes)
- setGamma(double) - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Sets the gamma value.
- setGenerateRanking(boolean) - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Records whether the user has requested a ranked list of attributes.
- setGenerateRanking(boolean) - 类中的方法 weka.attributeSelection.RaceSearch
-
Records whether the user has requested a ranked list of attributes.
- setGenerateRanking(boolean) - 接口中的方法 weka.attributeSelection.RankedOutputSearch
-
Sets whether or not ranking is to be performed.
- setGenerateRanking(boolean) - 类中的方法 weka.attributeSelection.Ranker
-
This is a dummy set method---Ranker is ONLY capable of producing a ranked list of attributes for attribute evaluators.
- setGenerator(DataGenerator) - 类中的方法 weka.gui.explorer.DataGeneratorPanel
-
sets the generator to use initially
- setGeneratorSamplesBase(double) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set the base for computing the number of samples to obtain from each generator.
- setGeneratorSamplesBase(double) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the base for computing the number of samples to obtain from each generator.
- setGlobalBlend(int) - 类中的方法 weka.classifiers.lazy.KStar
-
Set the global blend parameter
- setGlobalModel(NBTreeNoSplit) - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Set the global naive bayes model for this node
- setGridIsExtendable(boolean) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set whether the grid can be extended dynamically.
- setGridWidth(int) - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Set the width of the grid of plots
- setGroupIdentifier(long) - 类中的方法 weka.gui.beans.BatchClassifierEvent
- setGUI(boolean) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
This will set whether A GUI is brought up to allow interaction by the user with the neural network during training.
- setGUIType(SelectedTag) - 类中的方法 weka.gui.Main
-
Sets the type of GUI to use.
- setHandler(CapabilitiesHandler) - 类中的方法 weka.core.FindWithCapabilities
-
sets the Capabilities handler to generate the data for.
- setHandler(CapabilitiesHandler) - 类中的方法 weka.core.TestInstances
-
sets the Capabilities handler to generate the data for
- setHandleRightClicks(boolean) - 类中的方法 weka.gui.ResultHistoryPanel
-
Set whether the result history list should handle right clicks or whether the parent object will handle them.
- setHashtable(Hashtable) - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Set hashtable from END.
- setHashtable(Hashtable) - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Set hashtable from END.
- setHashtable(Hashtable) - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
-
Set hashtable from END.
- setHDRank(int) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Sets the rank associated to the Hausdorff distance
- setHeuristic(boolean) - 类中的方法 weka.classifiers.trees.BFTree
-
Set if use heuristic search for nominal attributes in multi-class problems.
- setHeuristic(boolean) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Set if use heuristic search for nominal attributes in multi-class problems.
- setHeuristicStop(int) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Set the value of heuristicStop.
- setHeuristicStop(int) - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Sets the option "heuristicStop".
- setHidden(boolean) - 类中的方法 weka.gui.beans.BeanConnection
-
Make this connection invisible on the display
- setHiddenLayers(String) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
This will set what the hidden layers are made up of when auto build is enabled.
- setHighlight(String) - 类中的方法 weka.gui.treevisualizer.TreeVisualizer
-
Set the highlight for the node with the given id
- setHistory(DefaultListModel) - 类中的方法 weka.gui.sql.ConnectionPanel
-
sets the local history to the given one.
- setHistory(DefaultListModel) - 类中的方法 weka.gui.sql.QueryPanel
-
sets the local history to the given one.
- setHoldOutFile(File) - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Set the file that contains hold out/test instances
- setHornClauses(boolean) - 类中的方法 weka.associations.Tertius
-
Set the value of hornClauses.
- setHyperparameterRange(String) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the range of hyperparameter values to consider during CV-based selection
- setHyperparameterSelection(SelectedTag) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the method used to select the hyperparameter
- setHyperparameterValue(double) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the hyperparameter value.
- setID(int) - 类中的方法 weka.core.Tag
-
Sets the numeric ID of the Tag.
- setIDFTransform(boolean) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j. - setIDIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Sets index of the attribute used.
- setIDStr(String) - 类中的方法 weka.core.Tag
-
Sets the string ID of the Tag.
- setIgnoreClass(boolean) - 类中的方法 weka.filters.unsupervised.attribute.PotentialClassIgnorer
-
Set the IgnoreClass value.
- setIgnoredAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Sets the ranges of attributes to be ignored.
- setIgnoredAttributeIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Sets the ranges of attributes to be ignored.
- setIgnoredProperties(String) - 类中的方法 weka.core.CheckGOE
-
Sets the properties to ignore in checkToolTips().
- setIgnoreRange(String) - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Set which attributes are to be ignored
- setIncludeClass(boolean) - 类中的方法 weka.core.InstanceComparator
-
sets whether the class should be included (= TRUE) in the comparison
- setIncludeClass(boolean) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Sets whether the class can be cleaned, too.
- setIndex(int) - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Set the index of this field in the mining schema Instances
- setInitAsNaiveBayes(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
Sets whether to init as naive bayes
- setInitAsNaiveBayes(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Sets whether to init as naive bayes
- setInitAsNaiveBayes(boolean) - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
Sets whether to init as naive bayes
- setInitAsNaiveBayes(boolean) - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Sets whether to init as naive bayes
- setInitFile(File) - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Sets the file to initialize the filter with, can be null.
- setInitFileClassIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Sets class index of the file to initialize the filter with.
- setInitialAnchorRandom(boolean) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Sets whether if the initial anchor is chosen randomly.
- setInputCenterFile(File) - 类中的方法 weka.clusterers.XMeans
-
Sets the file to read the list of centers from.
- setInputFilename(String) - 类中的方法 weka.gui.GenericPropertiesCreator
-
sets the file to get the information about the packages from.
- setInputFormat(Instances) - 类中的方法 weka.filters.AllFilter
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.Filter
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.SimpleFilter
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.supervised.instance.Resample
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Center
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.NumericToBinary
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Obfuscate
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.PotentialClassIgnorer
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.ReplaceMissingValues
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.Standardize
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.TimeSeriesDelta
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.attribute.TimeSeriesTranslate
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.NonSparseToSparse
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Sets the format of the input instances.
- setInputFormat(Instances) - 类中的方法 weka.filters.unsupervised.instance.SparseToNonSparse
-
Sets the format of the input instances.
- setInputOrder(SelectedTag) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the input order.
- setInputs(Vector) - 类中的方法 weka.gui.beans.MetaBean
- setInstance(Instance) - 类中的方法 weka.gui.beans.InstanceEvent
-
Set the instance
- setInstanceIndex(int, boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Changes the boolean value at the specified index in the InstIndexes array
- setInstanceList(int[]) - 类中的方法 weka.core.neighboursearch.balltrees.BallSplitter
-
Sets the master index array containing indices of the training instances.
- setInstanceList(int[]) - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Sets the master index array that points to instances in m_Instances, so that only this array is manipulated, and m_Instances is left untouched.
- setInstanceList(int[]) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Sets the master index array that points to instances in m_Instances, so that only this array is manipulated, and m_Instances is left untouched.
- setInstanceList(int[]) - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Sets the master index array containing indices of the training instances.
- setInstanceRange(int) - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Sets the number of instances forward to translate values between.
- setInstances(Instances) - 类中的方法 weka.core.converters.AbstractSaver
-
Sets instances that should be stored.
- setInstances(Instances) - 类中的方法 weka.core.converters.LibSVMSaver
-
Sets instances that should be stored.
- setInstances(Instances) - 接口中的方法 weka.core.converters.Saver
-
Sets the instances to be saved
- setInstances(Instances) - 类中的方法 weka.core.converters.SVMLightSaver
-
Sets instances that should be stored.
- setInstances(Instances) - 类中的方法 weka.core.converters.XRFFSaver
-
Sets instances that should be stored.
- setInstances(Instances) - 接口中的方法 weka.core.DistanceFunction
-
Sets the instances.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.BallTree
-
Builds the BallTree based on the given set of instances.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.balltrees.BallSplitter
-
Sets the training instances on which the tree is (or is to be) built.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Sets the instances on which the tree is to be built.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Sets the instances on which the tree is to be built.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Builds the Cover Tree on the given set of instances.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.KDTree
-
Builds the KDTree on the given set of instances.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Sets the training instances on which the tree is (or is to be) built.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Sets the instances comprising the current neighbourhood.
- setInstances(Instances) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Sets the instances.
- setInstances(Instances) - 类中的方法 weka.core.NormalizableDistance
-
Sets the instances.
- setInstances(Instances) - 类中的方法 weka.core.xml.XMLInstances
-
builds up the XML structure based on the given data
- setInstances(Instances) - 类中的方法 weka.experiment.AveragingResultProducer
-
Sets the dataset that results will be obtained for.
- setInstances(Instances) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Sets the dataset that results will be obtained for.
- setInstances(Instances) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Sets the dataset that results will be obtained for.
- setInstances(Instances) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Sets the dataset that results will be obtained for.
- setInstances(Instances) - 类中的方法 weka.experiment.PairedTTester
-
Set the value of Instances.
- setInstances(Instances) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Sets the dataset that results will be obtained for.
- setInstances(Instances) - 接口中的方法 weka.experiment.ResultProducer
-
Sets the dataset that results will be obtained for.
- setInstances(Instances) - 接口中的方法 weka.experiment.Tester
-
Set the value of Instances.
- setInstances(Instances) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
displays the given instances, i.e.
- setInstances(Instances) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
sets the data
- setInstances(Instances) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
sets the data
- setInstances(Instances) - 类中的方法 weka.gui.AttributeListPanel
-
Sets the instances who's attribute names will be displayed.
- setInstances(Instances) - 类中的方法 weka.gui.AttributeSelectionPanel
-
Sets the instances who's attribute names will be displayed.
- setInstances(Instances) - 类中的方法 weka.gui.AttributeSummaryPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - 类中的方法 weka.gui.AttributeVisualizationPanel
-
Sets the instances for use
- setInstances(Instances) - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Set instances for this bean.
- setInstances(Instances) - 类中的方法 weka.gui.beans.DataVisualizer
-
Set instances for this bean.
- setInstances(Instances) - 类中的方法 weka.gui.beans.ScatterPlotMatrix
-
Set instances for this bean.
- setInstances(Instances) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Set the training instances
- setInstances(Instances) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the training data
- setInstances(Instances) - 类中的方法 weka.gui.experiment.ResultsPanel
-
Sets up the panel with a new set of instances, attempting to guess the correct settings for various columns.
- setInstances(Instances) - 类中的方法 weka.gui.explorer.AssociationsPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - 类中的方法 weka.gui.explorer.AttributeSelectionPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - 类中的方法 weka.gui.explorer.ClassifierPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - 类中的方法 weka.gui.explorer.ClustererPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - 接口中的方法 weka.gui.explorer.Explorer.ExplorerPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Tells the panel to use a new base set of instances.
- setInstances(Instances) - 类中的方法 weka.gui.InstancesSummaryPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - 类中的方法 weka.gui.SetInstancesPanel
-
Updates the set of instances that is currently held by the panel
- setInstances(Instances) - 类中的方法 weka.gui.ViewerDialog
-
sets the instances to display
- setInstances(Instances) - 类中的方法 weka.gui.visualize.AttributePanel
-
This sets the instances to be drawn into the attribute panel
- setInstances(Instances) - 类中的方法 weka.gui.visualize.ClassPanel
-
Set the instances.
- setInstances(Instances) - 类中的方法 weka.gui.visualize.MatrixPanel
-
This method changes the Instances object of this class to a new one.
- setInstances(Instances) - 类中的方法 weka.gui.visualize.Plot2D
-
Sets the master plot from a set of instances
- setInstances(Instances) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Tells the panel to use a new set of instances.
- setInstancesFromDB(InstanceQuery) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Loads instances from a database
- setInstancesFromDBQ(String, String, String, String) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Loads instances from an SQL query the user provided with the SqlViewerDialog, then loads the instances in a background process.
- setInstancesFromFile(AbstractFileLoader) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Loads results from a set of instances retrieved with the supplied loader.
- setInstancesFromFileQ() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Queries the user for a file to load instances from, then loads the instances in a background process.
- setInstancesFromFileQ() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Queries the user for a file to load instances from, then loads the instances in a background process.
- setInstancesFromFileQ() - 类中的方法 weka.gui.SetInstancesPanel
-
Queries the user for a file to load instances from, then loads the instances in a background process.
- setInstancesFromURL(URL) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Loads instances from a URL.
- setInstancesFromURLQ() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Queries the user for a URL to load instances from, then loads the instances in a background process.
- setInstancesFromURLQ() - 类中的方法 weka.gui.SetInstancesPanel
-
Queries the user for a URL to load instances from, then loads the instances in a background process.
- setInstancesIndices(String) - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Sets the ranges of instances to be selected.
- SetInstancesPanel - weka.gui中的类
-
A panel that displays an instance summary for a set of instances and lets the user open a set of instances from either a file or URL.
- SetInstancesPanel() - 类的构造器 weka.gui.SetInstancesPanel
-
Default constructor
- SetInstancesPanel(boolean, ConverterFileChooser) - 类的构造器 weka.gui.SetInstancesPanel
-
Create the panel.
- setInsts(int[], boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Changes the boolean value at the specified index in the InstIndexes array
- setInterAnchorDistances(Vector, MiddleOutConstructor.TempNode, Vector) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Sets the distances of a supplied new anchor to all the rest of the previous anchor points.
- setInternalCacheSize(int) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
sets the size of the internal cache for intermediate results.
- setInternals(boolean) - 类中的方法 weka.classifiers.bayes.WAODE
-
Sets whether internals about classifier are printed via toString().
- setInvert(boolean) - 类中的方法 weka.core.Range
-
Sets whether the range sense is inverted, i.e.
- setInvert(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Set whether selection is inverted.
- setInvertSelection(boolean) - 接口中的方法 weka.core.DistanceFunction
-
Sets whether the matching sense of attribute indices is inverted or not.
- setInvertSelection(boolean) - 类中的方法 weka.core.NormalizableDistance
-
Sets whether the matching sense of attribute indices is inverted or not.
- setInvertSelection(boolean) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Sets whether selected columns should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.supervised.instance.Resample
-
Sets whether the selection is inverted (only if instances are drawn WIHTOUT replacement).
- setInvertSelection(boolean) - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Sets if selection is to be inverted.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Set whether selected columns should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Set whether selected columns should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Sets whether selected columns should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Set whether selected columns should be select or unselect.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Sets whether selected columns should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Sets whether the selection of the indices is inverted or not
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Sets whether selected columns should be worked on or all the others apart from these.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Set whether selected columns should be transformed or not.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Sets whether selected columns should be processed or skipped.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Set whether selected columns should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Set whether selected columns should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets whether selected columns should be processed or skipped.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Sets if selection is to be inverted.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Set whether selected values should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Sets if selection is to be inverted.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Sets if selection is to be inverted.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Set whether selected values should be removed or kept.
- setInvertSelection(boolean) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Sets whether the selection is inverted (only if instances are drawn WIHTOUT replacement).
- setItem(int[]) - 类中的方法 weka.associations.ItemSet
-
Sets an item sets
- setItemAt(int, int) - 类中的方法 weka.associations.ItemSet
-
Sets the index of an attribute value
- setJitter(int) - 类中的方法 weka.gui.visualize.Plot2D
-
Set level of jitter and repaint the plot using the new jitter value
- setKDTree(KDTree) - 类中的方法 weka.clusterers.XMeans
-
Sets the KDTree class.
- setKernel(Kernel) - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Sets the kernel to use.
- setKernel(Kernel) - 类中的方法 weka.classifiers.functions.SMO.BinarySMO
-
sets the kernel to use
- setKernel(Kernel) - 类中的方法 weka.classifiers.functions.SMO
-
sets the kernel to use
- setKernel(Kernel) - 类中的方法 weka.classifiers.functions.SMOreg
-
sets the kernel to use
- setKernel(Kernel) - 类中的方法 weka.classifiers.functions.supportVector.CheckKernel
-
Set the lernel to test.
- setKernel(Kernel) - 类中的方法 weka.classifiers.mi.MISMO
-
Sets the kernel to use.
- setKernel(Kernel) - 类中的方法 weka.classifiers.mi.MISVM
-
Sets the kernel to use.
- setKernel(Kernel) - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Sets the kernel to use.
- setKernelBandwidth(int) - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
-
Set the kernel bandwidth (number of nearest neighbours to cover)
- setKernelFactorExpression(String) - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Sets the expression for the kernel.
- setKernelMatrixFile(File) - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Sets the file holding the kernel matrix
- setKernelType(SelectedTag) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets type of kernel function (default KERNELTYPE_RBF)
- setKey(String) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Sets the key for this DataObject
- setKey(String) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Sets the key for this DataObject
- setKey(String) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Sets the key for this DataObject
- setKeyFieldName(String) - 类中的方法 weka.experiment.AveragingResultProducer
-
Set the value of KeyFieldName.
- setKeys(String) - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets the key columns of a database table
- setKeywords(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Sets the keywords (comma-separated list) to use.
- setKeywordsMaskChar(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Sets the mask character to append to table or attribute names that are a reserved keyword.
- setKNN(int) - 类中的方法 weka.classifiers.lazy.IBk
-
Set the number of neighbours the learner is to use.
- setKNN(int) - 类中的方法 weka.classifiers.lazy.LWL
-
Sets the number of neighbours used for kernel bandwidth setting.
- setKValue(int) - 类中的方法 weka.classifiers.trees.RandomTree
-
Set the value of K.
- setLabels(String) - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Sets the comma-separated list of labels.
- setLambda(double) - 类中的方法 weka.classifiers.functions.SPegasos
-
Set the value of lambda to use
- setLambda(double) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Sets the lambda constant used in the string kernel
- setLearningRate(double) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
The learning rate can be set using this command.
- setLegendText(Vector) - 类中的方法 weka.gui.beans.ChartEvent
-
Set the legend text vector
- setLikelihoodThreshold(double) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Set the value of Precision.
- setLinkType(SelectedTag) - 类中的方法 weka.clusterers.HierarchicalClusterer
- setListData(Object[]) - 类中的方法 weka.gui.CheckBoxList
-
Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.
- setListData(Vector) - 类中的方法 weka.gui.CheckBoxList
-
Constructs a CheckBoxListModel from a Vector and then applies setModel to it.
- setLNorm(double) - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Set the L-norm to used
- setLoader(Loader) - 类中的方法 weka.gui.beans.Loader
-
Set the loader to use
- setLocallyPredictive(boolean) - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Include locally predictive attributes
- setLocationProbs(int, double[]) - 类中的方法 weka.gui.boundaryvisualizer.RemoteResult
-
Store the classifier's distribution for a particular pixel in the visualization
- setLog(Debug.Log) - 类中的方法 weka.core.Debug.Random
-
the log to use, if it is null then stdout is used
- setLog(Logger) - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Set a logger to use.
- setLog(Logger) - 接口中的方法 weka.core.pmml.PMMLModel
-
Set a logger to use.
- setLog(Logger) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Set a log for this bean
- setLog(Logger) - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Set a log for this bean
- setLog(Logger) - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.Associator
-
Set a logger
- setLog(Logger) - 接口中的方法 weka.gui.beans.BeanCommon
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.ClassAssigner
- setLog(Logger) - 类中的方法 weka.gui.beans.Classifier
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.ClassValuePicker
- setLog(Logger) - 类中的方法 weka.gui.beans.Clusterer
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.Filter
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.FlowRunner
- setLog(Logger) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.Loader
-
Set a logger
- setLog(Logger) - 接口中的方法 weka.gui.beans.LogWriter
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.MetaBean
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.PredictionAppender
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Set a log for this bean.
- setLog(Logger) - 类中的方法 weka.gui.beans.StripChart
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.beans.TextViewer
-
Set a logger
- setLog(Logger) - 类中的方法 weka.gui.explorer.AssociationsPanel
-
Sets the Logger to receive informational messages
- setLog(Logger) - 类中的方法 weka.gui.explorer.AttributeSelectionPanel
-
Sets the Logger to receive informational messages
- setLog(Logger) - 类中的方法 weka.gui.explorer.ClassifierPanel
-
Sets the Logger to receive informational messages
- setLog(Logger) - 类中的方法 weka.gui.explorer.ClustererPanel
-
Sets the Logger to receive informational messages
- setLog(Logger) - 类中的方法 weka.gui.explorer.DataGeneratorPanel
-
Sets the Logger to receive informational messages
- setLog(Logger) - 接口中的方法 weka.gui.explorer.Explorer.LogHandler
-
Sets the Logger to receive informational messages
- setLog(Logger) - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Sets the Logger to receive informational messages
- setLog(Logger) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Sets the Logger to receive informational messages
- setLogFile(File) - 类中的方法 weka.classifiers.meta.GridSearch
-
Sets the log file to use.
- setLookAndFeel() - 类中的静态方法 weka.gui.LookAndFeel
-
sets the look and feel to the one in the props-file or if not set the default one of the system
- setLookAndFeel(String) - 类中的静态方法 weka.gui.LookAndFeel
-
sets the look and feel to the specified class
- setLookupCacheSize(int) - 类中的方法 weka.attributeSelection.BestFirst
-
Set the maximum size of the evaluated subset cache (hashtable).
- setLookupCacheSize(int) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Set the maximum size of the evaluated subset cache (hashtable).
- setLookupCacheSize(int) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Set the maximum size of the evaluated subset cache (hashtable).
- setLoss(double) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets the epsilon in loss function of epsilon-SVR (default 0.1)
- setLossFunction(SelectedTag) - 类中的方法 weka.classifiers.functions.SPegasos
-
Set the loss function to use.
- setLowerBoundMinSupport(double) - 类中的方法 weka.associations.Apriori
-
Set the value of lowerBoundMinSupport.
- setLowerBoundMinSupport(double) - 类中的方法 weka.associations.FPGrowth
-
Set the value of lowerBoundMinSupport.
- setLowerCaseTokens(boolean) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets whether if the tokens are to be downcased or not.
- setLowerSize(int) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Set the value of LowerSize.
- setMajorityClass(boolean) - 类中的方法 weka.classifiers.rules.Ridor
- setMakeBinary(boolean) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Sets whether binary attributes should be made for discretized ones.
- setMakeBinary(boolean) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Sets whether binary attributes should be made for discretized ones.
- setManualThresholdValue(double) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Sets the value for a manual threshold.
- setMargin(int, double[]) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
set marginal distibution for a node
- setMarkovBlanketClassifier(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
- setMarkovBlanketClassifier(boolean) - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
- setMasterPlot(PlotData2D) - 类中的方法 weka.gui.visualize.Plot2D
-
Set the master plot.
- setMasterPlot(PlotData2D) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Set the master plot for the visualize panel
- setMatchMissingValues(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Sets whether missing values are counted as a match.
- setMatrix(double[], boolean) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Set the whole matrix from a 1-D array
- setMatrix(int[], int[], Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Set a submatrix.
- setMatrix(int[], int, int, Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Set a submatrix.
- setMatrix(int, int, int[], Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Set a submatrix.
- setMatrix(int, int, int, int, double) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Set the submatrix A[i0:i1][j0:j1] with a same value
- setMatrix(int, int, int, int, Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Set a submatrix.
- setMatrix(int, int, int, DoubleVector) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Set the submatrix A[i0:i1][j] with the values stored in a DoubleVector
- setMax(double) - 类中的方法 weka.gui.beans.ChartEvent
-
Set the max y value
- setMaxBoostingIterations(int) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Set the value of maxBoostingIterations.
- setMaxCardinality(int) - 类中的方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
-
sets the cardinality
- setMaxCardinality(int) - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Sets the maximum number of values allowed for nominal attributes, before they're skipped.
- setMaxChunkSize(int) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Set the maximum chunk size
- setMaxCount(double) - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Sets the value for the max count
- setMaxDefault(double) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Set the naximum default.
- setMaxDepth(int) - 类中的方法 weka.classifiers.trees.RandomForest
-
Set the maximum depth of the tree, 0 for unlimited.
- setMaxDepth(int) - 类中的方法 weka.classifiers.trees.RandomTree
-
Set the maximum depth of the tree, 0 for unlimited.
- setMaxDepth(int) - 类中的方法 weka.classifiers.trees.REPTree
-
Set the value of MaxDepth.
- setMaxGenerations(int) - 类中的方法 weka.attributeSelection.GeneticSearch
-
set the number of generations to evaluate
- setMaxGridExtensions(int) - 类中的方法 weka.classifiers.meta.GridSearch
-
Sets the maximum number of grid extensions, -1 for unlimited.
- setMaxGroup(int) - 类中的方法 weka.classifiers.meta.RotationForest
-
Sets the maximum size of a group.
- setMaximumAttributeNames(int) - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Sets maximum number of attributes to include in transformed attribute names.
- setMaximumAttributeNames(int) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Sets maximum number of attributes to include in transformed attribute names.
- setMaximumAttributeNames(int) - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Sets maximum number of attributes to include in transformed attribute names.
- setMaximumAttributes(int) - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Sets maximum number of PC attributes to retain.
- setMaximumVariancePercentageAllowed(double) - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Sets the maximum variance attributes are allowed to have before they are deleted by the filter.
- setMaxInstancesInLeaf(int) - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Sets the maximum number of instances allowed in a leaf.
- setMaxInstancesInLeaf(int) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Sets the maximum number of instances allowed in a leaf.
- setMaxInstInLeaf(int) - 类中的方法 weka.core.neighboursearch.KDTree
-
Sets the maximum number of instances in a leaf.
- setMaxInstNum(int) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the upper boundary for instances per cluster.
- setMaxInstNum(int) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets the upper boundary for instances per cluster.
- setMaxIteration(int) - 类中的方法 weka.core.Optimization
-
Set the maximal number of iterations in searching (Default 200)
- setMaxIterations(int) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the maximum number of iterations to perform
- setMaxIterations(int) - 类中的方法 weka.classifiers.mi.MIBoost
-
Set the maximum number of boost iterations
- setMaxIterations(int) - 类中的方法 weka.classifiers.mi.MISVM
-
Sets the maximum number of iterations.
- setMaxIterations(int) - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Sets the parameter "maxIterations".
- setMaxIterations(int) - 类中的方法 weka.clusterers.EM
-
Set the maximum number of iterations to perform
- setMaxIterations(int) - 类中的方法 weka.clusterers.sIB
-
Set the max number of iterations
- setMaxIterations(int) - 类中的方法 weka.clusterers.SimpleKMeans
-
set the maximum number of iterations to be executed
- setMaxIterations(int) - 类中的方法 weka.clusterers.XMeans
-
Sets the maximum number of iterations to perform.
- setMaxIterations(int) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed
- setMaxIts(int) - 类中的方法 weka.classifiers.functions.Logistic
-
Set the value of MaxIts.
- setMaxIts(int) - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Set the value of MaxIts.
- setMaxK(int) - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Set the value of maxK.
- setMaxKMeans(int) - 类中的方法 weka.clusterers.XMeans
-
Set the maximum number of iterations to perform in KMeans.
- setMaxKMeansForChildren(int) - 类中的方法 weka.clusterers.XMeans
-
Sets the maximum number of iterations KMeans that is performed on the child centers.
- setMaxNrOfParents(int) - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
Sets the max number of parents
- setMaxNrOfParents(int) - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Sets the max number of parents
- setMaxNrOfParents(int) - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
Sets the max number of parents
- setMaxNrOfParents(int) - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Sets the max number of parents
- setMaxNrOfParents(int) - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Sets the max number of parents
- setMaxNumberOfItems(int) - 类中的方法 weka.associations.FPGrowth
-
Set the maximum number of items to include in large items sets.
- setMaxNumClusters(int) - 类中的方法 weka.clusterers.XMeans
-
Sets the maximum number of clusters to generate.
- setMaxPlots(int) - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Set the maximum number of plots to display
- setMaxRadius(double) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the upper boundary for the radiuses of the clusters.
- setMaxRange(double) - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Sets the upper boundary for the range of x
- setMaxRelativeLeafRadius(double) - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Sets the maximum relative radius, allowed for a leaf node.
- setMaxRows(int) - 类中的方法 weka.gui.sql.QueryPanel
-
sets the maximum number of rows to display.
- setMaxRuleSize(int) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Sets the maximum number of tests in rules.
- setMaxSubsequenceLength(int) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Sets the maximum length of the subsequence.
- setMaxThreshold(double) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Set the maximum threshold.
- setMDLTheoryWeight(double) - 类中的方法 weka.classifiers.rules.RuleStats
-
Set the weight of theory in MDL calcualtion
- setMean(int, int, double) - 类中的方法 weka.experiment.ResultMatrix
-
sets the mean at the given position (if the position is valid)
- setMeanPrec(int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the precision for the means
- setMeanPrec(int) - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
Sets the precision of the mean output.
- setMeanSquared(boolean) - 类中的方法 weka.classifiers.lazy.IBk
-
Sets whether the mean squared error is used rather than mean absolute error when doing cross-validation.
- setMeanStddev(String) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets mean and standarddeviation.
- setMeanWidth(int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the width for the mean (0 = optimal)
- setMeasure(SelectedTag) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
set measure used for determining threshold
- setMeasurePerformance(boolean) - 类中的方法 weka.core.neighboursearch.BallTree
-
Sets whether to calculate the performance statistics or not.
- setMeasurePerformance(boolean) - 类中的方法 weka.core.neighboursearch.KDTree
-
Sets whether to calculate the performance statistics or not.
- setMeasurePerformance(boolean) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Sets whether to calculate the performance statistics or not.
- setMestWeight(double) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Sets the weight for m-estimate
- setMetaClassifier(Classifier) - 类中的方法 weka.classifiers.meta.Stacking
-
Adds meta classifier
- setMethod(NeuralMethod) - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Set how this node should operate (note that the neural method has no internal state, so the same object can be used by any number of nodes.
- setMethod(SelectedTag) - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Sets the method used.
- setMethod(SelectedTag) - 类中的方法 weka.classifiers.mi.MIWrapper
-
Set the method used in testing.
- setMethodName(String) - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Set the transformation method.
- setMetricType(SelectedTag) - 类中的方法 weka.associations.Apriori
-
Set the metric type for ranking rules
- setMetricType(SelectedTag) - 类中的方法 weka.associations.FPGrowth
-
Set the metric type to use.
- setMin(double) - 类中的方法 weka.gui.beans.ChartEvent
-
Set the min y value
- setMinBoxRelWidth(double) - 类中的方法 weka.core.neighboursearch.KDTree
-
Sets the minimum relative box width.
- setMinBucketSize(int) - 类中的方法 weka.classifiers.rules.OneR
-
Set the value of minBucketSize.
- setMinChange(int) - 类中的方法 weka.clusterers.sIB
-
set the minimum number of changes
- setMinChunkSize(int) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Set the minimum chunk size
- setMinDefault(double) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Set the minimum default.
- setMinGroup(int) - 类中的方法 weka.classifiers.meta.RotationForest
-
Sets the minimum size of a group.
- setMinimax(boolean) - 类中的方法 weka.classifiers.mi.MISMO
-
Set if the MIMinimax feature space is to be used.
- setMinimizeExpectedCost(boolean) - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Set the value of MinimizeExpectedCost.
- setMinimumBucketSize(int) - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Set the minumum bucket size used by OneR
- setMinimumNumberInstances(int) - 类中的方法 weka.core.Capabilities
-
sets the minimum number of instances that have to be in the dataset
- setMinInstNum(int) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the lower boundary for instances per cluster.
- setMinInstNum(int) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets the lower boundary for instances per cluster.
- setMinMaxValues() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Sets the minimum and maximum values for each attribute in different arrays by walking through every DataObject of the database
- setMinMaxValues() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Sets the minimum and maximum values for each attribute in different arrays by walking through every DataObject of the database
- setMinMaxX(double, double) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the minimum and maximum values of the x axis fixed dimension
- setMinMaxY(double, double) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the minimum and maximum values of the y axis fixed dimension
- setMinMetric(double) - 类中的方法 weka.associations.Apriori
-
Set the value of minConfidence.
- setMinMetric(double) - 类中的方法 weka.associations.FPGrowth
-
Set the value of minConfidence.
- setMinNo(double) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Sets the minimum total weight of the instances in a rule
- setMinNo(double) - 类中的方法 weka.classifiers.rules.JRip
-
Sets the minimum total weight of the instances in a rule
- setMinNo(double) - 类中的方法 weka.classifiers.rules.Ridor
- setMinNum(double) - 类中的方法 weka.classifiers.trees.RandomTree
-
Set the value of MinNum.
- setMinNum(double) - 类中的方法 weka.classifiers.trees.REPTree
-
Set the value of MinNum.
- setMinNumClusters(int) - 类中的方法 weka.clusterers.XMeans
-
Sets the minimum number of clusters to generate.
- setMinNumInstances(double) - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Set the minimum number of instances to allow at a leaf node
- setMinNumInstances(double) - 类中的方法 weka.classifiers.trees.m5.Rule
-
Set the minumum number of instances to allow at a leaf node
- setMinNumInstances(double) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Set the minumum number of instances to allow at a leaf node
- setMinNumInstances(int) - 类中的方法 weka.classifiers.trees.FT
-
Set the value of minNumInstances.
- setMinNumInstances(int) - 类中的方法 weka.classifiers.trees.LMT
-
Set the value of minNumInstances.
- setMinNumObj(double) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Set minimal number of instances at the terminal nodes.
- setMinNumObj(int) - 类中的方法 weka.classifiers.rules.PART
-
Set the value of minNumObj.
- setMinNumObj(int) - 类中的方法 weka.classifiers.trees.BFTree
-
Set minimal number of instances at the terminal nodes.
- setMinNumObj(int) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of minNumObj.
- setMinNumObj(int) - 类中的方法 weka.classifiers.trees.J48graft
-
Set the value of minNumObj.
- setMinPoints(int) - 类中的方法 weka.clusterers.DBSCAN
-
Sets a new value for minPoints
- setMinPoints(int) - 类中的方法 weka.clusterers.OPTICS
-
Sets a new value for minPoints
- setMinRadius(double) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the lower boundary for the radiuses of the clusters.
- setMinRange(double) - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Sets the lower boundary for the range of x
- setMinRuleSize(int) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Sets the minimum number of tests in rules.
- setMinStdDev(double) - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Set the MinStdDev value.
- setMinStdDev(double) - 类中的方法 weka.clusterers.EM
-
Set the minimum value for standard deviation when calculating normal density.
- setMinStdDev(double) - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Set the minimum value for standard deviation when calculating normal density.
- setMinStdDevPerAtt(double[]) - 类中的方法 weka.clusterers.EM
- setMinSupport(double) - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Sets the minimum support threshold.
- setMinTermFreq(int) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Set the MinTermFreq value.
- setMinThreshold(double) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Set the minimum threshold.
- setMinVarianceProp(double) - 类中的方法 weka.classifiers.trees.REPTree
-
Set the value of MinVarianceProp.
- setMissing(int) - 类中的方法 weka.core.Instance
-
Sets a specific value to be "missing".
- setMissing(Attribute) - 类中的方法 weka.core.Instance
-
Sets a specific value to be "missing".
- setMissingMerge(boolean) - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
distribute the counts for missing values across observed values
- setMissingMerge(boolean) - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
distribute the counts for missing values across observed values
- setMissingMerge(boolean) - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
distribute the counts for missing values across observed values
- setMissingMerge(boolean) - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
distribute the counts for missing values across observed values
- setMissingMode(int) - 类中的方法 weka.classifiers.lazy.kstar.KStarNumericAttribute
-
Set the missing value mode.
- setMissingMode(SelectedTag) - 类中的方法 weka.classifiers.lazy.KStar
-
Sets the method to use for handling missing values.
- setMissingSeparate(boolean) - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Treat missing as a separate value
- setMissingValue(String) - 类中的方法 weka.core.converters.CSVLoader
-
Sets the placeholder for missing values.
- setMissingValues(SelectedTag) - 类中的方法 weka.associations.Tertius
-
Set the value of missingValues.
- setMixingDistribution(DiscreteFunction) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Sets the mixing distribution
- setModel(ListModel) - 类中的方法 weka.gui.CheckBoxList
-
sets the model - must be an instance of CheckBoxListModel
- setModel(TableModel) - 类中的方法 weka.gui.arffviewer.ArffTable
-
sets the new model
- setModel(TableModel) - 类中的方法 weka.gui.SortedTableModel
-
sets the model to use
- setModel(Classifier) - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Sets the fully built model to use, if one doesn't want to load a model from a file or already deserialized a model from somewhere else.
- setModelFile(File) - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Sets the file containing the serialized model.
- setModelType(SelectedTag) - 类中的方法 weka.classifiers.trees.FT
-
Set the Functional Tree type.
- setModePanel(SetupModePanel) - 类中的方法 weka.gui.experiment.SimpleSetupPanel
-
Sets the panel used to switch between simple and advanced modes.
- setModifyHeader(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Sets whether the header will be modified when selecting on nominal attributes.
- setModifyHeader(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Sets whether the header will be modified when selecting on nominal attributes.
- setMomentum(double) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
The momentum can be set using this command.
- setMultiInstance(boolean) - 类中的方法 weka.core.TestInstances
-
sets whether multi-instance data should be generated (with a fixed data structure)
- setMultinomialWord(boolean) - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Sets whether use binary text representation
- setMutationProb(double) - 类中的方法 weka.attributeSelection.GeneticSearch
-
set the probability of mutation
- setName(String) - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Set the name for the new attribute.
- setName(String) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Set a name for this plot
- setNearestNeighbors(int) - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Sets the number of nearest neighbors to use.
- setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - 类中的方法 weka.classifiers.lazy.IBk
-
Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).
- setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - 类中的方法 weka.classifiers.lazy.LWL
-
Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).
- setNegation(Literal) - 类中的方法 weka.associations.tertius.Literal
- setNegation(SelectedTag) - 类中的方法 weka.associations.Tertius
-
Set the value of negation.
- setNewToolTip(String) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Displays a toolTip for the selected DataObject
- setNGramMaxSize(int) - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Sets the max size of the Ngram.
- setNGramMinSize(int) - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Sets the min size of the Ngram.
- setNoClass(boolean) - 类中的方法 weka.core.TestInstances
-
whether to have no class, e.g., for clusterers; otherwise the class attribute index is set to last
- setNodeName(int, String) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
change the name of a node
- setNodesEdges(FastVector, FastVector) - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
Sets the nodes and edges for this LayoutEngine.
- setNodesEdges(FastVector, FastVector) - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
This method sets the nodes and edges vectors of the LayoutEngine
- setNodeSize(int, int) - 类中的方法 weka.gui.graphvisualizer.HierarchicalBCEngine
-
Sets the size of a node.
- setNodeSize(int, int) - 接口中的方法 weka.gui.graphvisualizer.LayoutEngine
-
This method sets the allowed size of the node
- setNodeSplitter(KDTreeNodeSplitter) - 类中的方法 weka.core.neighboursearch.KDTree
-
Sets the splitting method to use to split the nodes of the KDTree.
- setNodeWidthNormalization(boolean) - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Sets whether if a nodes region is normalized or not.
- setNoise(double) - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Set the level of Gaussian Noise.
- setNoisePercent(double) - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Sets the noise percentage.
- setNoiseRate(double) - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Sets the gaussian noise rate.
- setNoiseRate(double) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the percentage of noise set.
- setNoiseRate(double) - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Sets the percentage of noise set.
- setNoiseThreshold(double) - 类中的方法 weka.associations.Tertius
-
Set the value of noiseThreshold.
- setNoiseVariance(double) - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Sets the noise variance
- setNominalAttributes(String) - 类中的方法 weka.core.converters.CSVLoader
-
Sets the attribute range to be forced to type nominal.
- setNominalCols(Range) - 类中的方法 weka.datagenerators.ClusterGenerator
-
Sets which attributes are nominal.
- setNominalIndices(String) - 类中的方法 weka.datagenerators.ClusterGenerator
-
Sets which attributes are nominal
- setNominalIndices(String) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Set which nominal labels are to be included in the selection.
- setNominalIndicesArr(int[]) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Set which values of a nominal attribute are to be used for selection.
- setNominalLabels(String) - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Set the labels for nominal attribute creation.
- setNominalToBinaryFilter(boolean) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- setNoPruning(boolean) - 类中的方法 weka.classifiers.trees.REPTree
-
Set the value of NoPruning.
- setNoReplacement(boolean) - 类中的方法 weka.filters.supervised.instance.Resample
-
Sets whether instances are drawn with or with out replacement.
- setNoReplacement(boolean) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Sets whether instances are drawn with or with out replacement.
- setNorm(double) - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Set the norm of the instances
- setNormalize(boolean) - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Set whether input data will be normalized.
- setNormalize(boolean) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
whether to normalize input data
- setNormalize(boolean) - 类中的方法 weka.classifiers.functions.LibSVM
-
whether to normalize input data
- setNormalizeAttributes(boolean) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- setNormalizeData(boolean) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set whether to normalize the data or not
- setNormalizeDimWidths(boolean) - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Should we normalize the widths(ranges) of the dimensions (attributes) before selecting the widest one.
- setNormalizeDocLength(SelectedTag) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets whether if the word frequencies for a document (instance) should be normalized or not.
- setNormalizeNodeWidth(boolean) - 类中的方法 weka.core.neighboursearch.KDTree
-
Sets the flag for normalizing the widths of a KDTree Node by the width of the dimension in the universe.
- setNormalizeNumericClass(boolean) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- setNormalizeWordWeights(boolean) - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Sets whether if the word weights for each class should be normalized
- setNotCapabilities(Capabilities) - 类中的方法 weka.core.FindWithCapabilities
-
Uses the given "not to have" Capabilities for the search.
- setNotes(String) - 类中的方法 weka.experiment.Experiment
-
Set the user notes.
- setNotes(String) - 类中的方法 weka.experiment.RemoteExperiment
-
Set the user notes.
- setNotificationEnabled(boolean) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
sets whether the notification of changes is enabled
- setNotificationEnabled(boolean) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
sets whether the notification of changes is enabled
- setNotUnifyNorm(boolean) - 类中的方法 weka.clusterers.sIB
-
Set whether to normalize instances to unify prior probability before building the clusterer
- setNrOfGoodOperations(int) - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Sets the number of "good operations"
- setNrOfLookAheadSteps(int) - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Sets the number of look-ahead steps
- setNu(double) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)
- setNumAllConds(double) - 类中的方法 weka.classifiers.rules.RuleStats
-
Set the number of all conditions that could appear in a rule in this RuleStats object, if the number set is smaller than 0 (typically -1), then it calcualtes based on the data store
- setNumAntds(int) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Sets the number of antecedants
- setNumArcs(int) - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Sets the number of arcs for the bayesian net
- setNumAttemptsOfGeneOption(int) - 类中的方法 weka.classifiers.rules.NNge
-
Sets the number of attempts for generalisation.
- setNumAttributes(double) - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Set the number of attributes.
- setNumAttributes(int) - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Sets the number of attributes the dataset should have.
- setNumAttributes(int) - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Sets the number of attributes the dataset should have.
- setNumAttributes(int) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Sets the number of attributes the dataset should have.
- setNumAttributes(int) - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Sets the number of attributes the dataset should have.
- setNumAttributes(int) - 类中的方法 weka.datagenerators.ClusterGenerator
-
Sets the number of attributes the dataset should have.
- setNumberLiterals(int) - 类中的方法 weka.associations.Tertius
-
Set the value of numberLiterals.
- setNumberOfAttributes(int) - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Sets the number of attributes (dimensions) the data should be reduced to
- setNumberOfGroups(boolean) - 类中的方法 weka.classifiers.meta.RotationForest
-
Set whether minGroup and maxGroup refer to the number of groups or their size
- setNumBins(int) - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Sets the number of bins to divide each selected numeric attribute into
- setNumBoostingIterations(int) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Set the value of numBoostingIterations.
- setNumBoostingIterations(int) - 类中的方法 weka.classifiers.trees.FT
-
Set the value of numBoostingIterations.
- setNumBoostingIterations(int) - 类中的方法 weka.classifiers.trees.LMT
-
Set the value of numBoostingIterations.
- setNumCentroids(int) - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Sets the number of centroids to use.
- setNumCiters(int) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Sets the number of citers considered to estimate the class prediction of tests bags
- setNumClasses(int) - 类中的方法 weka.core.TestInstances
-
sets the number of classes
- setNumClasses(int) - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Sets the number of classes the dataset should have.
- setNumClasses(int) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Sets the number of classes the dataset should have.
- setNumClusters(int) - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Set the number of clusters for K-means to generate.
- setNumClusters(int) - 类中的方法 weka.clusterers.EM
-
Set the number of clusters (-1 to select by CV).
- setNumClusters(int) - 类中的方法 weka.clusterers.FarthestFirst
-
set the number of clusters to generate
- setNumClusters(int) - 类中的方法 weka.clusterers.HierarchicalClusterer
- setNumClusters(int) - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Set the number of clusters to generate.
- setNumClusters(int) - 接口中的方法 weka.clusterers.NumberOfClustersRequestable
-
Set the number of clusters to generate
- setNumClusters(int) - 类中的方法 weka.clusterers.sIB
-
Set the number of clusters
- setNumClusters(int) - 类中的方法 weka.clusterers.SimpleKMeans
-
set the number of clusters to generate
- setNumClusters(int) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the number of clusters the dataset should have.
- setNumComponents(int) - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
sets the maximum number of attributes to use.
- setNumCycles(int) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the the number of cycles.
- setNumDate(int) - 类中的方法 weka.core.CheckScheme
-
sets the number of data attributes
- setNumDate(int) - 类中的方法 weka.core.TestInstances
-
sets the number of date attributes
- setNumeric(boolean) - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Sets if the new Attribute is to be numeric.
- setNumExamples(int) - 类中的方法 weka.datagenerators.ClassificationGenerator
-
Sets the number of examples, given by option.
- setNumExamples(int) - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Sets the number of examples, given by option.
- setNumExamples(int) - 类中的方法 weka.datagenerators.RegressionGenerator
-
Sets the number of examples, given by option.
- setNumFeatures(int) - 类中的方法 weka.classifiers.trees.RandomForest
-
Set the number of features to use in random selection.
- setNumFoldersMIOption(int) - 类中的方法 weka.classifiers.rules.NNge
-
Sets the number of folder for mutual information.
- setNumFolds(int) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the number of folds to use for CV-based hyperparameter selection
- setNumFolds(int) - 类中的方法 weka.classifiers.functions.SMO
-
Set the value of numFolds.
- setNumFolds(int) - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Sets the number of folds for the cross-validation.
- setNumFolds(int) - 类中的方法 weka.classifiers.meta.Dagging
-
Sets the number of folds to use for splitting the training set.
- setNumFolds(int) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Set the value of NumFolds.
- setNumFolds(int) - 类中的方法 weka.classifiers.meta.MultiScheme
-
Sets the number of folds for cross-validation.
- setNumFolds(int) - 类中的方法 weka.classifiers.meta.Stacking
-
Sets the number of folds for the cross-validation.
- setNumFolds(int) - 类中的方法 weka.classifiers.mi.MISMO
-
Set the value of numFolds.
- setNumFolds(int) - 类中的方法 weka.classifiers.rules.PART
-
Set the value of numFolds.
- setNumFolds(int) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of numFolds.
- setNumFolds(int) - 类中的方法 weka.classifiers.trees.RandomTree
-
Set the value of NumFolds.
- setNumFolds(int) - 类中的方法 weka.classifiers.trees.REPTree
-
Set the value of NumFolds.
- setNumFolds(int) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Set the value of NumFolds.
- setNumFolds(int) - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Sets the number of folds the dataset is split into.
- setNumFolds(int) - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Sets the number of folds the dataset is split into.
- setNumFolds(int) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Sets the number of cross-validation folds to use - < 2 means no cross-validation.
- setNumFoldsPruning(int) - 类中的方法 weka.classifiers.trees.BFTree
-
Set number of folds in internal cross-validation.
- setNumFoldsPruning(int) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Set number of folds in internal cross-validation.
- setNumInstances(int) - 类中的方法 weka.core.CheckScheme
-
Sets the number of instances to use in the datasets (some classifiers might require more instances).
- setNumInstances(int) - 类中的方法 weka.core.TestInstances
-
sets the number of instances to produce
- setNumInstances(int) - 类中的方法 weka.estimators.CheckEstimator
-
Sets the number of instances to use in the datasets (some estimators might require more instances).
- setNumInstances(Random) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets the real number of instances for this cluster.
- setNumInstancesRelational(int) - 类中的方法 weka.core.CheckScheme
-
sets the number of instances in relational/bag attributes to produce
- setNumInstancesRelational(int) - 类中的方法 weka.core.TestInstances
-
sets the number of instances in relational/bag attributes to produce
- setNumIrrelevant(int) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Sets the number of irrelevant attributes.
- setNumIterations(int) - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Sets the number of iterations to be performed
- setNumIterations(int) - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Set the value of NumIterations.
- setNumIterations(int) - 类中的方法 weka.classifiers.functions.Winnow
-
Set the value of numIterations.
- setNumIterations(int) - 类中的方法 weka.classifiers.IteratedSingleClassifierEnhancer
-
Sets the number of bagging iterations
- setNumIterations(int) - 类中的方法 weka.classifiers.meta.MetaCost
-
Sets the number of bagging iterations
- setNumNeighbours(int) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Set the number of nearest neighbours
- setNumNeighbours(int) - 类中的方法 weka.classifiers.mi.MINND
-
Sets the number of nearest neighbours to estimate the class prediction of tests bags
- setNumNominal(int) - 类中的方法 weka.core.CheckScheme
-
sets the number of nominal attributes
- setNumNominal(int) - 类中的方法 weka.core.TestInstances
-
sets the number of nominal attributes
- setNumNominalValues(int) - 类中的方法 weka.core.TestInstances
-
sets the number of values for nominal attributes
- setNumNumeric(int) - 类中的方法 weka.core.CheckScheme
-
sets the number of numeric attributes
- setNumNumeric(int) - 类中的方法 weka.core.TestInstances
-
sets the number of numeric attributes
- setNumNumeric(int) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Sets the number of numerical attributes.
- setNumOfBoostingIterations(int) - 类中的方法 weka.classifiers.trees.ADTree
-
Sets the number of boosting iterations.
- setNumOfBoostingIterations(int) - 类中的方法 weka.classifiers.trees.LADTree
-
Sets the number of boosting iterations.
- setNumReferences(int) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Sets the number of references considered to estimate the class prediction of tests bags
- setNumRelational(int) - 类中的方法 weka.core.CheckScheme
-
sets the number of relational attributes
- setNumRelational(int) - 类中的方法 weka.core.TestInstances
-
sets the number of relational attributes
- setNumRelationalDate(int) - 类中的方法 weka.core.TestInstances
-
sets the number of date attributes in a relational attribute
- setNumRelationalNominal(int) - 类中的方法 weka.core.TestInstances
-
sets the number of nominal attributes in a relational attribute
- setNumRelationalNominalValues(int) - 类中的方法 weka.core.TestInstances
-
sets the number of values for nominal attributes in a relational attribute
- setNumRelationalNumeric(int) - 类中的方法 weka.core.TestInstances
-
sets the number of numeric attributes in a relational attribute
- setNumRelationalString(int) - 类中的方法 weka.core.TestInstances
-
sets the number of string attributes in a relational attribute
- setNumRestarts(int) - 类中的方法 weka.clusterers.sIB
-
Set the number of restarts
- setNumRules(int) - 类中的方法 weka.associations.Apriori
-
Set the value of numRules.
- setNumRules(int) - 类中的方法 weka.associations.PredictiveApriori
-
Set the value of required rules.
- setNumRulesToFind(int) - 类中的方法 weka.associations.FPGrowth
-
Set the desired number of rules to find.
- setNumRuns(int) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Set the value of NumRuns.
- setNumSamplesPerRegion(int) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set the number of points to uniformly sample from a region (fixed dimensions).
- setNumSamplesPerRegion(int) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the number of points to uniformly sample from a region (fixed dimensions).
- setNumString(int) - 类中的方法 weka.core.CheckScheme
-
sets the number of string attributes
- setNumString(int) - 类中的方法 weka.core.TestInstances
-
sets the number of string attributes
- setNumSubCmtys(int) - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Set the number of sub committees to use
- setNumSubsetSizeCVFolds(int) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Set the number of cross validation folds for subset size determination (default = 5).
- setNumTestingNoises(int) - 类中的方法 weka.classifiers.mi.MINND
-
Sets The number of nearest neighbour exemplars in the selection of noises in the test data
- setNumToSelect(int) - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Specify the number of attributes to select from the ranked list (if generating a ranking).
- setNumToSelect(int) - 类中的方法 weka.attributeSelection.RaceSearch
-
Specify the number of attributes to select from the ranked list (if generating a ranking).
- setNumToSelect(int) - 接口中的方法 weka.attributeSelection.RankedOutputSearch
-
Specify the number of attributes to select from the ranked list.
- setNumToSelect(int) - 类中的方法 weka.attributeSelection.Ranker
-
Specify the number of attributes to select from the ranked list.
- setNumTrainingNoises(int) - 类中的方法 weka.classifiers.mi.MINND
-
Sets the number of nearest neighbour instances in the selection of noises in the training data
- setNumTrees(int) - 类中的方法 weka.classifiers.trees.RandomForest
-
Set the value of numTrees.
- setNumUsedAttributes(int) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Set the number of top-ranked attributes that taken into account by the search process.
- setNumUsedAttributes(int) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Set the number of top-ranked attributes that taken into account by the search process.
- setNumValues(int) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Sets how many values are retained
- setNumXValFolds(int) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Set the number of folds used for cross-validation.
- setObject(Object) - 类中的方法 weka.core.CheckGOE
-
Set the object to work on..
- setObject(Object) - 类中的方法 weka.gui.beans.AssociatorCustomizer
-
Set the classifier object to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.ClassAssignerCustomizer
-
Set the bean to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.ClassifierCustomizer
-
Set the classifier object to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.ClassValuePickerCustomizer
-
Set the bean to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.ClustererCustomizer
-
Set the Clusterer object to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.CrossValidationFoldMakerCustomizer
-
Set the object to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.FilterCustomizer
-
Set the filter bean to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
-
Set the object to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.LoaderCustomizer
-
Set the loader to be customized
- setObject(Object) - 类中的方法 weka.gui.beans.PredictionAppenderCustomizer
-
Set the object to be edited
- setObject(Object) - 类中的方法 weka.gui.beans.SaverCustomizer
-
Set the saver to be customized
- setObject(Object) - 类中的方法 weka.gui.beans.SerializedModelSaverCustomizer
-
Set the model saver to be customized
- setObject(Object) - 类中的方法 weka.gui.beans.StripChartCustomizer
-
Set the StripChart object to be customized
- setObject(Object) - 类中的方法 weka.gui.beans.TrainTestSplitMakerCustomizer
-
Set the TrainTestSplitMaker to be customized
- setOfSequencesToString(FastVector, Instances, FastVector) - 类中的静态方法 weka.associations.gsp.Sequence
-
Returns a String representation of a set of Sequences where the numeric value of each event/item is represented by its respective nominal value.
- setOkButtonText(String) - 类中的方法 weka.gui.GenericObjectEditor.GOEPanel
-
Allows customization of the action label on the dialog.
- setOmega(double) - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Sets the omega value.
- setOn(boolean) - 类中的方法 weka.gui.visualize.ClassPanel
-
Enables the panel
- setOnDemandDirectory(File) - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Sets the directory that will be searched for cost files when loading on demand.
- setOnDemandDirectory(File) - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Sets the directory that will be searched for cost files when loading on demand.
- setOnDemandDirectory(File) - 类中的方法 weka.classifiers.meta.MetaCost
-
Sets the directory that will be searched for cost files when loading on demand.
- setOnDemandDirectory(File) - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Sets the directory that will be searched for cost files when loading on demand.
- setOptimalColumnWidth() - 类中的方法 weka.gui.JTableHelper
-
sets the optimal column width for all columns
- setOptimalColumnWidth(int) - 类中的方法 weka.gui.JTableHelper
-
sets the optimal column width for the given column
- setOptimalColumnWidth(JTable) - 类中的静态方法 weka.gui.JTableHelper
-
sets the optimal column width for alls column if the given table
- setOptimalColumnWidth(JTable, int) - 类中的静态方法 weka.gui.JTableHelper
-
sets the optimal column width for the given column
- setOptimalColWidth() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
calculates the optimal column width for the current column
- setOptimalColWidths() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
calculates the optimal column widths for all columns
- setOptimalColWidths() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
sets the optimal column width for all columns
- setOptimalHeaderWidth() - 类中的方法 weka.gui.JTableHelper
-
sets the optimal header width for all columns
- setOptimalHeaderWidth(int) - 类中的方法 weka.gui.JTableHelper
-
sets the optimal header width for the given column
- setOptimalHeaderWidth(JTable) - 类中的静态方法 weka.gui.JTableHelper
-
sets the optimal header width for alls column if the given table
- setOptimalHeaderWidth(JTable, int) - 类中的静态方法 weka.gui.JTableHelper
-
sets the optimal header width for the given column
- setOptimizations(int) - 类中的方法 weka.classifiers.rules.JRip
-
Sets the number of optimization runs
- setOptionHandler(OptionHandler) - 类中的方法 weka.core.CheckOptionHandler
-
Set the OptionHandler to work on..
- setOptions(int, int, int) - 类中的方法 weka.classifiers.lazy.kstar.KStarNominalAttribute
-
Sets the options.
- setOptions(int, int, int) - 类中的方法 weka.classifiers.lazy.kstar.KStarNumericAttribute
-
Set options.
- setOptions(String[]) - 类中的方法 weka.associations.Apriori
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.associations.CheckAssociator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.associations.FilteredAssociator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.associations.FPGrowth
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.associations.PredictiveApriori
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.associations.SingleAssociatorEnhancer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.associations.Tertius
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.BestFirst
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
Parses and sets a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.GeneticSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.RaceSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.RandomSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.Ranker
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.RankSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.AODE
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.DMNBtext
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.fixed.FromFile
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.global.TAN
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.LAGDHillClimber
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.local.TAN
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.net.search.SearchAlgorithm
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.bayes.WAODE
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.BVDecompose
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.classifiers.CheckClassifier
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.CheckSource
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.Classifier
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Sets the classifier options
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets the classifier options
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.LinearRegression
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.Logistic
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.PaceRegression
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.PLSClassifier
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.SMO
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.SMOreg
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.SPegasos
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.CachedKernel
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.CheckKernel
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.Kernel
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.RegSMO
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.functions.Winnow
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.IteratedSingleClassifierEnhancer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.lazy.IBk
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.lazy.KStar
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.lazy.LWL
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.Bagging
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.Dagging
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.Decorate
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.GridSearch
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.MetaCost
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.MultiScheme
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.RotationForest
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.Stacking
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.meta.Vote
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MDD
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MIBoost
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MIDD
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MIEMDD
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MILR
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MINND
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MISMO
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MISVM
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.MIWrapper
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.mi.SimpleMI
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.classifiers.misc.VFI
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.MultipleClassifiersCombiner
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.RandomizableClassifier
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.RandomizableMultipleClassifiersCombiner
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.RandomizableSingleClassifierEnhancer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.classifiers.rules.DTNB
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.classifiers.rules.JRip
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.rules.NNge
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.classifiers.rules.OneR
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.rules.PART
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.rules.Ridor
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.SingleClassifierEnhancer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.ADTree
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.BFTree
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.FT
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.J48
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.J48graft
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.LADTree
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.LMT
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.M5P
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.RandomForest
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.RandomTree
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.REPTree
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.CheckClusterer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.CLOPE
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.Cobweb
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.DBSCAN
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.clusterers.EM
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.FarthestFirst
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.FilteredClusterer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.HierarchicalClusterer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.OPTICS
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.clusterers.RandomizableClusterer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.RandomizableDensityBasedClusterer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.RandomizableSingleClustererEnhancer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.sIB
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.SimpleKMeans
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.SingleClustererEnhancer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.clusterers.XMeans
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.Check
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.CheckGOE
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.CheckOptionHandler
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.CheckScheme
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.converters.ArffSaver
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.core.converters.C45Saver
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.converters.CSVLoader
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets the options.
- setOptions(String[]) - 类中的方法 weka.core.converters.DatabaseSaver
-
Sets the options.
- setOptions(String[]) - 类中的方法 weka.core.converters.LibSVMSaver
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.core.converters.SVMLightSaver
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.converters.XRFFSaver
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.core.FindWithCapabilities
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.Javadoc
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.ListOptions
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.BallTree
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.balltrees.BallSplitter
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.balltrees.BallTreeConstructor
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.KDTree
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.NormalizableDistance
-
Parses a given list of options.
- setOptions(String[]) - 接口中的方法 weka.core.OptionHandler
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.core.OptionHandlerJavadoc
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.stemmers.SnowballStemmer
-
Parses the options.
- setOptions(String[]) - 类中的方法 weka.core.TechnicalInformationHandlerJavadoc
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.TestInstances
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.tokenizers.CharacterDelimitedTokenizer
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.core.tokenizers.Tokenizer
-
Sets the OptionHandler's options using the given list.
- setOptions(String[]) - 类中的方法 weka.datagenerators.ClassificationGenerator
-
Sets the options.
- setOptions(String[]) - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.classifiers.classification.LED24
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.classifiers.classification.RandomRBF
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.classifiers.regression.Expression
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.classifiers.regression.MexicanHat
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.ClusterDefinition
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.clusterers.SubspaceCluster
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.ClusterGenerator
-
Sets the options.
- setOptions(String[]) - 类中的方法 weka.datagenerators.DataGenerator
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.datagenerators.RegressionGenerator
-
Sets the options.
- setOptions(String[]) - 类中的方法 weka.estimators.CheckEstimator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.estimators.Estimator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.AveragingResultProducer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.CSVResultListener
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.Experiment
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.InstanceQuery
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.PairedTTester
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.CheckSource
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.MultiFilter
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.SimpleFilter
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.instance.Resample
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.AbstractTimeSeries
-
Parses a given list of options controlling the behaviour of this object.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.Add
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.AddCluster
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.AddExpression
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.AddID
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.ChangeDateFormat
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.ClassAssigner
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.ClusterMembership
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.Copy
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.FirstOrder
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.MathExpression
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.NominalToString
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.NumericCleaner
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.NumericToNominal
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.NumericTransform
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.PotentialClassIgnorer
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Parses a list of options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.Remove
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.RemoveType
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.RemoveUseless
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.Reorder
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.StringToNominal
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Parses the options for this object.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.Normalize
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.RemoveRange
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.filters.unsupervised.instance.SubsetByExpression
-
Parses a given list of options.
- setOptions(String[]) - 类中的方法 weka.gui.Main
-
Parses the options for this object.
- setOriginalCoords(Vector) - 类中的方法 weka.gui.beans.MetaBean
-
sets the vector containing the original coordinates (instances of class Point) for the inputs
- setOutlierFactor(double) - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Sets the factor for determining the thresholds for outliers.
- setOutput(PrintWriter) - 类中的方法 weka.datagenerators.DataGenerator
-
Sets the print writer.
- setOutputCenterFile(File) - 类中的方法 weka.clusterers.XMeans
-
Sets file to write the list of centers to.
- setOutputClassification(boolean) - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Set whether the classification of the classifier is output.
- setOutputDistribution(boolean) - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Set whether the Distribution of the classifier is output.
- setOutputErrorFlag(boolean) - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Set whether the classification of the classifier is output.
- setOutputFile(File) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Set the value of OutputFile.
- setOutputFile(File) - 类中的方法 weka.experiment.CSVResultListener
-
Set the value of OutputFile.
- setOutputFile(File) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Set the value of OutputFile.
- setOutputFilename(boolean) - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Sets whether the filename will be stored as an extra attribute.
- setOutputFilename(String) - 类中的方法 weka.gui.GenericPropertiesCreator
-
sets the file to output the properties for the GEO to
- setOutputFileName(String) - 类中的方法 weka.experiment.CSVResultListener
-
Set the value of OutputFileName.
- setOutputFormat(int) - 类中的方法 weka.core.Debug.Clock
-
sets the format of the output
- setOutputFormatFromDialog() - 类中的方法 weka.gui.experiment.ResultsPanel
-
displays the Dialog for the output format and sets the chosen settings, if the user approves.
- setOutputItemSets(boolean) - 类中的方法 weka.associations.Apriori
-
Sets whether itemsets are output as well
- setOutputOffsetMultiplier(boolean) - 类中的方法 weka.filters.unsupervised.attribute.InterquartileRange
-
Set whether an additional attribute "Offset" is generated per Outlier/ExtremeValue attribute pair that lists the multiplier the value is off the median: value = median + 'multiplier' * IQR.
- setOutputPerClassInfoRetrievalStats(boolean) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Set whether to output per-class information retrieval statistics (nominal class only).
- setOutputs(Vector) - 类中的方法 weka.gui.beans.MetaBean
- setOutputTypes(String) - 类中的方法 weka.core.Debug.DBO
-
Switches the outputs on that are requested from the option O
- setOutputWordCounts(boolean) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets whether output instances contain 0 or 1 indicating word presence, or word counts.
- setOverwriteWarning(boolean) - 类中的方法 weka.gui.ConverterFileChooser
-
Whether a warning is popped up if the file that is to be saved already exists (only save dialog).
- setOwner(CapabilitiesHandler) - 类中的方法 weka.core.Capabilities
-
sets the owner of this capabilities object
- setP(double) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Set the proportion of instances that are common between two training sets used to train a classifier.
- setPadding(SelectedTag) - 类中的方法 weka.filters.unsupervised.attribute.Wavelet
-
Sets the type of Padding to use
- setPaint(Paint) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- setPaintMode() - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- setPanelHeight(int) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the height of the visualization
- setPanelWidth(int) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the width of the visualization
- setParameterDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.BuiltInArithmetic
-
Set the structure of the parameters that are expected as input by this function.
- setParameterDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.BuiltInMath
-
Set the structure of the parameters that are expected as input by this function.
- setParameterDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.BuiltInString
-
Set the structure of the parameters that are expected as input by this function.
- setParameterDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.DefineFunction
-
Set the structure of the parameters that are expected as input by this function.
- setParameterDefs(ArrayList<Attribute>) - 类中的方法 weka.core.pmml.Function
-
Set the structure of the parameters that are expected as input by this function.
- setParent(Container) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
sets the new parent frame
- setParent(SubspaceCluster) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
sets the parent datagenerator this cluster belongs to
- setParent(ClusterGenerator) - 类中的方法 weka.datagenerators.ClusterDefinition
-
sets the parent datagenerator this cluster belongs to
- setParent(Edge) - 类中的方法 weka.gui.treevisualizer.Node
-
Set the value of parent.
- SetParent(int, int) - 类中的方法 weka.classifiers.bayes.net.ParentSet
-
sets index parent of parent specified by index
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.AssociatorCustomizer
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.ClassAssignerCustomizer
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.ClassifierCustomizer
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.ClassValuePickerCustomizer
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.ClustererCustomizer
- setParentFrame(JFrame) - 接口中的方法 weka.gui.beans.CustomizerCloseRequester
-
A reference to the parent is passed in
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.FilterCustomizer
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.LoaderCustomizer
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.SaverCustomizer
- setParentFrame(JFrame) - 类中的方法 weka.gui.beans.SerializedModelSaverCustomizer
- setParentFrame(JFrame) - 类中的方法 weka.gui.SetInstancesPanel
-
Sets the frame, this panel resides in.
- setParentSeparator(MarginCalculator.JunctionTreeSeparator) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
- setPassword(String) - 接口中的方法 weka.core.converters.DatabaseConverter
- setPassword(String) - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets user password for the database
- setPassword(String) - 类中的方法 weka.core.converters.DatabaseSaver
-
Sets the database password.
- setPassword(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Set the database password.
- setPassword(String) - 类中的方法 weka.gui.sql.ConnectionPanel
-
sets the Password.
- setPattern(SelectedTag) - 类中的方法 weka.datagenerators.clusterers.BIRCHCluster
-
Sets the pattern type.
- setPercent() - 类中的方法 weka.gui.visualize.MatrixPanel
-
Calculates the percentage to resample
- setPercent(double) - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Sets the percent the attributes (dimensions) of the data should be reduced to
- setPercent(int) - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Sets the size of noise data, as a percentage of the original set.
- setPercentage(double) - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Sets the percentage of SMOTE instances to create.
- setPercentage(double) - 类中的方法 weka.filters.unsupervised.instance.RemovePercentage
-
Sets the percentage of intances to select.
- setPercentCompleted(int) - 类中的方法 weka.gui.boundaryvisualizer.RemoteResult
-
Set the progress for this row so far
- setPercentThreshold(int) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Set the threshold below which percentage elimination reverts to constant elimination.
- setPercentToEliminatePerIteration(int) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Set the percentage of attributes to eliminate per iteration
- setPerformPrediction(boolean) - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Sets whether to update the class attribute with the predicted value.
- setPerformRanking(boolean) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Perform initial ranking to select top-ranked attributes.
- setPerformRanking(boolean) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Perform initial ranking to select top-ranked attributes.
- setPeriodicPruning(double) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.
- setPerturbationFraction(double) - 类中的方法 weka.datagenerators.classifiers.classification.Agrawal
-
Sets the perturbation fraction.
- setPivot(Instance) - 类中的方法 weka.core.neighboursearch.balltrees.BallNode
-
Sets the pivot/centre of this nodes ball.
- setPixHeight(double) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the height of a pixel
- setPixWidth(double) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the width of a pixel
- setPlotCompanion(Plot2DCompanion) - 类中的方法 weka.gui.visualize.Plot2D
-
Set a companion class.
- setPlotList(FastVector) - 类中的方法 weka.gui.visualize.LegendPanel
-
Set the list of plots to generate legend entries for
- setPlotName(String) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the name of this plot
- setPlotNameHTML(String) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the plot name for use in a tool tip text.
- setPlotTrainingData(boolean) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set whether to superimpose the training data plot
- setPlus(int, double) - 类中的方法 weka.core.matrix.DoubleVector
-
Adds a value to an element
- setPlus(int, int, double) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Add a value to an element and reset the element
- setPMMLVersion(Document) - 类中的方法 weka.classifiers.pmml.consumer.PMMLClassifier
-
Set the version of PMML used for this model.
- setPMMLVersion(Document) - 接口中的方法 weka.core.pmml.PMMLModel
-
Set the version of the PMML.
- setPoints(MiddleOutConstructor.TempNode, int, int, int[]) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Sets the points of an anchor node.
- setPointValue(int, double) - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Sets a particular point value
- setPopulationSize(int) - 类中的方法 weka.attributeSelection.GeneticSearch
-
set the population size
- setPopulationSize(int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Set the population size
- setPopulationSize(int) - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- setPopulationSize(int) - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- setPopup(JPopupMenu) - 类中的方法 weka.gui.GenericObjectEditor.CapabilitiesFilterDialog
-
sets the JPopupMenu to display again after closing the dialog.
- setPosition(int, int, int) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
set position of node
- setPosition(int, int, int, FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
Set position of node.
- setPositiveIndex(int) - 类中的方法 weka.associations.FPGrowth
-
Set the index of the attribute value to consider as positive for binary attributes in normal dense instances.
- setPostProcessor(CheckScheme.PostProcessor) - 类中的方法 weka.core.CheckScheme
-
sets the PostProcessor to use
- setPostProcessor(CheckEstimator.PostProcessor) - 类中的方法 weka.estimators.CheckEstimator
-
sets the PostProcessor to use
- setPredTargetColumn(boolean) - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Set the flag for prediction and target output.
- setPreferredScrollableViewportSize(Dimension) - 类中的方法 weka.gui.AttributeSelectionPanel
- setPrefix(String) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Set the prefix to prepend to the model file names.
- setPreprocessing(SelectedTag) - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Sets the type of preprocessing to use
- setPreprocessing(Filter) - 类中的方法 weka.filters.unsupervised.attribute.KernelFilter
-
Sets the filter to use for preprocessing (use the AllFilter for no preprocessing)
- setPreserveInstancesOrder(boolean) - 类中的方法 weka.clusterers.SimpleKMeans
-
Sets whether order of instances must be preserved
- setPrintColNames(boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets whether the column names or numbers instead are printed.
- setPrintNewick(boolean) - 类中的方法 weka.clusterers.HierarchicalClusterer
- setPrintRowNames(boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets whether the row names or numbers instead are printed deactivating automatically sets m_EnumerateColNames to TRUE.
- setPriorClass(SelectedTag) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the type of prior to use.
- setPriors(Instances) - 类中的方法 weka.classifiers.Evaluation
-
Sets the class prior probabilities
- setProbabilityEstimates(boolean) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns whether probability estimates are generated instead of -1/+1 for classification problems.
- setProbabilityEstimates(boolean) - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns whether probability estimates are generated instead of -1/+1 for classification problems.
- setProcessed(boolean) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Marks this dataObject as processed
- setProcessed(boolean) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Marks this dataObject as processed
- setProcessed(boolean) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Marks this dataObject as processed
- setProjectionFilter(Filter) - 类中的方法 weka.classifiers.meta.RotationForest
-
Sets the filter used to project the data.
- setProlog(boolean) - 类中的方法 weka.core.OptionHandlerJavadoc
-
sets whether to add the "Valid options are..." prolog
- setProlog(boolean) - 类中的方法 weka.core.TechnicalInformationHandlerJavadoc
-
sets whether to add the "Valid options are..." prolog
- setProperty(String, String) - 类中的方法 weka.core.ProtectedProperties
-
Overrides a method to prevent the properties from being modified.
- setPropertyArray(Object) - 类中的方法 weka.experiment.Experiment
-
Sets the array of values to set the custom property to.
- setPropertyArray(Object) - 类中的方法 weka.experiment.RemoteExperiment
-
Sets the array of values to set the custom property to.
- setPropertyPath(PropertyNode[]) - 类中的方法 weka.experiment.Experiment
-
Sets the path of properties taken to get to the custom property to iterate over.
- setPropertyPath(PropertyNode[]) - 类中的方法 weka.experiment.RemoteExperiment
-
Sets the path of properties taken to get to the custom property to iterate over.
- setPruningMethod(SelectedTag) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Sets the method used to for pruning.
- setPruningStrategy(SelectedTag) - 类中的方法 weka.classifiers.trees.BFTree
-
Sets the pruning strategy.
- setPruningType(SelectedTag) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Set the pruning type
- setQuality(float) - 类中的方法 weka.gui.visualize.JPEGWriter
-
sets the quality the JPEG is saved in.
- setQuery(String) - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets the query to execute against the database
- setQuery(String) - 类中的方法 weka.experiment.InstanceQuery
-
Set the query to execute against the database
- setQuery(String) - 类中的方法 weka.gui.sql.QueryPanel
-
sets the query in the textarea.
- setQueryPanel(QueryPanel) - 类中的方法 weka.gui.sql.ResultPanel
-
sets the QueryPanel to use for displaying the query
- setRaceType(SelectedTag) - 类中的方法 weka.attributeSelection.RaceSearch
-
Set the race type
- setRadius(double) - 类中的方法 weka.core.neighboursearch.balltrees.BallNode
-
Sets the radius of the node's ball.
- setRandom(Random) - 类中的方法 weka.datagenerators.DataGenerator
-
Sets the random generator.
- setRandomize(boolean) - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Sets whether the order of the generated data is randomized
- setRandomizeData(boolean) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Set to true if dataset is to be randomized
- setRandomOrder(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.K2
-
Set random order flag
- setRandomOrder(boolean) - 类中的方法 weka.classifiers.bayes.net.search.local.K2
-
Set random order flag
- setRandomSeed(int) - 类中的方法 weka.classifiers.functions.SMO
-
Set the value of randomSeed.
- setRandomSeed(int) - 类中的方法 weka.classifiers.mi.MISMO
-
Set the value of randomSeed.
- setRandomSeed(int) - 类中的方法 weka.classifiers.trees.ADTree
-
Sets random seed for a random walk.
- setRandomSeed(int) - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Sets the seed for random number generator.
- setRandomSeed(int) - 类中的方法 weka.filters.supervised.instance.Resample
-
Sets the random number seed.
- setRandomSeed(int) - 类中的方法 weka.filters.supervised.instance.SMOTE
-
Sets the random number seed.
- setRandomSeed(int) - 类中的方法 weka.filters.supervised.instance.SpreadSubsample
-
Sets the random number seed.
- setRandomSeed(int) - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Sets the random number seed.
- setRandomSeed(int) - 类中的方法 weka.filters.unsupervised.instance.Randomize
-
Set the random number generator seed value.
- setRandomSeed(int) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Sets the random number seed.
- setRandomSeed(int) - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Sets the random number seed.
- setRandomSeed(long) - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Set the seed for the random number generator
- setRandomSeed(long) - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Sets the random seed of the random number generator
- setRandomWidthFactor(double) - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Sets the multiplier when generating random codes.
- setRangeCorrection(SelectedTag) - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Sets the confidence range correction mode used.
- setRanges(String) - 类中的方法 weka.core.Range
-
Sets the ranges from a string representation.
- setRanges(Range[]) - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Sets the list of possible Ranges to choose from.
- setRank(double) - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Sets the desired matrix rank (or coverage proportion) for feature-space reduction
- setRanking(boolean) - 类中的方法 weka.attributeSelection.AttributeSelection
-
produce a ranking (if possible with the set search and evaluator)
- setRanking(int[][]) - 类中的方法 weka.experiment.ResultMatrix
-
sets the ranking data based on the wins
- setRawOutput(boolean) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Set to true if raw split evaluator output is to be saved
- setRawOutput(boolean) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Set to true if raw split evaluator output is to be saved
- setReachabilityDistance(double) - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
-
Sets a new reachability-distance for this dataObject
- setReachabilityDistance(double) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
-
Sets a new reachability-distance for this dataObject
- setReachabilityDistance(double) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
-
Sets a new reachability-distance for this dataObject
- setReachabilityDistanceColor(Color) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Sets a new color for the reachabilityDistance
- setReadable(String) - 类中的方法 weka.core.Tag
-
Sets the string description of the Tag.
- setReadIncrementally(boolean) - 类中的方法 weka.gui.SetInstancesPanel
-
Sets whether or not instances should be read incrementally by the Loader.
- setReadOnly(boolean) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
sets whether the model is read-only
- setReadOnly(boolean) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
sets whether the model is read-only
- setReadOnly(boolean) - 类中的方法 weka.gui.arffviewer.ArffTable
-
sets whether the model is read-only
- setReadOnly(boolean) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
sets whether the model is read-only
- setReducedErrorPruning(boolean) - 类中的方法 weka.classifiers.rules.PART
-
Set the value of reducedErrorPruning.
- setReducedErrorPruning(boolean) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of reducedErrorPruning.
- setRefer(String) - 类中的方法 weka.gui.treevisualizer.Node
-
Set the value of refer.
- setRefreshFreq(int) - 类中的方法 weka.gui.beans.StripChart
-
Set how often (in x axis points) to refresh the display
- setRegOptimizer(RegOptimizer) - 类中的方法 weka.classifiers.functions.SMOreg
-
sets the learning algorithm
- setRegressionTree(boolean) - 类中的方法 weka.classifiers.trees.m5.Rule
-
Set the value of regressionTree.
- setRegressionTree(boolean) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Set the value of regressionTree.
- setRelabel(boolean) - 类中的方法 weka.classifiers.trees.J48graft
-
Set the value of relabelling.
- setRelation(String) - 类中的方法 weka.core.TestInstances
-
sets the name of the relation
- setRelationalClassFormat(Instances) - 类中的方法 weka.core.TestInstances
-
sets the structure for the relational class attribute
- setRelationalFormat(int, Instances) - 类中的方法 weka.core.TestInstances
-
sets the structure for the bags for the relational attribute
- setRelationForTableName(boolean) - 类中的方法 weka.core.converters.DatabaseSaver
-
En/Dis-ables that the relation name is used for the name of the table (default enabled).
- setRelationName(String) - 类中的方法 weka.core.Instances
-
Sets the relation's name.
- setRelationName(String) - 类中的方法 weka.datagenerators.DataGenerator
-
Sets the relation name the dataset should have.
- setRelationNameForFilename(boolean) - 类中的方法 weka.gui.beans.Saver
-
Set whether to use the relation name as the primary part of the filename.
- setRemoteHosts(Vector) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanelDistributed
-
Set a list of host names of machines to distribute processing to
- setRemoteHosts(DefaultListModel) - 类中的方法 weka.experiment.RemoteExperiment
-
Set the list of remote host names
- setRemoveAllMissingCols(boolean) - 类中的方法 weka.associations.Apriori
-
Remove columns containing all missing values.
- setRemoveClassColumn(boolean) - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Set whether the class column should be removed from the data.
- setRemovedPercentage(int) - 类中的方法 weka.classifiers.meta.RotationForest
-
Sets the percentage of instance to be removed
- setRemoveFilterName(boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets whether to remove the filter classname from the dataset name
- setRemoveFilterName(boolean) - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
sets whether to remove the filter classname from the dataset name.
- setRemoveOldClass(boolean) - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Set whether the old class attribute is removed.
- setRemoveUnused(boolean) - 类中的方法 weka.filters.unsupervised.attribute.PartitionedMultiFilter
-
Sets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.
- setRenderingHint(RenderingHints.Key, Object) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- setRenderingHints(Map) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- setRepeatLiterals(boolean) - 类中的方法 weka.associations.Tertius
-
Set the value of repeatLiterals.
- setReplaceMissing(boolean) - 类中的方法 weka.filters.supervised.attribute.PLSFilter
-
Sets whether to replace missing values.
- setReplaceMissingValues(boolean) - 类中的方法 weka.filters.unsupervised.attribute.RandomProjection
-
Sets either to use replace missing values filter or not
- setReportFrequency(int) - 类中的方法 weka.attributeSelection.GeneticSearch
-
set how often reports are generated
- setRepulsion(double) - 类中的方法 weka.clusterers.CLOPE
-
set the repulsion
- setReset(boolean) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
This sets the network up to be able to reset itself with the current settings and the learning rate at half of what it is currently.
- setReset(boolean) - 类中的方法 weka.gui.beans.ChartEvent
-
Set the reset flag
- setResult(Boolean) - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Sets the result of the evaluation.
- setResult(Double) - 类中的方法 weka.core.mathematicalexpression.Parser
-
Sets the result of the evaluation.
- setResultKeyFromDialog() - 类中的方法 weka.gui.experiment.ResultsPanel
- setResultListener(ResultListener) - 类中的方法 weka.experiment.AveragingResultProducer
-
Sets the object to send results of each run to.
- setResultListener(ResultListener) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Sets the object to send results of each run to.
- setResultListener(ResultListener) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Sets the object to send results of each run to.
- setResultListener(ResultListener) - 类中的方法 weka.experiment.Experiment
-
Sets the result listener where results will be sent.
- setResultListener(ResultListener) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Sets the object to send results of each run to.
- setResultListener(ResultListener) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Sets the object to send results of each run to.
- setResultListener(ResultListener) - 类中的方法 weka.experiment.RemoteExperiment
-
Sets the result listener where results will be sent.
- setResultListener(ResultListener) - 接口中的方法 weka.experiment.ResultProducer
-
Sets the object to send results of each run to.
- setResultMatrix(Class) - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
Sets the matrix to use as initial selected output format.
- setResultMatrix(ResultMatrix) - 类中的方法 weka.experiment.PairedTTester
-
Sets the matrix to use to produce the output.
- setResultMatrix(ResultMatrix) - 接口中的方法 weka.experiment.Tester
-
Sets the matrix to use to produce the output.
- setResultProducer(ResultProducer) - 类中的方法 weka.experiment.AveragingResultProducer
-
Set the ResultProducer.
- setResultProducer(ResultProducer) - 类中的方法 weka.experiment.DatabaseResultProducer
-
Set the ResultProducer.
- setResultProducer(ResultProducer) - 类中的方法 weka.experiment.Experiment
-
Set the result producer used for the current experiment.
- setResultProducer(ResultProducer) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Set the ResultProducer.
- setResultProducer(ResultProducer) - 类中的方法 weka.experiment.RemoteExperiment
-
Set the result producer used for the current experiment.
- setResultsetKeyColumns(Range) - 类中的方法 weka.experiment.PairedTTester
-
Set the value of ResultsetKeyColumns.
- setResultsetKeyColumns(Range) - 接口中的方法 weka.experiment.Tester
-
Set the value of ResultsetKeyColumns.
- setResultsPanel(ResultsPanel) - 类中的方法 weka.gui.experiment.RunPanel
-
Sets the pointer to the results panel.
- setResultVector(FastVector) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Sets a new resultVector
- setRetrieval(int) - 类中的方法 weka.core.converters.AbstractLoader
-
Sets the retrieval mode.
- setRetrieval(int) - 类中的方法 weka.core.converters.AbstractSaver
-
Sets the retrieval mode.
- setRetrieval(int) - 接口中的方法 weka.core.converters.Loader
-
Sets the retrieval mode.
- setRetrieval(int) - 接口中的方法 weka.core.converters.Saver
-
Sets the retrieval mode
- setRidge(double) - 类中的方法 weka.classifiers.functions.LinearRegression
-
Set the value of Ridge.
- setRidge(double) - 类中的方法 weka.classifiers.functions.Logistic
-
Sets the ridge in the log-likelihood.
- setRidge(double) - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Sets the ridge value for logistic or linear regression.
- setRidge(double) - 类中的方法 weka.classifiers.mi.MILR
-
Sets the ridge in the log-likelihood.
- setRocAnalysis(boolean) - 类中的方法 weka.associations.Tertius
-
Set the value of rocAnalysis.
- setROCString(String) - 类中的方法 weka.gui.visualize.ThresholdVisualizePanel
-
Set the string with ROC area
- setRoot(boolean) - 类中的方法 weka.gui.treevisualizer.Node
-
Set the value of root.
- setRootNode(String) - 类中的方法 weka.core.xml.XMLDocument
-
sets the root node to use in the XML output.
- setRow(int, double[]) - 类中的方法 weka.core.Matrix
-
已过时。Sets a row of the matrix to the given row.
- setRowDimension(int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Set the row dimenion of the matrix
- setRowHidden(int, boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets the hidden status of the row (if the index is valid)
- setRowName(int, String) - 类中的方法 weka.experiment.ResultMatrix
-
sets the name of the row (if the index is valid)
- setRowNameWidth(int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the width for the row names (0 = optimal)
- setRowNumber(int) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the row number for this sub task
- setRowOrder(int[]) - 类中的方法 weka.experiment.ResultMatrix
-
sets the ordering of the rows, null means default
- setRsource(String) - 类中的方法 weka.gui.treevisualizer.Edge
-
Set the value of rsource.
- setRtarget(String) - 类中的方法 weka.gui.treevisualizer.Edge
-
Set the value of rtarget.
- setRuleset(FastVector) - 类中的方法 weka.classifiers.rules.RuleStats
-
Set the ruleset of the stats, overwriting the old one if any
- setRulesMustContain(String) - 类中的方法 weka.associations.FPGrowth
-
Set the comma separated list of items that rules must contain in order to be output.
- setRunColumn(int) - 类中的方法 weka.experiment.PairedTTester
-
Set the value of RunColumn.
- setRunColumn(int) - 接口中的方法 weka.experiment.Tester
-
Set the value of RunColumn.
- setRunLower(int) - 类中的方法 weka.experiment.Experiment
-
Set the lower run number for the experiment.
- setRunLower(int) - 类中的方法 weka.experiment.RemoteExperiment
-
Set the lower run number for the experiment.
- setRuns(int) - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
-
Sets the number of runs
- setRuns(int) - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
Sets the number of runs
- setRuns(int) - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Sets the m_nRuns.
- setRuns(int) - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
-
Sets the number of runs
- setRuns(int) - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
-
Sets the number of runs
- setRuns(int) - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
-
Sets the number of runs
- setRuns(int) - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Sets the m_nRuns.
- setRuns(int) - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
-
Sets the number of runs
- setRunUpper(int) - 类中的方法 weka.experiment.Experiment
-
Set the upper run number for the experiment.
- setRunUpper(int) - 类中的方法 weka.experiment.RemoteExperiment
-
Set the upper run number for the experiment.
- setSampleSize(int) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Set the number of instances to sample for attribute estimation
- setSampleSize(int) - 类中的方法 weka.classifiers.functions.LeastMedSq
-
sets number of samples
- setSampleSize(int) - 类中的方法 weka.filters.unsupervised.instance.ReservoirSample
-
Sets the size of the subsample.
- setSampleSizePercent(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Sets the sample size for the initial grid search.
- setSampleSizePercent(double) - 类中的方法 weka.filters.supervised.instance.Resample
-
Sets the size of the subsample, as a percentage of the original set.
- setSampleSizePercent(double) - 类中的方法 weka.filters.unsupervised.instance.Resample
-
Sets the size of the subsample, as a percentage of the original set.
- setSaveDialogTitle(String) - 类中的方法 weka.gui.visualize.PrintableComponent
-
sets the title for the save dialog.
- setSaveDialogTitle(String) - 接口中的方法 weka.gui.visualize.PrintableHandler
-
sets the title for the save dialog
- setSaveDialogTitle(String) - 类中的方法 weka.gui.visualize.PrintablePanel
-
sets the title for the save dialog
- setSaveInstanceData(boolean) - 类中的方法 weka.classifiers.trees.ADTree
-
Sets whether the tree is to save instance data.
- setSaveInstanceData(boolean) - 类中的方法 weka.classifiers.trees.J48
-
Set whether instance data is to be saved.
- setSaveInstanceData(boolean) - 类中的方法 weka.classifiers.trees.J48graft
-
Set whether instance data is to be saved.
- setSaveInstanceData(boolean) - 类中的方法 weka.clusterers.Cobweb
-
Set the value of saveInstances.
- setSaveInstances(boolean) - 类中的方法 weka.classifiers.trees.M5P
-
Set whether to save instance data at each node in the tree for visualization purposes
- setSaverTemplate(Saver) - 类中的方法 weka.gui.beans.Saver
-
Set the loader to use
- setScale(double) - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Sets the scaling factor.
- setScale(double, double) - 类中的方法 weka.gui.visualize.JComponentWriter
-
sets the scale factor - is ignored since we always create a screenshot!
- setScale(double, double) - 类中的方法 weka.gui.visualize.PrintableComponent
-
sets the scale factor.
- setScale(double, double) - 接口中的方法 weka.gui.visualize.PrintableHandler
-
sets the scale factor
- setScale(double, double) - 类中的方法 weka.gui.visualize.PrintablePanel
-
sets the scale factor
- setScalingEnabled(boolean) - 类中的方法 weka.gui.visualize.JComponentWriter
-
sets whether to enable scaling
- setScoreType(SelectedTag) - 类中的方法 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
set quality measure to be used in searching for networks.
- setSearch(ASSearch) - 类中的方法 weka.attributeSelection.AttributeSelection
-
set the search method
- setSearch(ASSearch) - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Set the search method to test.
- setSearch(ASSearch) - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Sets the search method
- setSearch(ASSearch) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Sets the search method to use
- setSearch(ASSearch) - 类中的方法 weka.classifiers.rules.DTNB
-
Sets the search method to use
- setSearch(ASSearch) - 类中的方法 weka.filters.supervised.attribute.AttributeSelection
-
Set search class
- setSearchAlgorithm(SearchAlgorithm) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Set the SearchAlgorithm used in searching for network structures.
- setSearchBackwards(boolean) - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Set whether to search backwards instead of forwards
- setSearchPath(SelectedTag) - 类中的方法 weka.classifiers.trees.ADTree
-
Sets the method of searching the tree for a new insertion.
- setSearchPercent(double) - 类中的方法 weka.attributeSelection.RandomSearch
-
set the percentage of the search space to consider
- setSearchString(String) - 类中的方法 weka.gui.arffviewer.ArffTable
-
sets the search string to look for in the table, NULL or "" disables the search
- setSearchTermination(int) - 类中的方法 weka.attributeSelection.BestFirst
-
Set the numnber of non-improving nodes to consider before terminating search.
- setSearchTermination(int) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Set the numnber of non-improving nodes to consider before terminating search.
- setSecondValueIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.MergeTwoValues
-
Sets index of the second value used.
- setSecondValueIndex(String) - 类中的方法 weka.filters.unsupervised.attribute.SwapValues
-
Sets index of the second value used.
- setSeed(int) - 类中的方法 weka.attributeSelection.AttributeSelection
-
set the seed for use in cross validation
- setSeed(int) - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.attributeSelection.GeneticSearch
-
set the seed for random number generation
- setSeed(int) - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Set the random number seed for cross validation
- setSeed(int) - 类中的方法 weka.attributeSelection.RandomSearch
-
Set the random seed to use
- setSeed(int) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Set the random number seed for randomly sampling instances.
- setSeed(int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
set the seed for random number generation
- setSeed(int) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Seed for cross validation subset size determination.
- setSeed(int) - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Set the seed to use for cross validation
- setSeed(int) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the seed for randomizing the instances for CV-based hyperparameter selection
- setSeed(int) - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
-
Sets the random number seed
- setSeed(int) - 类中的方法 weka.classifiers.bayes.net.search.global.RepeatedHillClimber
-
Sets the random number seed
- setSeed(int) - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Sets the random number seed
- setSeed(int) - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
-
Sets the random number seed
- setSeed(int) - 类中的方法 weka.classifiers.bayes.net.search.local.RepeatedHillClimber
-
Sets the random number seed
- setSeed(int) - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Sets the random number seed
- setSeed(int) - 类中的方法 weka.classifiers.BVDecompose
-
Sets the random number seed
- setSeed(int) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Sets the random number seed
- setSeed(int) - 类中的方法 weka.classifiers.evaluation.EvaluationUtils
-
Sets the seed for randomization during cross-validation
- setSeed(int) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
This seeds the random number generator, that is used when a random number is needed for the network.
- setSeed(int) - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Sets the seed value for the random number generator
- setSeed(int) - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Set the value of Seed.
- setSeed(int) - 类中的方法 weka.classifiers.functions.Winnow
-
Set the value of Seed.
- setSeed(int) - 类中的方法 weka.classifiers.meta.MultiScheme
-
Sets the seed for random number generation.
- setSeed(int) - 类中的方法 weka.classifiers.RandomizableClassifier
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.classifiers.RandomizableMultipleClassifiersCombiner
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.classifiers.RandomizableSingleClassifierEnhancer
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.classifiers.rules.PART
-
Set the value of Seed.
- setSeed(int) - 类中的方法 weka.classifiers.rules.Ridor
- setSeed(int) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of Seed.
- setSeed(int) - 类中的方法 weka.classifiers.trees.RandomForest
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.classifiers.trees.RandomTree
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.classifiers.trees.REPTree
-
Set the value of Seed.
- setSeed(int) - 类中的方法 weka.clusterers.RandomizableClusterer
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.clusterers.RandomizableDensityBasedClusterer
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.clusterers.RandomizableSingleClustererEnhancer
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Sets the seed for random number generator (that is used for selecting the first anchor point randomly).
- setSeed(int) - 接口中的方法 weka.core.Randomizable
-
Set the seed for random number generation.
- setSeed(int) - 类中的方法 weka.core.TestInstances
-
sets the seed value for the random number generator
- setSeed(int) - 类中的方法 weka.datagenerators.classifiers.classification.BayesNet
-
Sets the random number seed.
- setSeed(int) - 类中的方法 weka.datagenerators.DataGenerator
-
Sets the random number seed.
- setSeed(int) - 类中的方法 weka.filters.unsupervised.attribute.PropositionalToMultiInstance
-
Sets the new seed for randomizing the order of the generated data
- setSeed(int) - 类中的方法 weka.filters.unsupervised.attribute.RandomSubset
-
Set the seed value for the random number generator.
- setSeed(int) - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Set the seed
- setSeed(int) - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Set the random seed
- setSeed(int) - 接口中的方法 weka.gui.boundaryvisualizer.DataGenerator
-
Set a seed for random number generation (if needed).
- setSeed(int) - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
-
Initializes a new random number generator using the supplied seed.
- setSeed(long) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
sets the seed for randomizing the data
- setSeed(long) - 类中的方法 weka.classifiers.rules.JRip
-
Sets the seed value to use in randomizing the data
- setSeed(long) - 类中的方法 weka.core.Debug.Random
-
Sets the seed of this random number generator using a single long seed.
- setSeed(long) - 类中的方法 weka.filters.supervised.attribute.ClassOrder
-
Set randomization seed
- setSeed(long) - 类中的方法 weka.filters.supervised.instance.StratifiedRemoveFolds
-
Sets the random number seed for shuffling the dataset.
- setSeed(long) - 类中的方法 weka.filters.unsupervised.instance.RemoveFolds
-
Sets the random number seed for shuffling the dataset.
- setSelectedAttributes(boolean[]) - 类中的方法 weka.gui.AttributeSelectionPanel
-
Set the selected attributes in the widget.
- setSelectedColumn(int) - 类中的方法 weka.gui.arffviewer.ArffTable
-
sets the selected column
- setSelectedRange(String) - 类中的方法 weka.filters.unsupervised.attribute.RELAGGS
-
Set the range of attributes to process.
- setSelectedRange(String) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Set the value of m_SelectedRange.
- setSelectionThreshold(double) - 类中的方法 weka.attributeSelection.RaceSearch
-
Set the threshold by which the AttributeSelection module can discard attributes.
- setSeparatingThreshold(double) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Sets the separating threshold value
- setSeparatingThreshold(double) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Sets the separating threshold value
- setSeperator(String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Set the seperator between levels.
- setSequentialAttIndex(boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
A Sequential Attribute index is all those Attributes that are set to the specified value placed in a sequential array.
- setSequentialDataset(boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
Sets both the Instance and Attribute indexes to a specified value
- setSequentialInstanceIndex(boolean) - 类中的方法 weka.classifiers.lazy.LBR.Indexes
-
A Sequential Instance index is all those Instances that are set to the specified value placed in a sequential array.
- setSerializedClassifierFile(File) - 类中的方法 weka.filters.supervised.attribute.AddClassification
-
Sets the file pointing to a serialized, trained classifier.
- setShape(int) - 类中的方法 weka.gui.treevisualizer.Node
-
Set the value of shape.
- setShapes(FastVector) - 类中的方法 weka.gui.visualize.VisualizePanel
-
This will set the shapes for the instances.
- setShapeSize(int[]) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the shape sizes for the plot data
- setShapeSize(FastVector) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the shape sizes for the plot data
- setShapeType(int[]) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the shape type for the plot data
- setShapeType(FastVector) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the shape type for the plot data
- setShowAttBars(boolean) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Set whether the attribute bars should be shown or not.
- setShowAverage(boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets whether to display the average per column or not
- setShowAverage(boolean) - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
sets whether the average for each column is displayed.
- setShowClassPanel(boolean) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Set whether the class panel should be shown or not.
- setShowCoreDistances(boolean) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Sets the flag for showCoreDistances
- setShowGUI(boolean) - 类中的方法 weka.clusterers.OPTICS
-
Sets the flag for displaying the GUI.
- setShowReachabilityDistances(boolean) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Sets the flag for showReachabilityDistances
- setShowStdDev(boolean) - 类中的方法 weka.experiment.ResultMatrix
-
sets whether to display the std deviations or not
- setShowStdDev(boolean) - 类中的方法 weka.experiment.ResultMatrixSignificance
-
sets whether to display the std deviations or not - always false!
- setShowStdDevs(boolean) - 类中的方法 weka.experiment.PairedTTester
-
Set whether standard deviations are displayed or not.
- setShowStdDevs(boolean) - 接口中的方法 weka.experiment.Tester
-
Set whether standard deviations are displayed or not.
- setShowZeroInstancesAsUnknown(boolean) - 类中的方法 weka.gui.InstancesSummaryPanel
-
Set whether to show zero instances as unknown (i.e.
- setShrinkage(double) - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Set the shrinkage parameter
- setShrinkage(double) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Set the value of Shrinkage.
- setShrinking(boolean) - 类中的方法 weka.classifiers.functions.LibSVM
-
whether to use the shrinking heuristics
- setShuffle(int) - 类中的方法 weka.classifiers.rules.Ridor
- setSigma(double) - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Sets the sigma value.
- setSigma(int) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Sets the sigma value.
- setSignificance(int, int, int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the significance at the given position (if the position is valid)
- setSignificanceLevel(double) - 类中的方法 weka.associations.Apriori
-
Set the value of significanceLevel.
- setSignificanceLevel(double) - 类中的方法 weka.attributeSelection.RaceSearch
-
Sets the significance level to use
- setSignificanceLevel(double) - 类中的方法 weka.experiment.PairedTTester
-
Set the value of SignificanceLevel.
- setSignificanceLevel(double) - 接口中的方法 weka.experiment.Tester
-
Set the value of SignificanceLevel.
- setSignificanceWidth(int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the width for the significance (0 = optimal)
- setSilent(boolean) - 类中的方法 weka.core.AllJavadoc
-
sets whether to suppress output in the console
- setSilent(boolean) - 类中的方法 weka.core.Check
-
Set slient mode, i.e., no output at all to stdout
- setSilent(boolean) - 类中的方法 weka.core.Javadoc
-
sets whether to suppress output in the console
- setSilent(boolean) - 类中的方法 weka.estimators.CheckEstimator
-
Set slient mode, i.e., no output at all to stdout
- setSIndex(int) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Set the shape for creating splits.
- setSingle(String) - 类中的方法 weka.gui.ResultHistoryPanel
-
Sets the single-click display to view the named result.
- setSingleIndex(String) - 类中的方法 weka.core.SingleIndex
-
Sets the index from a string representation.
- setSize(int) - 类中的方法 weka.core.matrix.DoubleVector
-
Sets the size of the vector
- setSize(int) - 类中的方法 weka.core.matrix.IntVector
-
Sets the size of the vector.
- setSize(int, int) - 类中的方法 weka.experiment.ResultMatrix
-
clears the content of the matrix and sets the new size
- setSizePer(double) - 类中的方法 weka.classifiers.trees.BFTree
-
Set training set size.
- setSizePer(double) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Set training set size.
- setSkipIdentical(boolean) - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Sets the property to skip identical instances (with distance zero from the target) from the set of neighbours returned.
- setSmoothing(boolean) - 类中的方法 weka.classifiers.trees.m5.Rule
-
Smooth predictions
- setSmoothingParameter(double) - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Sets the smoothing value used to avoid zero WordGivenClass probabilities
- setSMOReg(SMOreg) - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
sets the parent SVM
- setSort(boolean) - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Sets whether the labels are sorted.
- setSortColumn(int) - 类中的方法 weka.experiment.PairedTTester
-
Set the column to sort on, -1 means the default sorting.
- setSortColumn(int) - 接口中的方法 weka.experiment.Tester
-
Set the column to sort on, -1 means the default sorting.
- setSource() - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets the database url using the DatabaseUtils file
- setSource(File) - 类中的方法 weka.core.converters.AbstractFileLoader
-
Resets the Loader object and sets the source of the data set to be the supplied File object.
- setSource(File) - 类中的方法 weka.core.converters.AbstractLoader
-
Default implementation throws an IOException.
- setSource(File) - 类中的方法 weka.core.converters.C45Loader
-
Resets the Loader object and sets the source of the data set to be the supplied File object.
- setSource(File) - 类中的方法 weka.core.converters.CSVLoader
-
Resets the Loader object and sets the source of the data set to be the supplied File object.
- setSource(File) - 接口中的方法 weka.core.converters.Loader
-
Resets the Loader object and sets the source of the data set to be the supplied File object.
- setSource(File) - 类中的方法 weka.core.converters.TextDirectoryLoader
-
Resets the Loader object and sets the source of the data set to be the supplied File object.
- setSource(File) - 类中的方法 weka.core.converters.XRFFLoader
-
Resets the Loader object and sets the source of the data set to be the supplied File object.
- setSource(InputStream) - 类中的方法 weka.core.converters.AbstractLoader
-
Default implementation throws an IOException.
- setSource(InputStream) - 类中的方法 weka.core.converters.ArffLoader
-
Resets the Loader object and sets the source of the data set to be the supplied InputStream.
- setSource(InputStream) - 类中的方法 weka.core.converters.CSVLoader
-
Resets the Loader object and sets the source of the data set to be the supplied Stream object.
- setSource(InputStream) - 类中的方法 weka.core.converters.LibSVMLoader
-
Resets the Loader object and sets the source of the data set to be the supplied InputStream.
- setSource(InputStream) - 接口中的方法 weka.core.converters.Loader
-
Resets the Loader object and sets the source of the data set to be the supplied InputStream.
- setSource(InputStream) - 类中的方法 weka.core.converters.SerializedInstancesLoader
-
Resets the Loader object and sets the source of the data set to be the supplied InputStream.
- setSource(InputStream) - 类中的方法 weka.core.converters.SVMLightLoader
-
Resets the Loader object and sets the source of the data set to be the supplied InputStream.
- setSource(InputStream) - 类中的方法 weka.core.converters.XRFFLoader
-
Resets the Loader object and sets the source of the data set to be the supplied InputStream.
- setSource(String) - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets the database url
- setSource(String, String, String) - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets the database url, user and pw
- setSource(URL) - 类中的方法 weka.core.converters.ArffLoader
-
Resets the Loader object and sets the source of the data set to be the supplied url.
- setSource(URL) - 类中的方法 weka.core.converters.LibSVMLoader
-
Resets the Loader object and sets the source of the data set to be the supplied url.
- setSource(URL) - 类中的方法 weka.core.converters.SVMLightLoader
-
Resets the Loader object and sets the source of the data set to be the supplied url.
- setSource(URL) - 类中的方法 weka.core.converters.XRFFLoader
-
Resets the Loader object and sets the source of the data set to be the supplied url.
- setSource(Node) - 类中的方法 weka.gui.treevisualizer.Edge
-
Set the value of source.
- setSourceCode(Classifier) - 类中的方法 weka.classifiers.CheckSource
-
Sets the class to test.
- setSourceCode(Filter) - 类中的方法 weka.filters.CheckSource
-
Sets the class to test.
- setSparseData(boolean) - 类中的方法 weka.experiment.InstanceQuery
-
Sets whether data should be encoded as sparse instances
- setSplitByDataSet(boolean) - 类中的方法 weka.experiment.RemoteExperiment
-
Set whether sub experiments are to be created on the basis of data set.
- setSplitEvaluator(SplitEvaluator) - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Set the SplitEvaluator.
- setSplitEvaluator(SplitEvaluator) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Set the SplitEvaluator.
- setSplitOnResiduals(boolean) - 类中的方法 weka.classifiers.trees.LMT
-
Set the value of splitOnResiduals.
- setSplitPoint(double) - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Split point to be used for selection on numeric attribute.
- setSplitPoint(Instances) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Sets split point to greatest value in given data smaller or equal to old split point.
- setSplitPoint(Instances) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Sets split point to greatest value in given data smaller or equal to old split point.
- setStartEndIndices(int, int) - 类中的方法 weka.core.neighboursearch.balltrees.BallNode
-
Sets the the start and end index of the portion of the master index array that is assigned to this node.
- setStartPoint(int) - 类中的方法 weka.attributeSelection.RankSearch
-
Set the point at which to start evaluating the ranking
- setStartSequentially(boolean) - 类中的方法 weka.gui.beans.FlowRunner
-
Set whether to launch Startable beans one after the other or all in parallel.
- setStartSet(String) - 类中的方法 weka.attributeSelection.BestFirst
-
Sets a starting set of attributes for the search.
- setStartSet(String) - 类中的方法 weka.attributeSelection.GeneticSearch
-
Sets a starting set of attributes for the search.
- setStartSet(String) - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Sets a starting set of attributes for the search.
- setStartSet(String) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Sets a starting set of attributes for the search.
- setStartSet(String) - 类中的方法 weka.attributeSelection.RandomSearch
-
Sets a starting set of attributes for the search.
- setStartSet(String) - 类中的方法 weka.attributeSelection.Ranker
-
Sets a starting set of attributes for the search.
- setStartSet(String) - 接口中的方法 weka.attributeSelection.StartSetHandler
-
Sets a starting set of attributes for the search.
- setStatic() - 类中的方法 weka.gui.beans.BeanVisual
-
Set the static version of the icon
- setStatus(int) - 类中的方法 weka.gui.beans.IncrementalClassifierEvent
-
Set the status
- setStatus(int) - 类中的方法 weka.gui.beans.InstanceEvent
-
Set the status
- setStatusFrequency(int) - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Set how often progress is reported to the status bar.
- setStatusMessage(String) - 类中的方法 weka.experiment.TaskStatusInfo
-
Set the status message.
- setStdDev(int, int, double) - 类中的方法 weka.experiment.ResultMatrix
-
sets the std deviation at the given position (if the position is valid)
- setStdDevPrec(int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the precision for the standard deviation
- setStdDevPrec(int) - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
Sets the precision of the std.
- setStdDevWidth(int) - 类中的方法 weka.experiment.ResultMatrix
-
sets the width for the std dev (0 = optimal)
- setStemmer(String) - 类中的方法 weka.core.stemmers.SnowballStemmer
-
sets the stemmer with the given name, e.g., "porter".
- setStemmer(Stemmer) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
- setStepSize(int) - 类中的方法 weka.attributeSelection.RankSearch
-
Set the number of attributes to add from the rankining in each iteration
- setStepSize(int) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Set the value of StepSize.
- setStopwords(File) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
sets the file containing the stopwords, null or a directory unset the stopwords.
- setStringAttributes(String) - 类中的方法 weka.core.converters.CSVLoader
-
Sets the attribute range to be forced to type string.
- setStroke(Stroke) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- setStructure(Instances) - 类中的方法 weka.core.converters.AbstractSaver
-
Sets the strcuture of the instances for the first step of incremental saving.
- setStructure(Instances) - 类中的方法 weka.gui.beans.IncrementalClassifierEvent
-
Set the instances structure
- setStructure(Instances) - 类中的方法 weka.gui.beans.InstanceEvent
-
Set the instances structure
- setSubFlow(Vector) - 类中的方法 weka.gui.beans.MetaBean
- setSubFlowPreview(ImageIcon) - 类中的方法 weka.gui.beans.MetaBean
- setSubsequenceLength(int) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Sets the length of the subsequence.
- setSubsetEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Set the subset evaluator to use
- setSubsetSizeEvaluator(ASEvaluation) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Set the subset evaluator to use for subset size determination.
- setSubSpaceSize(double) - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Sets the size of each subSpace, as a percentage of the training set size.
- setSubtreeRaising(boolean) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of subtreeRaising.
- setSubtreeRaising(boolean) - 类中的方法 weka.classifiers.trees.J48graft
-
Set the value of subtreeRaising.
- setSummary(int[][], int[][]) - 类中的方法 weka.experiment.ResultMatrix
-
sets the non-significant and significant wins of the resultsets
- setSuppressErrorMessage(boolean) - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Turn off the error message that is reported when no useful attribute is found.
- setSVMType(SelectedTag) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Sets type of SVM (default SVMTYPE_L2)
- setSVMType(SelectedTag) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets type of SVM (default SVMTYPE_C_SVC)
- setSymbols(HashMap) - 类中的方法 weka.core.mathematicalexpression.Parser
-
Sets the variable - value relation to use.
- setSymbols(HashMap) - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Sets the variable - value relation to use.
- setTableName(String) - 类中的方法 weka.core.converters.DatabaseSaver
-
Sets the table's name.
- setTabuList(int) - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
-
Sets the Tabu List length.
- setTabuList(int) - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
-
Sets the Tabu List length.
- setTarget(Object) - 类中的方法 weka.gui.PropertySheetPanel
-
Sets a new target object for customisation.
- setTarget(Node) - 类中的方法 weka.gui.treevisualizer.Edge
-
Set the value of target.
- setTargetClass(int) - 类中的方法 weka.classifiers.bayes.DMNBtext.DNBBinary
-
Sets the Target Class
- setTaskResult(Object) - 类中的方法 weka.experiment.TaskStatusInfo
-
Set the returnable result for this task..
- setTestBaseFromDialog() - 类中的方法 weka.gui.experiment.ResultsPanel
- setTestEvaluator(boolean) - 类中的方法 weka.attributeSelection.CheckAttributeSelection
-
Sets whether the evaluator or the search method is being tested.
- setTestSet(DataSetEvent) - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Set the test set
- setText(String) - 类中的方法 weka.gui.beans.BeanVisual
-
Set the label for the visual.
- setTFTransform(boolean) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
- setThreshold(double) - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Set the threshold by which the AttributeSelection module can discard attributes.
- setThreshold(double) - 类中的方法 weka.attributeSelection.RaceSearch
-
Sets the threshold for comparisons
- setThreshold(double) - 接口中的方法 weka.attributeSelection.RankedOutputSearch
-
Sets a threshold by which attributes can be discarded from the ranking.
- setThreshold(double) - 类中的方法 weka.attributeSelection.Ranker
-
Set the threshold by which the AttributeSelection module can discard attributes.
- setThreshold(double) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Set the treshold
- setThreshold(double) - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Set the value of the threshold for repeating cross validation
- setThreshold(double) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the threshold to use.
- setThreshold(double) - 类中的方法 weka.classifiers.functions.PaceRegression
-
Set threshold for the olsc estimator
- setThreshold(double) - 类中的方法 weka.classifiers.functions.Winnow
-
Set the value of Threshold.
- setThreshold(double) - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Sets the threshold for the max error when predicting a numeric class.
- setTimes(int, double) - 类中的方法 weka.core.matrix.DoubleVector
-
Multiplies a value to an element
- setTimes(int, int, double) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Multiply a value with an element and reset the element
- setTokenizer(Tokenizer) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
the tokenizer algorithm to use.
- setTolerance(double) - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Set the tolerance value
- setTolerance(double) - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
sets the tolerance
- setToleranceParameter(double) - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Set the value of T for SMO
- setToleranceParameter(double) - 类中的方法 weka.classifiers.functions.SMO
-
Set the value of tolerance parameter.
- setToleranceParameter(double) - 类中的方法 weka.classifiers.mi.MISMO
-
Set the value of tolerance parameter.
- setToolTipText(String) - 类中的方法 weka.gui.GenericObjectEditor.GOETreeNode
-
Set the tool tip for this node
- setTop(double) - 类中的方法 weka.gui.treevisualizer.Node
-
Set the value of top.
- setTrainingData(Instances) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set the training data to use
- setTrainingTime(int) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
Set the number of training epochs to perform.
- setTrainIterations(int) - 类中的方法 weka.classifiers.BVDecompose
-
Sets the maximum number of boost iterations
- setTrainPercent(double) - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Set the value of TrainPercent.
- setTrainPercent(double) - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Set the percentage of data to be in the training portion of the split
- setTrainPoolSize(int) - 类中的方法 weka.classifiers.BVDecompose
-
Set the number of instances in the training pool.
- setTrainSet(DataSetEvent) - 类中的方法 weka.gui.beans.BatchClassifierEvent
-
Set the training set
- setTrainSize(int) - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Set the training size.
- setTransactionsMustContain(String) - 类中的方法 weka.associations.FPGrowth
-
Set the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.
- setTransform(AffineTransform) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- setTransformAllValues(boolean) - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Sets whether all nominal values are transformed into new attributes, not just if there are more than 2.
- setTransformAllValues(boolean) - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Sets whether all nominal values are transformed into new attributes, not just if there are more than 2.
- setTransformBackToOriginal(boolean) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Sets whether the data should be transformed back to the original space
- setTransformMethod(SelectedTag) - 类中的方法 weka.classifiers.mi.SimpleMI
-
Set the method used in transformation.
- setTranslation(double) - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Sets the translation.
- setTraversal(SelectedTag) - 类中的方法 weka.classifiers.meta.GridSearch
-
Sets the type of traversal for the grid.
- setTrimingThreshold(double) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Sets the triming thresholding value.
- setTrimingThreshold(double) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Sets the triming thresholding value.
- setTrueNegative(double) - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Sets the number of negative instances predicted as negative
- setTruePositive(double) - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Sets the number of positive instances predicted as positive
- setTStart(double) - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
-
Sets the m_fTStart.
- setTStart(double) - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
-
Sets the m_fTStart.
- setType(int) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- setType(SelectedTag) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Set the type
- setType(SelectedTag) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Set the type
- setUndoEnabled(boolean) - 接口中的方法 weka.core.Undoable
-
sets whether undo support is enabled
- setUndoEnabled(boolean) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
sets whether undo support is enabled
- setUndoEnabled(boolean) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
sets whether undo support is enabled
- setUndoEnabled(boolean) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
sets whether undo support is enabled
- setUnpruned(boolean) - 类中的方法 weka.classifiers.rules.PART
-
Set the value of unpruned.
- setUnpruned(boolean) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of unpruned.
- setUnpruned(boolean) - 类中的方法 weka.classifiers.trees.J48graft
-
Set the value of unpruned.
- setUnpruned(boolean) - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Use unpruned tree/rules
- setUnpruned(boolean) - 类中的方法 weka.classifiers.trees.m5.Rule
-
Use unpruned tree/rules
- setupAttribLists() - 类中的方法 weka.gui.visualize.MatrixPanel
-
Sets up the UI's attributes lists
- setUpBoundaryPanel() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Sets up the BoundaryPanel object so that it is ready for plotting.
- setUpComboBoxes(Instances) - 类中的方法 weka.gui.visualize.ThresholdVisualizePanel
-
This overloads VisualizePanel's setUpComboBoxes to add ActionListeners to watch for when the X/Y Axis comboboxes are changed.
- setUpComboBoxes(Instances) - 类中的方法 weka.gui.visualize.VisualizePanel
-
initializes the comboboxes based on the data
- setUpdateIncrementalClassifier(boolean) - 类中的方法 weka.gui.beans.Classifier
-
Set whether an incremental classifier will be updated on the incoming instance stream.
- setUpFile() - 类中的方法 weka.gui.beans.LoaderCustomizer
- setUpFile() - 类中的方法 weka.gui.beans.SaverCustomizer
-
Sets up dialog for saving instances in a file
- setUpFile() - 类中的方法 weka.gui.beans.SerializedModelSaverCustomizer
-
Sets up dialog for saving models to a file
- SetupModePanel - weka.gui.experiment中的类
-
This panel switches between simple and advanced experiment setup panels.
- SetupModePanel() - 类的构造器 weka.gui.experiment.SetupModePanel
-
Creates the setup panel with no initial experiment.
- SetupPanel - weka.gui.experiment中的类
-
This panel controls the configuration of an experiment.
- SetupPanel() - 类的构造器 weka.gui.experiment.SetupPanel
-
Creates the setup panel with no initial experiment.
- SetupPanel(Experiment) - 类的构造器 weka.gui.experiment.SetupPanel
-
Creates the setup panel with the supplied initial experiment.
- setUpper(int) - 类中的方法 weka.core.Range
-
Sets the value of "last".
- setUpper(int) - 类中的方法 weka.core.SingleIndex
-
Sets the value of "last".
- setUpperBoundMinSupport(double) - 类中的方法 weka.associations.Apriori
-
Set the value of upperBoundMinSupport.
- setUpperBoundMinSupport(double) - 类中的方法 weka.associations.FPGrowth
-
Set the value of upperBoundMinSupport.
- setUpperSize(int) - 类中的方法 weka.experiment.LearningRateResultProducer
-
Set the value of UpperSize.
- setUpVisualizableInstances(Instances) - 类中的静态方法 weka.gui.explorer.ClassifierPanel
-
Sets up the structure for the visualizable instances.
- setUpVisualizableInstances(Instances, ClusterEvaluation) - 类中的静态方法 weka.gui.explorer.ClustererPanel
-
Sets up the structure for the visualizable instances.
- setUrl(String) - 接口中的方法 weka.core.converters.DatabaseConverter
- setUrl(String) - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets the database URL
- setUrl(String) - 类中的方法 weka.core.converters.DatabaseSaver
-
Sets the database URL.
- setURL(String) - 类中的方法 weka.core.converters.ArffLoader
-
Set the url to load from
- setURL(String) - 类中的方法 weka.core.converters.LibSVMLoader
-
Set the url to load from.
- setURL(String) - 类中的方法 weka.core.converters.SVMLightLoader
-
Set the url to load from.
- setURL(String) - 接口中的方法 weka.core.converters.URLSourcedLoader
-
Set the url to load from
- setURL(String) - 类中的方法 weka.core.converters.XRFFLoader
-
Set the url to load from
- setURL(String) - 类中的方法 weka.gui.sql.ConnectionPanel
-
sets the URL.
- setUseADTree(boolean) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Set whether ADTree structure is used or not
- setUseAIC(boolean) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Set the value of useAIC.
- setUseAIC(boolean) - 类中的方法 weka.classifiers.trees.FT
-
Set the value of useAIC.
- setUseAIC(boolean) - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Set the value of useAIC.
- setUseAIC(boolean) - 类中的方法 weka.classifiers.trees.LMT
-
Set the value of useAIC.
- setUseArcReversal(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
-
set use the arc reversal operation
- setUseArcReversal(boolean) - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
-
set use the arc reversal operation
- setUseBetterEncoding(boolean) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Sets whether better encoding is to be used for MDL.
- setUseCpuTime(boolean) - 类中的方法 weka.core.Debug.Clock
-
enables/disables the use of CPU time (if measurement of CPU time is available).
- setUseCrossOver(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- setUseCrossOver(boolean) - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- setUseCrossValidation(boolean) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Set the value of useCrossValidation.
- setUseCustomDimensions(boolean) - 类中的方法 weka.gui.visualize.JComponentWriter
-
sets whether to use custom dimensions for the image
- setUseEqualFrequency(boolean) - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Set the value of UseEqualFrequency.
- setUseEqualFrequency(boolean) - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Set the value of UseEqualFrequency.
- setUseEqualFrequency(boolean) - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Set the value of UseEqualFrequency.
- setUseErrorRate(boolean) - 类中的方法 weka.classifiers.trees.BFTree
-
Set if use error rate in internal cross-validation.
- setUseGini(boolean) - 类中的方法 weka.classifiers.trees.BFTree
-
Set if use Gini index as splitting criterion.
- setUseIBk(boolean) - 类中的方法 weka.classifiers.rules.DecisionTable
-
Sets whether IBk should be used instead of the majority class
- setUseK2Prior(boolean) - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
Sets the UseK2Prior.
- setUseK2Prior(boolean) - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
Sets the UseK2Prior.
- setUseKDTree(boolean) - 类中的方法 weka.clusterers.XMeans
-
Sets whether to use the KDTree or not.
- setUseKernelEstimator(boolean) - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Sets if kernel estimator is to be used.
- setUseKononenko(boolean) - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Sets whether Kononenko's MDL criterion is to be used.
- setUseLaplace(boolean) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Sets if laplace correction is to be used.
- setUseLaplace(boolean) - 类中的方法 weka.classifiers.trees.J48
-
Set the value of useLaplace.
- setUseLaplace(boolean) - 类中的方法 weka.classifiers.trees.J48graft
-
Set the value of useLaplace.
- setUseLeastValues(boolean) - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Sets whether to use values with least or most instances
- setUseLowerOrder(boolean) - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Sets whether to use lower-order terms.
- setUseMEstimates(boolean) - 类中的方法 weka.classifiers.bayes.AODE
-
Sets if m-estimates is to be used.
- setUseMissing(boolean) - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Sets the flag if missing values are treated as extra values.
- setUseMutation(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- setUseMutation(boolean) - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- setUseNormalization(boolean) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Sets whether to use normalization.
- setUseOneSE(boolean) - 类中的方法 weka.classifiers.trees.BFTree
-
Set if use the 1SE rule to choose final model.
- setUseOneSE(boolean) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Set if use the 1SE rule to choose final model.
- setUseORForMustContainList(boolean) - 类中的方法 weka.associations.FPGrowth
-
Set whether to use OR rather than AND when considering must contain lists.
- setUsePairwiseCoupling(boolean) - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Set whether to use pairwise coupling with 1-vs-1 classification to improve probability estimates.
- setUseProb(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
- setUsePropertyIterator(boolean) - 类中的方法 weka.experiment.Experiment
-
Sets whether the custom property iterator should be used.
- setUsePropertyIterator(boolean) - 类中的方法 weka.experiment.RemoteExperiment
-
Sets whether the custom property iterator should be used.
- setUsePrune(boolean) - 类中的方法 weka.classifiers.trees.SimpleCart
-
Set if use minimal cost-complexity pruning.
- setUsePruning(boolean) - 类中的方法 weka.classifiers.rules.JRip
-
Sets whether pruning is performed
- setUser(String) - 接口中的方法 weka.core.converters.DatabaseConverter
- setUser(String) - 类中的方法 weka.core.converters.DatabaseLoader
-
Sets the database user
- setUser(String) - 类中的方法 weka.core.converters.DatabaseSaver
-
Sets the database user.
- setUser(String) - 类中的方法 weka.gui.sql.ConnectionPanel
-
sets the User.
- setUseRelativePath(boolean) - 类中的方法 weka.core.converters.AbstractFileLoader
-
Set whether to use relative rather than absolute paths
- setUseRelativePath(boolean) - 类中的方法 weka.core.converters.AbstractFileSaver
-
Set whether to use relative rather than absolute paths
- setUseRelativePath(boolean) - 接口中的方法 weka.core.converters.FileSourcedConverter
-
Set whether to use relative rather than absolute paths
- setUseRelativePath(boolean) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Set whether to use relative paths for the directory.
- setUseResampling(boolean) - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Set resampling mode
- setUseResampling(boolean) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Set resampling mode
- setUseResampling(boolean) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Set resampling mode
- setUsername(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Set the database username.
- setUserOptions(String[]) - 类中的方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
sets the option the user supplied for the kernel
- setUserOptions(String[]) - 类中的方法 weka.core.CheckOptionHandler
-
Sets the user-supplied options (creates a copy)
- setUseStars(boolean) - 类中的方法 weka.core.AllJavadoc
-
sets whether to prefix the Javadoc with "*"
- setUseStars(boolean) - 类中的方法 weka.core.Javadoc
-
sets whether to prefix the Javadoc with "*"
- setUseStoplist(boolean) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets whether if the words that are on a stoplist are to be ignored (The stop list is in weka.core.StopWords).
- setUseSupervisedDiscretization(boolean) - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Set whether supervised discretization is to be used.
- setUseSupervisedDiscretization(boolean) - 类中的方法 weka.classifiers.bayes.NaiveBayesUpdateable
-
Set whether supervised discretization is to be used.
- setUseTournamentSelection(boolean) - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- setUseTournamentSelection(boolean) - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- setUseTraining(boolean) - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Set if training data is to be used instead of hold out/test data
- setUseTree(boolean) - 类中的方法 weka.classifiers.trees.m5.Rule
-
Use an m5 tree rather than generate rules
- setUseUnsmoothed(boolean) - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Use unsmoothed predictions
- setUseVariant1(boolean) - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Sets whether to use variant 1
- setValidating(boolean) - 类中的方法 weka.core.xml.XMLDocument
-
sets whether to use a validating parser or not.
Note: this does clear the current DOM document! - setValidating(boolean) - 类中的方法 weka.core.xml.XMLOptions
-
sets whether to use a validating parser or not.
- setValidationChunkSize(int) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Set the validation chunk size
- setValidationSetSize(int) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
This will set the size of the validation set.
- setValidationThreshold(int) - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
-
This sets the threshold to use for when validation testing is being done.
- setValue(double) - 类中的方法 weka.classifiers.trees.adtree.PredictionNode
-
Sets the prediction value of the node.
- setValue(int, double) - 类中的方法 weka.core.BinarySparseInstance
-
Sets a specific value in the instance to the given value (internal floating-point format).
- setValue(int, double) - 类中的方法 weka.core.Instance
-
Sets a specific value in the instance to the given value (internal floating-point format).
- setValue(int, double) - 类中的方法 weka.core.SparseInstance
-
Sets a specific value in the instance to the given value (internal floating-point format).
- setValue(int, String) - 类中的方法 weka.core.Instance
-
Sets a value of a nominal or string attribute to the given value.
- setValue(Object) - 类中的方法 weka.gui.CostMatrixEditor
-
Sets the value of the CostMatrix to be edited.
- setValue(Object) - 类中的方法 weka.gui.GenericArrayEditor
-
Sets the current object array.
- setValue(Object) - 类中的方法 weka.gui.GenericObjectEditor
-
Sets the current Object.
- setValue(Object) - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Sets the value of the date format to be edited.
- setValue(Object, String, Object) - 类中的静态方法 weka.core.PropertyPath
-
set the given value specified by the given path in the object
- setValue(Object, PropertyPath.Path, Object) - 类中的静态方法 weka.core.PropertyPath
-
set the given value specified by the given path in the object
- setValue(Attribute, double) - 类中的方法 weka.core.Instance
-
Sets a specific value in the instance to the given value (internal floating-point format).
- setValue(Attribute, String) - 类中的方法 weka.core.Instance
-
Sets a value of an nominal or string attribute to the given value.
- setValue(TechnicalInformation.Field, String) - 类中的方法 weka.core.TechnicalInformation
-
sets the value for the given field, overwrites any previously existing one.
- setValueAt(Object, int, int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
sets the value in the cell at columnIndex and rowIndex to aValue.
- setValueAt(Object, int, int) - 类中的方法 weka.gui.SortedTableModel
-
Sets the value in the cell at columnIndex and rowIndex to aValue.
- setValueAt(Object, int, int) - 类中的方法 weka.gui.sql.ResultSetTableModel
-
sets the value in the cell at columnIndex and rowIndex to aValue.
- setValueAt(Object, int, int, boolean) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
sets the value in the cell at columnIndex and rowIndex to aValue.
- setValueIndex(int) - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Sets index of the indicator value.
- setValueIndices(String) - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Sets indices of the indicator values.
- setValueIndicesArray(int[]) - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
-
Set which attributes are to be deleted (or kept if invert is true)
- setValuesList(String) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets the ranges for each attribute.
- setValuesList(String, double[], double[], String) - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Sets the ranges for each attribute.
- setValuesOutput(SelectedTag) - 类中的方法 weka.associations.Tertius
-
Set the value of valuesOutput.
- setValueSparse(int, double) - 类中的方法 weka.core.BinarySparseInstance
-
Sets a specific value in the instance to the given value (internal floating-point format).
- setValueSparse(int, double) - 类中的方法 weka.core.Instance
-
Sets a specific value in the instance to the given value (internal floating-point format).
- setValueSparse(int, double) - 类中的方法 weka.core.SparseInstance
-
Sets a specific value in the instance to the given value (internal floating-point format).
- setVarianceCovered(double) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Sets the amount of variance to account for when retaining principal components
- setVarianceCovered(double) - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Sets the amount of variance to account for when retaining principal components.
- setVerbose(boolean) - 类中的方法 weka.associations.Apriori
-
Sets verbose mode
- setVerbose(boolean) - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
set whether or not to output new best subsets as the search proceeds
- setVerbose(boolean) - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Set whether verbose output should be generated.
- setVerbose(boolean) - 类中的方法 weka.attributeSelection.RandomSearch
-
set whether or not to output new best subsets as the search proceeds
- setVerbose(boolean) - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Set whether verbose output should be generated.
- setVerbose(boolean) - 类中的方法 weka.classifiers.meta.Dagging
-
Set the verbose state.
- setVerboseOn() - 类中的方法 weka.core.Debug.DBO
-
Set the verbose on flag on
- setVerticalAdjustment(int) - 类中的方法 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
-
Sets a new value for the vertical verticalAdjustment
- setVisible(boolean) - 类中的方法 weka.gui.Main
-
Shows or hides this component depending on the value of parameter b.
- setVisible(boolean) - 类中的方法 weka.gui.sql.SqlViewerDialog
-
displays the dialog if TRUE
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.AbstractDataSink
-
Set the visual for this data source
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.AbstractDataSource
-
Set the visual for this data source
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Set the visual
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Set the visual for this bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Set the visual for this bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Set the visual for this bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.Associator
-
Sets the visual appearance of this wrapper bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.ClassAssigner
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.Classifier
-
Sets the visual appearance of this wrapper bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.ClassValuePicker
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.Clusterer
-
Sets the visual appearance of this wrapper bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.DataVisualizer
-
Set the visual appearance of this bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.Filter
-
Set the visual appearance of this bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.GraphViewer
-
Set the visual appearance of this bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Sets the visual appearance of this wrapper bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.MetaBean
-
Sets the visual appearance of this wrapper bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Set the visual appearance of this bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.PredictionAppender
-
Set the visual for this data source
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Set the visual for this data source.
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.StripChart
-
Set the visual appearance of this bean
- setVisual(BeanVisual) - 类中的方法 weka.gui.beans.TextViewer
-
Describe
setVisual
method here. - setVisual(BeanVisual) - 接口中的方法 weka.gui.beans.Visible
-
Set a new visual representation
- setVoteFlag(boolean) - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Sets the vote flag.
- setWeight(double) - 类中的方法 weka.core.Attribute
-
Sets the new attribute's weight
- setWeight(double) - 类中的方法 weka.core.Instance
-
Sets the weight of an instance.
- setWeight(int) - 类中的方法 weka.classifiers.bayes.AODE
-
Sets the weight for m-estimate
- setWeightByConfidence(boolean) - 类中的方法 weka.classifiers.misc.VFI
-
Set weighting by confidence
- setWeightByDistance(boolean) - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Set the nearest neighbour weighting method
- setWeightingDimensions(boolean[]) - 接口中的方法 weka.gui.boundaryvisualizer.DataGenerator
-
Set the dimensions to be used in computing a weight for each instance generated
- setWeightingDimensions(boolean[]) - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
-
Set which dimensions to use when computing a weight for the next instance to generate
- setWeightingKernel(int) - 类中的方法 weka.classifiers.lazy.LWL
-
Sets the kernel weighting method to use.
- setWeightingValues(double[]) - 接口中的方法 weka.gui.boundaryvisualizer.DataGenerator
-
Set the values of the dimensions (chosen via setWeightingDimensions) to be used when computing instance weights
- setWeightingValues(double[]) - 类中的方法 weka.gui.boundaryvisualizer.KDDataGenerator
-
Set the values for the weighting dimensions to be used when computing the weight for the next instance to be generated
- setWeightMethod(SelectedTag) - 类中的方法 weka.classifiers.mi.MIWrapper
-
The new method for weighting the instances.
- setWeightMethod(SelectedTag) - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
The new method for weighting the instances.
- setWeights(String) - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Sets the parameters C of class i to weight[i]*C (default 1).
- setWeights(String) - 类中的方法 weka.classifiers.functions.LibSVM
-
Sets the parameters C of class i to weight[i]*C, for C-SVC (default 1).
- setWeightThreshold(int) - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Set weight threshold
- setWeightThreshold(int) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Set weight thresholding
- setWeightTrimBeta(double) - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Set the value of weightTrimBeta.
- setWeightTrimBeta(double) - 类中的方法 weka.classifiers.trees.FT
-
Set the value of weightTrimBeta.
- setWeightTrimBeta(double) - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Sets the option "weightTrimBeta".
- setWeightTrimBeta(double) - 类中的方法 weka.classifiers.trees.LMT
-
Set the value of weightTrimBeta.
- setWholeDataErr(boolean) - 类中的方法 weka.classifiers.rules.Ridor
- setWindowSize(int) - 类中的方法 weka.classifiers.lazy.IBk
-
Sets the maximum number of instances allowed in the training pool.
- setWords(String) - 类中的方法 weka.core.CheckScheme
-
Sets the comma-separated list of words to use for generating strings.
- setWords(String) - 类中的方法 weka.core.TestInstances
-
Sets the comma-separated list of words to use for generating strings.
- setWordSeparators(String) - 类中的方法 weka.core.CheckScheme
-
sets the word separators (chars) to use for assembling strings.
- setWordSeparators(String) - 类中的方法 weka.core.TestInstances
-
sets the word separators (chars) to use for assembling strings.
- setWordsToKeep(int) - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Sets the number of words (per class if there is a class attribute assigned) to attempt to keep.
- setWordwrap(boolean) - 类中的方法 weka.gui.LogWindow
-
toggles the wordwrap
override wordwrap from: http://forum.java.sun.com/thread.jspa?threadID=498535&messageID=2356174 - setWrappedAlgorithm(Object) - 类中的方法 weka.gui.beans.Associator
-
Sets the algorithm (associator) for this bean
- setWrappedAlgorithm(Object) - 类中的方法 weka.gui.beans.Classifier
-
Sets the algorithm (classifier) for this bean
- setWrappedAlgorithm(Object) - 类中的方法 weka.gui.beans.Clusterer
-
Sets the algorithm (clusterer) for this bean
- setWrappedAlgorithm(Object) - 类中的方法 weka.gui.beans.Filter
-
Set the filter to be wrapped by this bean
- setWrappedAlgorithm(Object) - 类中的方法 weka.gui.beans.Loader
-
Set the loader
- setWrappedAlgorithm(Object) - 类中的方法 weka.gui.beans.Saver
-
Set the saver
- setWrappedAlgorithm(Object) - 接口中的方法 weka.gui.beans.WekaWrapper
-
Set the algorithm.
- setWriteOPTICSresults(boolean) - 类中的方法 weka.clusterers.OPTICS
-
Sets the flag for writing actions
- setX(double) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- setX(int) - 类中的方法 weka.gui.beans.BeanInstance
-
Sets the x coordinate of this bean
- setX(int) - 类中的方法 weka.gui.visualize.AttributePanel
-
shows which bar is the current x attribute.
- setXAttribute(int) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set the x attribute index
- setXAttribute(int) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the x axis fixed dimension
- setXBase(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the value of the base for X.
- setXExpression(String) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the expression for the X value.
- setXindex(int) - 类中的方法 weka.gui.visualize.Plot2D
-
Set the index of the attribute to go on the x axis
- setXindex(int) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the x index of the data.
- setXIndex(int) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Set the index of the attribute for the x axis
- setXLabelFreq(int) - 类中的方法 weka.gui.beans.StripChart
-
Set the frequency for printing x label values
- setXMax(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the value of the Maximum of X.
- setXMin(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the value of the minimum of X.
- setXML(Reader) - 类中的方法 weka.core.xml.XMLInstances
-
reads the XML structure from the given reader
- setXORMode(Color) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Not implemented
- setXProperty(String) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the X property.
- setXStep(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the value of the step size for X.
- setXval(boolean) - 类中的方法 weka.attributeSelection.AttributeSelection
-
do a cross validation
- setXY(int, int) - 类中的方法 weka.gui.beans.BeanInstance
-
Set the x and y coordinates of this bean
- setY(double) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
- setY(int) - 类中的方法 weka.gui.beans.BeanInstance
-
Sets the y coordinate of this bean
- setY(int) - 类中的方法 weka.gui.visualize.AttributePanel
-
shows which bar is the current y attribute.
- setYAttribute(int) - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Set the y attribute index
- setYAttribute(int) - 类中的方法 weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
-
Set the y axis fixed dimension
- setYBase(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the value of the base for Y.
- setYExpression(String) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the expression for the Y value.
- setYindex(int) - 类中的方法 weka.gui.visualize.Plot2D
-
Set the index of the attribute to go on the y axis
- setYindex(int) - 类中的方法 weka.gui.visualize.PlotData2D
-
Set the y index of the data
- setYIndex(int) - 类中的方法 weka.gui.visualize.VisualizePanel
-
Set the index of the attribute for the y axis
- setYMax(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the value of the Maximum of Y.
- setYMin(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the value of the minimum of Y.
- setYProperty(String) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the Y property (normally the classifier).
- setYStep(double) - 类中的方法 weka.classifiers.meta.GridSearch
-
Set the value of the step size for Y.
- SEVERE - enum class 中的枚举常量 weka.core.logging.Logger.Level
-
SEVERE level.
- SEVERE - 类中的静态变量 weka.core.Debug
-
the log level Severe
- SFEntropyGain() - 类中的方法 weka.classifiers.Evaluation
-
Returns the total SF, which is the null model entropy minus the scheme entropy.
- SFMeanEntropyGain() - 类中的方法 weka.classifiers.Evaluation
-
Returns the SF per instance, which is the null model entropy minus the scheme entropy, per instance.
- SFMeanPriorEntropy() - 类中的方法 weka.classifiers.Evaluation
-
Returns the entropy per instance for the null model
- SFMeanSchemeEntropy() - 类中的方法 weka.classifiers.Evaluation
-
Returns the entropy per instance for the scheme
- SFPriorEntropy() - 类中的方法 weka.classifiers.Evaluation
-
Returns the total entropy for the null model
- SFSchemeEntropy() - 类中的方法 weka.classifiers.Evaluation
-
Returns the total entropy for the scheme
- sgn(double) - 类中的静态方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Sign for a given value.
- shear(double, double) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- shift(int, int) - 类中的方法 weka.core.matrix.IntVector
-
Shifts an element to another position.
- shift(int, int, Instance) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Shifts given instance from one bag to another one.
- shiftBeans(BeanInstance, boolean) - 类中的方法 weka.gui.beans.MetaBean
-
Move coords of all inputs and outputs of this meta bean to the coords of the supplied BeanInstance.
- shiftRange(int, int, Instances, int, int) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Shifts all instances in given range from one bag to another one.
- shiftToEnd(int) - 类中的方法 weka.core.matrix.IntVector
-
Shifts an element to the end of the vector.
- SHORT - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for SHORT used for reading experiment results.
- show(Component, int, int) - 类中的方法 weka.gui.GenericObjectEditor.JTreePopupMenu
-
Displays the menu, making sure it will fit on the screen.
- showAttributes() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
displays all the attributes, returns the selected item or NULL if canceled
- showChart() - 类中的方法 weka.gui.beans.StripChart
-
Popup the chart panel
- showDialog() - 类中的方法 weka.gui.experiment.OutputFormatDialog
-
Pops up the modal dialog and waits for cancel or a selection.
- showDialog() - 类中的方法 weka.gui.ListSelectorDialog
-
Pops up the modal dialog and waits for cancel or a selection.
- showDialog() - 类中的方法 weka.gui.PropertySelectorDialog
-
Pops up the modal dialog and waits for cancel or a selection.
- showDialog() - 类中的方法 weka.gui.ViewerDialog
-
Pops up the modal dialog and waits for Cancel or OK.
- showDialog(Component, String) - 类中的方法 weka.gui.ConverterFileChooser
-
Pops a custom file chooser dialog with a custom approve button.
- showDialog(Instances) - 类中的方法 weka.gui.ViewerDialog
-
Pops up the modal dialog and waits for Cancel or OK.
- showExplorer(String) - 类中的方法 weka.gui.GUIChooser
- showGUITipText() - 类中的方法 weka.clusterers.OPTICS
-
Returns the tip text for this property.
- showHistory() - 类中的方法 weka.gui.sql.ConnectionPanel
-
displays the query history.
- showHistory() - 类中的方法 weka.gui.sql.QueryPanel
-
displays the query history.
- showInputBox(Component, String, String, Object) - 类中的静态方法 weka.gui.ComponentHelper
-
pops up an input dialog
- showKnowledgeFlow(String) - 类中的方法 weka.gui.GUIChooser
- showMemoryIsLow() - 类中的方法 weka.core.Memory
-
Prints a warning message if memoryIsLow (and if GUI is present a dialog).
- showMessageBox(Component, String, String, int, int) - 类中的静态方法 weka.gui.ComponentHelper
-
displays a message box with the given title, message, buttons and icon ant the dimension.
- showOpenDialog(Component) - 类中的方法 weka.gui.ConverterFileChooser
-
Pops up an "Open File" file chooser dialog.
- showOutOfMemory() - 类中的方法 weka.core.Memory
-
prints an error message if OutOfMemory (and if GUI is present a dialog), otherwise nothing happens.
- showPopup() - 类中的方法 weka.gui.GenericObjectEditor.CapabilitiesFilterDialog
-
if a JPopupMenu is set, it is displayed again.
- showProperties() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
displays some properties of the instances
- showPropertyDialog() - 类中的方法 weka.gui.PropertyPanel
-
Displays the property edit dialog for the panel.
- showResults() - 类中的方法 weka.gui.beans.GraphViewer
-
Popup a result list from which the user can select a graph to view
- showResults() - 类中的方法 weka.gui.beans.TextViewer
-
Popup a component to display the selected text
- showSaveDialog(Component) - 类中的方法 weka.gui.ConverterFileChooser
-
Pops up an "Save File" file chooser dialog.
- showTree() - 类中的方法 weka.gui.HierarchyPropertyParser
-
Show the whole tree in text format
- showValues() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
displays all the distinct values for an attribute
- showWindow(Container) - 类中的方法 weka.gui.Main
-
brings child frame to the top.
- showWindow(Class) - 类中的方法 weka.gui.Main
-
brings the first frame to the top that is of the specified window class.
- shrinkageTipText() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns the tip text for this property
- shrinkageTipText() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the tip text for this property
- shrinkingTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- shuffleTipText() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns the tip text for this property
- sIB - weka.clusterers中的类
-
Cluster data using the sequential information bottleneck algorithm.
Note: only hard clustering scheme is supported. - sIB() - 类的构造器 weka.clusterers.sIB
- sigLevel - 类中的变量 weka.experiment.PairedStats
-
The significance level for comparisons
- sigmaTipText() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns the tip text for this property
- sigmaTipText() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
Returns the tip text for this property
- SigmoidUnit - weka.classifiers.functions.neural中的类
-
This can be used by the neuralnode to perform all it's computations (as a sigmoid unit).
- SigmoidUnit() - 类的构造器 weka.classifiers.functions.neural.SigmoidUnit
- sign() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the signs of all elements in terms of -1, 0 and +1.
- SIGNIFICANCE_LOSS - 类中的静态变量 weka.experiment.ResultMatrix
-
loss
- SIGNIFICANCE_TIE - 类中的静态变量 weka.experiment.ResultMatrix
-
tie
- SIGNIFICANCE_WIN - 类中的静态变量 weka.experiment.ResultMatrix
-
win
- significanceLevelTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- significanceLevelTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- SIGNIFICANT - 类中的静态变量 weka.associations.Tertius
-
Way of handling missing values: missing as a particular value
- simetricDif(ScatterSearchV1.Subset, ScatterSearchV1.Subset, int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
- SimetricDiference(ScatterSearchV1.Subset, BitSet) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Calculate the Simetric Diference of two subsets
- SimpleBatchFilter - weka.filters中的类
-
This filter is a superclass for simple batch filters.
- SimpleBatchFilter() - 类的构造器 weka.filters.SimpleBatchFilter
- SimpleCart - weka.classifiers.trees中的类
-
Class implementing minimal cost-complexity pruning.
Note when dealing with missing values, use "fractional instances" method instead of surrogate split method.
For more information, see:
Leo Breiman, Jerome H. - SimpleCart() - 类的构造器 weka.classifiers.trees.SimpleCart
- SimpleCLI - weka.gui中的类
-
Creates a very simple command line for invoking the main method of classes.
- SimpleCLI() - 类的构造器 weka.gui.SimpleCLI
-
Constructor
- SimpleCLIPanel - weka.gui中的类
-
Creates a very simple command line for invoking the main method of classes.
- SimpleCLIPanel() - 类的构造器 weka.gui.SimpleCLIPanel
-
Constructor.
- SimpleCLIPanel.CommandlineCompletion - weka.gui中的类
-
A class for commandline completion of classnames.
- SimpleDateFormatEditor - weka.gui中的类
-
Class for editing SimpleDateFormat strings.
- SimpleDateFormatEditor() - 类的构造器 weka.gui.SimpleDateFormatEditor
-
Constructs a new SimpleDateFormatEditor.
- SimpleEstimator - weka.classifiers.bayes.net.estimate中的类
-
SimpleEstimator is used for estimating the conditional probability tables of a Bayes network once the structure has been learned.
- SimpleEstimator() - 类的构造器 weka.classifiers.bayes.net.estimate.SimpleEstimator
- SimpleFilter - weka.filters中的类
-
This filter contains common behavior of the SimpleBatchFilter and the SimpleStreamFilter.
- SimpleFilter() - 类的构造器 weka.filters.SimpleFilter
- SimpleKMeans - weka.clusterers中的类
-
Cluster data using the k means algorithm
- SimpleKMeans() - 类的构造器 weka.clusterers.SimpleKMeans
-
the default constructor
- SimpleLinearRegression - weka.classifiers.functions中的类
-
Learns a simple linear regression model.
- SimpleLinearRegression() - 类的构造器 weka.classifiers.functions.SimpleLinearRegression
- SimpleLinkedList - weka.associations.tertius中的类
- SimpleLinkedList() - 类的构造器 weka.associations.tertius.SimpleLinkedList
- SimpleLinkedList.LinkedListInverseIterator - weka.associations.tertius中的类
- SimpleLinkedList.LinkedListIterator - weka.associations.tertius中的类
- SimpleLog() - 类的构造器 weka.core.Debug.SimpleLog
-
default constructor, uses only stdout
- SimpleLog(String) - 类的构造器 weka.core.Debug.SimpleLog
-
Creates a logger that writes into the specified file.
- SimpleLog(String, boolean) - 类的构造器 weka.core.Debug.SimpleLog
-
Creates a logger that writes into the specified file.
- SimpleLogger() - 类的构造器 weka.gui.beans.FlowRunner.SimpleLogger
- SimpleLogistic - weka.classifiers.functions中的类
-
Classifier for building linear logistic regression models.
- SimpleLogistic() - 类的构造器 weka.classifiers.functions.SimpleLogistic
-
Constructor for creating SimpleLogistic object with standard options.
- SimpleLogistic(int, boolean, boolean) - 类的构造器 weka.classifiers.functions.SimpleLogistic
-
Constructor for creating SimpleLogistic object.
- SimpleMI - weka.classifiers.mi中的类
-
Reduces MI data into mono-instance data.
- SimpleMI() - 类的构造器 weka.classifiers.mi.SimpleMI
- SimpleSetupPanel - weka.gui.experiment中的类
-
This panel controls the configuration of an experiment.
- SimpleSetupPanel() - 类的构造器 weka.gui.experiment.SimpleSetupPanel
-
Creates the setup panel with no initial experiment.
- SimpleSetupPanel(Experiment) - 类的构造器 weka.gui.experiment.SimpleSetupPanel
-
Creates the setup panel with the supplied initial experiment.
- SimpleStreamFilter - weka.filters中的类
-
This filter is a superclass for simple stream filters.
- SimpleStreamFilter() - 类的构造器 weka.filters.SimpleStreamFilter
- SimulatedAnnealing - weka.classifiers.bayes.net.search.global中的类
-
This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure.
For more information see:
R.R. - SimulatedAnnealing - weka.classifiers.bayes.net.search.local中的类
-
This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure.
For more information see:
R.R. - SimulatedAnnealing() - 类的构造器 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- SimulatedAnnealing() - 类的构造器 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- SIN - 接口中的静态变量 weka.core.mathematicalexpression.sym
- SIN - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- SINE - 类中的静态变量 weka.datagenerators.clusterers.BIRCHCluster
-
Constant set for choice of pattern.
- SingleAssociatorEnhancer - weka.associations中的类
-
Abstract utility class for handling settings common to meta associators that use a single base associator.
- SingleAssociatorEnhancer() - 类的构造器 weka.associations.SingleAssociatorEnhancer
- SingleClassifierEnhancer - weka.classifiers中的类
-
Abstract utility class for handling settings common to meta classifiers that use a single base learner.
- SingleClassifierEnhancer() - 类的构造器 weka.classifiers.SingleClassifierEnhancer
- SingleClustererEnhancer - weka.clusterers中的类
-
Meta-clusterer for enhancing a base clusterer.
- SingleClustererEnhancer() - 类的构造器 weka.clusterers.SingleClustererEnhancer
- singleConsequence(Instances) - 类中的静态方法 weka.associations.CaRuleGeneration
-
generates a consequence of length 1 for a class association rule.
- singleConsequence(Instances, int, FastVector) - 类中的静态方法 weka.associations.RuleGeneration
-
generates a consequence of length 1 for an association rule.
- SingleIndex - weka.core中的类
-
Class representing a single cardinal number.
- SingleIndex() - 类的构造器 weka.core.SingleIndex
-
Default constructor.
- SingleIndex(String) - 类的构造器 weka.core.SingleIndex
-
Constructor to set initial index.
- singletons(Instances) - 类中的静态方法 weka.associations.AprioriItemSet
-
Converts the header info of the given set of instances into a set of item sets (singletons).
- singletons(Instances) - 类中的静态方法 weka.associations.CaRuleGeneration
-
Converts the header info of the given set of instances into a set of item sets (singletons).
- singletons(Instances) - 类中的静态方法 weka.associations.ItemSet
-
Converts the header info of the given set of instances into a set of item sets (singletons).
- singletons(Instances, Instances) - 类中的静态方法 weka.associations.LabeledItemSet
-
Converts the header info of the given set of instances into a set of item sets (singletons).
- SINGULAR_DUMMY - 接口中的静态变量 weka.gui.graphvisualizer.GraphConstants
-
SINGULAR_DUMMY node - node with only one outgoing edge i.e.
- SingularValueDecomposition - weka.core.matrix中的类
-
Singular Value Decomposition.
- SingularValueDecomposition(Matrix) - 类的构造器 weka.core.matrix.SingularValueDecomposition
-
Construct the singular value decomposition
- size() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- size() - 类中的方法 weka.classifiers.CostMatrix
-
The number of rows (and columns)
- size() - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Gets the number of classes.
- size() - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Returns the size of the point set.
- size() - 类中的方法 weka.classifiers.lazy.kstar.KStarCache.CacheTable
-
Returns the number of keys in this hashtable.
- size() - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
the number of antecedents of the rule
- size() - 类中的方法 weka.classifiers.rules.Rule
-
The size of the rule.
- size() - 接口中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.Database
-
Returns the size of the database (the number of dataObjects in the database)
- size() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
-
Returns the size of the database (the number of dataObjects in the database)
- size() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue
-
Returns the queue's size
- size() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue
-
Returns the queue's size
- size() - 类中的方法 weka.core.FastVector
-
Returns the vector's current size.
- size() - 类中的方法 weka.core.matrix.DoubleVector
-
Gets the size of the vector.
- size() - 类中的方法 weka.core.matrix.IntVector
-
Gets the size of the vector.
- size() - 类中的方法 weka.core.PropertyPath.Path
-
returns the number of path elements of this structure
- size() - 类中的方法 weka.core.Queue
-
Gets queue's size.
- size() - 类中的方法 weka.core.Tee
-
returns the number of streams currently in the list.
- size() - 类中的方法 weka.core.Trie
-
Returns the number of elements in this collection.
- size() - 类中的方法 weka.core.Trie.TrieNode
-
returns the number of stored strings, i.e., leaves
- size() - 类中的方法 weka.core.xml.MethodHandler
-
returns the number of currently stored Methods
- SIZE - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The physical dimensions of a work.
- sizePerTipText() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the tip text for this property
- sizePerTipText() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns the tip text for this property
- skipIdenticalTipText() - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Returns the tip text for this property.
- SlidingMidPointOfWidestSide - weka.core.neighboursearch.kdtrees中的类
-
The class that splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.
- SlidingMidPointOfWidestSide() - 类的构造器 weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
- sm(double, double) - 类中的静态方法 weka.core.Utils
-
Tests if a is smaller than b.
- SMALL - 类中的静态变量 weka.core.Utils
-
The small deviation allowed in double comparisons.
- SMO - weka.classifiers.functions中的类
-
Implements John Platt's sequential minimal optimization algorithm for training a support vector classifier.
This implementation globally replaces all missing values and transforms nominal attributes into binary ones. - SMO() - 类的构造器 weka.classifiers.functions.SMO
- SMO.BinarySMO - weka.classifiers.functions中的类
-
Class for building a binary support vector machine.
- smoothingParameterTipText() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Returns the tip text for this property
- SMOreg - weka.classifiers.functions中的类
-
SMOreg implements the support vector machine for regression.
- SMOreg() - 类的构造器 weka.classifiers.functions.SMOreg
- smOrEq(double, double) - 类中的静态方法 weka.core.Utils
-
Tests if a is smaller or equal to b.
- SMOset - weka.classifiers.functions.supportVector中的类
-
Stores a set of integer of a given size.
- SMOset(int) - 类的构造器 weka.classifiers.functions.supportVector.SMOset
-
Creates a new set of the given size.
- SMOTE - weka.filters.supervised.instance中的类
-
Resamples a dataset by applying the Synthetic Minority Oversampling TEchnique (SMOTE).
- SMOTE() - 类的构造器 weka.filters.supervised.instance.SMOTE
- SNAPSHOT - 类中的静态变量 weka.core.Version
-
True if snapshot
- SnowballStemmer - weka.core.stemmers中的类
-
A wrapper class for the Snowball stemmers.
- SnowballStemmer() - 类的构造器 weka.core.stemmers.SnowballStemmer
-
initializes the stemmer ("porter").
- SnowballStemmer(String) - 类的构造器 weka.core.stemmers.SnowballStemmer
-
initializes the stemmer with the given stemmer.
- solve(double[]) - 类中的方法 weka.core.Matrix
-
已过时。Solve A*X = B using backward substitution.
- solve(Matrix) - 类中的方法 weka.core.matrix.CholeskyDecomposition
-
Solve A*X = B
- solve(Matrix) - 类中的方法 weka.core.matrix.LUDecomposition
-
Solve A*X = B
- solve(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Solve A*X = B
- solve(Matrix) - 类中的方法 weka.core.matrix.QRDecomposition
-
Least squares solution of A*X = B
- solveTranspose(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Solve X*A = B, which is also A'*X' = B'
- solveTriangle(Matrix, double[], boolean, boolean[]) - 类中的静态方法 weka.core.Optimization
-
Solve the linear equation of TX=B where T is a triangle matrix It can be solved using back/forward substitution, with O(N^2) complexity
- sort() - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Sorts the point values of the discrete function.
- sort() - 类中的方法 weka.core.matrix.DoubleVector
-
Sorts the array in place
- sort() - 类中的方法 weka.core.matrix.IntVector
-
Sorts the elements in place
- sort(double[]) - 类中的静态方法 weka.core.Utils
-
Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
- sort(int) - 类中的方法 weka.core.Instances
-
Sorts the instances based on an attribute.
- sort(int) - 类中的方法 weka.gui.SortedTableModel
-
sorts the table over the given column (ascending)
- sort(int[]) - 类中的静态方法 weka.core.Utils
-
Sorts a given array of integers in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
- sort(int, boolean) - 类中的方法 weka.gui.SortedTableModel
-
sorts the table over the given column, either ascending or descending
- sort(Comparator) - 类中的方法 weka.associations.tertius.SimpleLinkedList
- sort(Attribute) - 类中的方法 weka.core.Instances
-
Sorts the instances based on an attribute.
- sortArray(double[]) - 类中的方法 weka.classifiers.mi.MIOptimalBall
-
Sort the array.
- sortClassesByRoot(String) - 类中的静态方法 weka.gui.GenericObjectEditor
-
parses the given string of classes separated by ", " and returns the a hashtable with as many entries as there are different root elements in the class names (the key is the root element).
- SortContainer(Comparable, int) - 类的构造器 weka.gui.SortedTableModel.SortContainer
-
Initializes the container.
- SortedTableModel - weka.gui中的类
-
Represents a TableModel with sorting functionality.
- SortedTableModel() - 类的构造器 weka.gui.SortedTableModel
-
initializes with no model
- SortedTableModel(TableModel) - 类的构造器 weka.gui.SortedTableModel
-
initializes with the given model
- SortedTableModel.SortContainer - weka.gui中的类
-
Helper class for sorting the columns.
- sortInstances() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
sorts the instances via the currently selected column
- sortInstances() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
sorts the current selected attribute
- sortInstances(int) - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
sorts the instances via the given attribute
- sortInstances(int) - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
sorts the instances via the given attribute
- sortTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddValues
-
Returns the tip text for this property
- sortWithIndex() - 类中的方法 weka.core.matrix.DoubleVector
-
Sorts the array in place with index returned
- sortWithIndex(int, int, IntVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Sorts the array in place with index changed
- sortWithNoMissingValues(double[]) - 类中的静态方法 weka.core.Utils
-
Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
- Sourcable - weka.classifiers中的接口
-
Interface for classifiers that can be converted to Java source.
- Sourcable - weka.filters中的接口
-
Interface for filters that can be converted to Java source.
- sourceClass(int, Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
- sourceExpression(int, Instances) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Returns a string containing java source code equivalent to the test made at this node.
- sourceExpression(int, Instances) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns a string containing java source code equivalent to the test made at this node.
- sourceExpression(int, Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
- sourceExpression(int, Instances) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
Returns a string containing java source code equivalent to the test made at this node.
- sourceExpression(int, Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Returns a string containing java source code equivalent to the test made at this node.
- sourceExpression(int, Instances) - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Returns a string containing java source code equivalent to the test made at this node.
- sourceExpression(int, Instances) - 类中的方法 weka.classifiers.trees.j48.NoSplit
-
Returns a string containing java source code equivalent to the test made at this node.
- sourceExpression(int, Instances) - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Method not in use
- SOUTH_CONNECTOR - 类中的静态变量 weka.gui.beans.BeanVisual
- spaceHorizontal(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
space out set of nodes evenly between left and right most node in the list
- spaceVertical(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
space out set of nodes evenly between top and bottom most node in the list
- SPARSE1 - 类中的静态变量 weka.filters.unsupervised.attribute.RandomProjection
-
distribution type: sparse 1
- SPARSE2 - 类中的静态变量 weka.filters.unsupervised.attribute.RandomProjection
-
distribution type: sparse 2
- sparseDataTipText() - 类中的方法 weka.experiment.InstanceQuery
-
Returns the tip text for this property
- sparseIndices() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the indices in sparse format.
- sparseIndices() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the indices in sparse format.
- SparseInstance - weka.core中的类
-
Class for storing an instance as a sparse vector.
- SparseInstance(double, double[]) - 类的构造器 weka.core.SparseInstance
-
Constructor that generates a sparse instance from the given parameters.
- SparseInstance(double, double[], int[], int) - 类的构造器 weka.core.SparseInstance
-
Constructor that inititalizes instance variable with given values.
- SparseInstance(int) - 类的构造器 weka.core.SparseInstance
-
Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.
- SparseInstance(Instance) - 类的构造器 weka.core.SparseInstance
-
Constructor that generates a sparse instance from the given instance.
- SparseInstance(SparseInstance) - 类的构造器 weka.core.SparseInstance
-
Constructor that copies the info from the given instance.
- SparseToNonSparse - weka.filters.unsupervised.instance中的类
-
An instance filter that converts all incoming sparse instances into non-sparse format.
- SparseToNonSparse() - 类的构造器 weka.filters.unsupervised.instance.SparseToNonSparse
- sparseWeights() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the weights in sparse format.
- sparseWeights() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the weights in sparse format.
- SpecialFunctions - weka.core中的类
-
Class implementing some mathematical functions.
- SpecialFunctions() - 类的构造器 weka.core.SpecialFunctions
- SPECIFIC_VALUE - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
- SPegasos - weka.classifiers.functions中的类
-
Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al.
- SPegasos() - 类的构造器 weka.classifiers.functions.SPegasos
- sphere - 类中的变量 weka.classifiers.lazy.kstar.KStarWrapper
-
used/reused to hold the sphere size
- splash(Image) - 类中的静态方法 weka.gui.SplashWindow
-
Open's a splash window using the specified image.
- splash(URL) - 类中的静态方法 weka.gui.SplashWindow
-
Open's a splash window using the specified image.
- SplashWindow - weka.gui中的类
-
A Splash window.
- split() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Finds an attribute and split point for this node
- split(Instances) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Splits the given set of instances into subsets.
- splitAtt() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the index of the splitting attribute for this node
- splitAttr() - 类中的方法 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Returns the attribute used in this split
- splitAttr() - 接口中的方法 weka.classifiers.trees.m5.SplitEvaluate
-
Returns the attribute used in this split
- splitAttr() - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Returns the attribute used in this split
- SplitCriterion - weka.classifiers.trees.j48中的类
-
Abstract class for computing splitting criteria with respect to distributions of class values.
- SplitCriterion() - 类的构造器 weka.classifiers.trees.j48.SplitCriterion
- splitCritValue(Distribution) - 类中的方法 weka.classifiers.trees.j48.EntropySplitCrit
-
Computes entropy for given distribution.
- splitCritValue(Distribution) - 类中的方法 weka.classifiers.trees.j48.GainRatioSplitCrit
-
This method is a straightforward implementation of the gain ratio criterion for the given distribution.
- splitCritValue(Distribution) - 类中的方法 weka.classifiers.trees.j48.InfoGainSplitCrit
-
This method is a straightforward implementation of the information gain criterion for the given distribution.
- splitCritValue(Distribution) - 类中的方法 weka.classifiers.trees.j48.SplitCriterion
-
Computes result of splitting criterion for given distribution.
- splitCritValue(Distribution, double) - 类中的方法 weka.classifiers.trees.j48.InfoGainSplitCrit
-
This method computes the information gain in the same way C4.5 does.
- splitCritValue(Distribution, double, double) - 类中的方法 weka.classifiers.trees.j48.GainRatioSplitCrit
-
This method computes the gain ratio in the same way C4.5 does.
- splitCritValue(Distribution, double, double) - 类中的方法 weka.classifiers.trees.j48.InfoGainSplitCrit
-
This method computes the information gain in the same way C4.5 does.
- splitCritValue(Distribution, Distribution) - 类中的方法 weka.classifiers.trees.j48.EntropySplitCrit
-
Computes entropy of test distribution with respect to training distribution.
- splitCritValue(Distribution, Distribution) - 类中的方法 weka.classifiers.trees.j48.SplitCriterion
-
Computes result of splitting criterion for given training and test distributions.
- splitCritValue(Distribution, Distribution, int) - 类中的方法 weka.classifiers.trees.j48.SplitCriterion
-
Computes result of splitting criterion for given training and test distributions and given number of classes.
- splitCritValue(Distribution, Distribution, Distribution) - 类中的方法 weka.classifiers.trees.j48.SplitCriterion
-
Computes result of splitting criterion for given training and test distributions and given default distribution.
- splitData(Instances, double, double) - 类中的方法 weka.classifiers.rules.JRip.Antd
- splitData(Instances, double, double) - 类中的方法 weka.classifiers.rules.JRip.NominalAntd
-
Implements the splitData function.
- splitData(Instances, double, double) - 类中的方法 weka.classifiers.rules.JRip.NumericAntd
-
Implements the splitData function.
- splitEnt(Distribution) - 类中的方法 weka.classifiers.trees.j48.EntropyBasedSplitCrit
-
Computes entropy after splitting without considering the class values.
- SplitEvaluate - weka.classifiers.trees.m5中的接口
-
Interface for objects that determine a split point on an attribute
- SplitEvaluator - weka.experiment中的接口
-
Interface to objects able to generate a fixed set of results for a particular split of a dataset.
- splitEvaluatorTipText() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Returns the tip text for this property
- splitEvaluatorTipText() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns the tip text for this property
- splitItemSet(int, int[]) - 类中的方法 weka.associations.PriorEstimation
-
splits an item set into premise and consequence and constructs therefore an association rule.
- splitNode(BallNode, int) - 类中的方法 weka.core.neighboursearch.balltrees.BallSplitter
-
Splits a node into two.
- splitNode(BallNode, int) - 类中的方法 weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint
-
Splits a ball into two.
- splitNode(BallNode, int) - 类中的方法 weka.core.neighboursearch.balltrees.MedianOfWidestDimension
-
Splits a ball into two.
- splitNode(BallNode, int) - 类中的方法 weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren
-
Splits a ball into two.
- splitNode(KDTreeNode, int, double[][], double[][]) - 类中的方法 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Splits a node into two.
- splitNode(KDTreeNode, int, double[][], double[][]) - 类中的方法 weka.core.neighboursearch.kdtrees.KMeansInpiredMethod
-
Splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.
- splitNode(KDTreeNode, int, double[][], double[][]) - 类中的方法 weka.core.neighboursearch.kdtrees.MedianOfWidestDimension
-
Splits a node into two based on the median value of the dimension in which the points have the widest spread.
- splitNode(KDTreeNode, int, double[][], double[][]) - 类中的方法 weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension
-
Splits a node into two based on the midpoint value of the dimension in which the points have the widest spread.
- splitNode(KDTreeNode, int, double[][], double[][]) - 类中的方法 weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
Splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.
- splitOnResidualsTipText() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the tip text for this property
- splitOptions(String) - 类中的静态方法 weka.core.Utils
-
Split up a string containing options into an array of strings, one for each option.
- splitPoint() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- splitPointTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveWithValues
-
Returns the tip text for this property
- Splitter - weka.classifiers.trees.adtree中的类
-
Abstract class representing a splitter node in an alternating tree.
- Splitter() - 类的构造器 weka.classifiers.trees.adtree.Splitter
- splitVal() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Get the split point for this node
- splitValue() - 类中的方法 weka.classifiers.trees.m5.CorrelationSplitInfo
-
Returns the split value
- splitValue() - 接口中的方法 weka.classifiers.trees.m5.SplitEvaluate
-
Returns the split value
- splitValue() - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Returns the split value
- SpreadSubsample - weka.filters.supervised.instance中的类
-
Produces a random subsample of a dataset.
- SpreadSubsample() - 类的构造器 weka.filters.supervised.instance.SpreadSubsample
- sqDifference(int, double, double) - 类中的方法 weka.core.EuclideanDistance
-
Returns the squared difference of two values of an attribute.
- SqlViewer - weka.gui.sql中的类
-
Represents a little tool for querying SQL databases.
- SqlViewer(JFrame) - 类的构造器 weka.gui.sql.SqlViewer
-
initializes the SqlViewer.
- SqlViewerDialog - weka.gui.sql中的类
-
A little dialog containing the SqlViewer.
- SqlViewerDialog(JFrame) - 类的构造器 weka.gui.sql.SqlViewerDialog
-
initializes the dialog
- sqrt() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the square-root of all the elements in the vector
- sqrt() - 类中的方法 weka.core.matrix.Matrix
-
returns the square root of the matrix, i.e., X from the equation X*X = A.
Steps in the Calculation (seesqrtm
in Matlab):
perform eigenvalue decomposition
[V,D]=eig(A) take the square root of all elements in D (only the ones with positive sign are considered for further computation)
S=sqrt(D) calculate the root
X=V*S/V, which can be also written as X=(V'\(V*S)')' - SQRT - 接口中的静态变量 weka.core.mathematicalexpression.sym
- SQRT - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- square() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the squared vector
- square(double) - 类中的静态方法 weka.core.matrix.Maths
-
Returns the square of a value
- stableSort(double[]) - 类中的静态方法 weka.core.Utils
-
Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
- Stack<T> - weka.core.neighboursearch.covertrees中的类
-
Class implementing a stack.
- Stack() - 类的构造器 weka.core.neighboursearch.covertrees.Stack
-
Constructor.
- Stack(int) - 类的构造器 weka.core.neighboursearch.covertrees.Stack
-
Constructor.
- Stacking - weka.classifiers.meta中的类
-
Combines several classifiers using the stacking method.
- Stacking() - 类的构造器 weka.classifiers.meta.Stacking
- StackingC - weka.classifiers.meta中的类
-
Implements StackingC (more efficient version of stacking).
For more information, see
A.K. - StackingC() - 类的构造器 weka.classifiers.meta.StackingC
-
The constructor.
- Standardize - weka.filters.unsupervised.attribute中的类
-
Standardizes all numeric attributes in the given dataset to have zero mean and unit variance (apart from the class attribute, if set).
- Standardize() - 类的构造器 weka.filters.unsupervised.attribute.Standardize
- start() - 类中的方法 weka.core.Debug.Clock
-
saves the current system time (or CPU time) in msec as start time
- start() - 类中的方法 weka.gui.beans.Loader
-
Start loading
- start() - 接口中的方法 weka.gui.beans.Startable
-
Start the flow running
- start() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Start the plotting thread
- start() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanelDistributed
-
Start processing
- start_production() - 类中的方法 weka.core.mathematicalexpression.Parser
-
Indicates start production.
- start_production() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Indicates start production.
- start_state() - 类中的方法 weka.core.mathematicalexpression.Parser
-
Indicates start state.
- start_state() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Parser
-
Indicates start state.
- Startable - weka.gui.beans中的接口
-
Interface to something that is a start point for a flow and can be launched programatically.
- startApp() - 类中的静态方法 weka.gui.beans.KnowledgeFlow
-
Static method that can be called from a running program to launch the KnowledgeFlow
- startClock() - 类中的方法 weka.core.Debug
-
starts the clock
- startLoading() - 类中的方法 weka.gui.beans.Loader
-
Start loading data
- startPlotThread() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Starts the plotting thread.
- startPointTipText() - 类中的方法 weka.attributeSelection.RankSearch
-
Returns the tip text for this property
- StartSetHandler - weka.attributeSelection中的接口
-
Interface for search methods capable of doing something sensible given a starting set of attributes.
- startSetTipText() - 类中的方法 weka.attributeSelection.BestFirst
-
Returns the tip text for this property
- startSetTipText() - 类中的方法 weka.attributeSelection.GeneticSearch
-
Returns the tip text for this property
- startSetTipText() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns the tip text for this property
- startSetTipText() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the tip text for this property
- startSetTipText() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns the tip text for this property
- startSetTipText() - 类中的方法 weka.attributeSelection.Ranker
-
Returns the tip text for this property
- startUpComplete() - 接口中的方法 weka.gui.beans.StartUpListener
- StartUpListener - weka.gui.beans中的接口
-
Interface to something that can be notified of a successful startup
- stateChanged(ChangeEvent) - 类中的方法 weka.gui.arffviewer.ArffPanel
-
Invoked when the target of the listener has changed its state.
- stateChanged(ChangeEvent) - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
Invoked when the target of the listener has changed its state.
- stateChanged(ChangeEvent) - 类中的方法 weka.gui.LogWindow
-
Invoked when the target of the listener has changed its state.
- stateChanged(ChangeEvent) - 类中的方法 weka.gui.sql.ResultPanel
-
Invoked when the target of the listener has changed its state.
- stateChanged(ChangeEvent) - 类中的方法 weka.gui.ViewerDialog
-
Invoked when the target of the listener has changed its state.
- Statistics - weka.core中的类
-
Class implementing some distributions, tests, etc.
- Statistics() - 类的构造器 weka.core.Statistics
- Stats - weka.classifiers.trees.j48中的类
-
Class implementing a statistical routine needed by J48 to compute its error estimate.
- Stats - weka.experiment中的类
-
A class to store simple statistics
- Stats() - 类的构造器 weka.classifiers.trees.j48.Stats
- Stats() - 类的构造器 weka.experiment.Stats
- statusFrequencyTipText() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Return a tip text string for this property
- statusMessage(String) - 类中的方法 weka.gui.beans.FlowRunner.SimpleLogger
- statusMessage(String) - 类中的方法 weka.gui.beans.LogPanel
-
Sends the supplied message to the status area.
- statusMessage(String) - 接口中的方法 weka.gui.Logger
-
Sends the supplied message to the status line.
- statusMessage(String) - 类中的方法 weka.gui.LogPanel
-
Sends the supplied message to the status line.
- statusMessage(String) - 类中的方法 weka.gui.SysErrLog
-
Sends the supplied message to the status line.
- stdDev - 类中的变量 weka.experiment.Stats
-
The std deviation of values at the last calculateDerived() call
- stealPoints(MiddleOutConstructor.TempNode, Vector, Vector) - 类中的方法 weka.core.neighboursearch.balltrees.MiddleOutConstructor
-
Removes points from old anchors that are nearer to the given new anchor and adds them to the list of points of the new anchor.
- stem(String) - 类中的方法 weka.core.stemmers.IteratedLovinsStemmer
-
Iterated stemming of the given word.
- stem(String) - 类中的方法 weka.core.stemmers.LovinsStemmer
-
Returns the stemmed version of the given word.
- stem(String) - 类中的方法 weka.core.stemmers.NullStemmer
-
Returns the word as it is.
- stem(String) - 类中的方法 weka.core.stemmers.SnowballStemmer
-
Returns the word in its stemmed form.
- stem(String) - 接口中的方法 weka.core.stemmers.Stemmer
-
Stems the given word and returns the stemmed version
- Stemmer - weka.core.stemmers中的接口
-
Interface for all stemming algorithms.
- stemmerTipText() - 类中的方法 weka.core.stemmers.SnowballStemmer
-
Returns the tip text for this property.
- stemmerTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- Stemming - weka.core.stemmers中的类
-
A helper class for using the stemmers.
- Stemming() - 类的构造器 weka.core.stemmers.Stemming
- stemString(String) - 类中的方法 weka.core.stemmers.LovinsStemmer
-
Stems everything in the given string.
- STEP_FIELD_NAME - 类中的静态变量 weka.experiment.LearningRateResultProducer
-
The name of the key field containing the learning rate step number
- steplsqr(PaceMatrix, IntVector, int, int, boolean) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Stepwise least squares QR-decomposition of the problem A x = b
- stepSizeTipText() - 类中的方法 weka.attributeSelection.RankSearch
-
Returns the tip text for this property
- stepSizeTipText() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns the tip text for this property
- stop() - 类中的方法 weka.core.Debug.Clock
-
saves the current system (or CPU time) in msec as stop time
- stop() - 类中的方法 weka.gui.beans.AbstractDataSink
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.Associator
-
Stop any associator action
- stop() - 接口中的方法 weka.gui.beans.BeanCommon
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.ClassAssigner
- stop() - 类中的方法 weka.gui.beans.Classifier
-
Stop any classifier action
- stop() - 类中的方法 weka.gui.beans.ClassifierPerformanceEvaluator
-
Try and stop any action
- stop() - 类中的方法 weka.gui.beans.ClassValuePicker
- stop() - 类中的方法 weka.gui.beans.Clusterer
-
Stop any clusterer action
- stop() - 类中的方法 weka.gui.beans.ClustererPerformanceEvaluator
-
Try and stop any action
- stop() - 类中的方法 weka.gui.beans.CostBenefitAnalysis
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.CrossValidationFoldMaker
-
Stop any action
- stop() - 类中的方法 weka.gui.beans.Filter
-
Stop all action if possible
- stop() - 类中的方法 weka.gui.beans.IncrementalClassifierEvaluator
-
Stop all action
- stop() - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Stop any action (if possible).
- stop() - 类中的方法 weka.gui.beans.Loader
-
Stop any loading action.
- stop() - 类中的方法 weka.gui.beans.MetaBean
-
Stop all encapsulated beans
- stop() - 类中的方法 weka.gui.beans.PredictionAppender
- stop() - 类中的方法 weka.gui.beans.Saver
-
Stops the bean
- stop() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.StripChart
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.TestSetMaker
- stop() - 类中的方法 weka.gui.beans.TextViewer
-
Stop any processing that the bean might be doing.
- stop() - 类中的方法 weka.gui.beans.TrainingSetMaker
-
Stop any action
- stop() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Stop processing
- STOP - 类中的静态变量 weka.core.Trie.TrieNode
-
the stop character
- stopAllFlows() - 类中的方法 weka.gui.beans.FlowRunner
- stopClock(String) - 类中的方法 weka.core.Debug
-
stops the clock and prints the message associated with the time, but only if the logging is enabled.
- stopMonitoring() - 类中的方法 weka.gui.MemoryUsagePanel
-
stops the monitoring thread.
- stoppingCriterion() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
This method implements the stopping criterion function.
- stopPlotting() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryPanel
-
Stop the plotting thread
- stopPlotting() - 类中的方法 weka.gui.boundaryvisualizer.BoundaryVisualizer
-
Stops the plotting thread.
- stopThreads() - 类中的方法 weka.core.Memory
-
stops all the current threads, to make a restart possible
- Stopwords - weka.core中的类
-
Class that can test whether a given string is a stop word.
- Stopwords() - 类的构造器 weka.core.Stopwords
-
initializes the stopwords (based on Rainbow).
- stopwordsTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- store(double, double, double) - 类中的方法 weka.classifiers.lazy.kstar.KStarCache
-
Stores the specified values in the cahce table for easy retrieval.
- StratifiedRemoveFolds - weka.filters.supervised.instance中的类
-
This filter takes a dataset and outputs a specified fold for cross validation.
- StratifiedRemoveFolds() - 类的构造器 weka.filters.supervised.instance.StratifiedRemoveFolds
- stratify(int) - 类中的方法 weka.core.Instances
-
Stratifies a set of instances according to its class values if the class attribute is nominal (so that afterwards a stratified cross-validation can be performed).
- stratify(Instances, int, Random) - 类中的静态方法 weka.classifiers.rules.RuleStats
-
Stratify the given data into the given number of bags based on the class values.
- StreamableFilter - weka.filters中的接口
-
Interface for filters can work with a stream of instances.
- STRING - 类中的静态变量 weka.core.Attribute
-
Constant set for attributes with string values.
- STRING - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for STRING used for reading experiment results.
- STRING - 类中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
lexical states
- STRING - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- STRING_ATTRIBUTES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle string attributes
- STRING_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle string classes
- stringAttributesTipText() - 类中的方法 weka.core.converters.CSVLoader
-
Returns the tip text for this property.
- StringCompare() - 类的构造器 weka.core.ClassDiscovery.StringCompare
- stringFreeStructure() - 类中的方法 weka.core.Instances
-
Create a copy of the structure if the data has string or relational attributes, "cleanses" string types (i.e.
- StringKernel - weka.classifiers.functions.supportVector中的类
-
Implementation of the subsequence kernel (SSK) as described in [1] and of the subsequence kernel with lambda pruning (SSK-LP) as described in [2].
For more information, see
Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Christopher J. - StringKernel() - 类的构造器 weka.classifiers.functions.supportVector.StringKernel
-
default constructor
- StringKernel(Instances, int, int, double, boolean) - 类的构造器 weka.classifiers.functions.supportVector.StringKernel
-
creates a new StringKernel object.
- StringLocator - weka.core中的类
-
This class locates and records the indices of String attributes, recursively in case of Relational attributes.
- StringLocator(Instances) - 类的构造器 weka.core.StringLocator
-
initializes the StringLocator with the given data
- StringLocator(Instances, int[]) - 类的构造器 weka.core.StringLocator
-
Initializes the AttributeLocator with the given data.
- StringLocator(Instances, int, int) - 类的构造器 weka.core.StringLocator
-
Initializes the StringLocator with the given data.
- stringSize(FontMetrics) - 类中的方法 weka.gui.treevisualizer.Edge
-
This will calculate how large a rectangle using the FontMetrics passed that the lines of the label will take up
- stringSize(FontMetrics) - 类中的方法 weka.gui.treevisualizer.Node
-
This will return the width and height of the rectangle that the text will fit into.
- stringToLevel(String) - 类中的静态方法 weka.core.Debug.Log
-
turns the string representing a level, e.g., "FINE" or "ALL" into the corresponding level (case-insensitive).
- stringToLevel(String) - 类中的静态方法 weka.core.Debug
-
turns the string representing a level, e.g., "FINE" or "ALL" into the corresponding level (case-insensitive).
- StringToNominal - weka.filters.unsupervised.attribute中的类
-
Converts a string attribute (i.e.
- StringToNominal() - 类的构造器 weka.filters.unsupervised.attribute.StringToNominal
- StringToWordVector - weka.filters.unsupervised.attribute中的类
-
Converts String attributes into a set of attributes representing word occurrence (depending on the tokenizer) information from the text contained in the strings.
- StringToWordVector() - 类的构造器 weka.filters.unsupervised.attribute.StringToWordVector
-
Default constructor.
- StringToWordVector(int) - 类的构造器 weka.filters.unsupervised.attribute.StringToWordVector
-
Constructor that allows specification of the target number of words in the output.
- stringValue(int) - 类中的方法 weka.core.Instance
-
Returns the value of a nominal, string, date, or relational attribute for the instance as a string.
- stringValue(Attribute) - 类中的方法 weka.core.Instance
-
Returns the value of a nominal, string, date, or relational attribute for the instance as a string.
- StripChart - weka.gui.beans中的类
-
Bean that can display a horizontally scrolling strip chart.
- StripChart() - 类的构造器 weka.gui.beans.StripChart
- StripChartBeanInfo - weka.gui.beans中的类
-
Bean info class for the strip chart bean
- StripChartBeanInfo() - 类的构造器 weka.gui.beans.StripChartBeanInfo
- StripChartCustomizer - weka.gui.beans中的类
-
GUI Customizer for the strip chart bean
- StripChartCustomizer() - 类的构造器 weka.gui.beans.StripChartCustomizer
- StructureProducer - weka.gui.beans中的接口
-
Interface for something that can describe the structure of what is encapsulated in a named event type as an empty set of Instances (i.e.
- STYLE_STDERR - 类中的静态变量 weka.gui.LogWindow
-
the name of the style for stderr
- STYLE_STDOUT - 类中的静态变量 weka.gui.LogWindow
-
the name of the style for stdout
- sub(int, Instance) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Subtracts given instance from given bag.
- subFlowContains(BeanInstance) - 类中的方法 weka.gui.beans.MetaBean
- subList(int, int) - 类中的方法 weka.core.neighboursearch.covertrees.Stack
-
Returns a sublist of the elements in the stack.
- subpath(int) - 类中的方法 weka.core.PropertyPath.Path
-
returns a subpath of the current structure, starting with the specified element index up to the end
- subpath(int, int) - 类中的方法 weka.core.PropertyPath.Path
-
returns a subpath of the current structure, starting with the specified element index up.
- subsequenceLengthTipText() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the tip text for this property
- Subset(BitSet, double) - 类的构造器 weka.attributeSelection.ScatterSearchV1.Subset
- SubsetByExpression - weka.filters.unsupervised.instance中的类
-
Filters instances according to a user-specified expression.
Grammar:
boolexpr_list ::= boolexpr_list boolexpr_part | boolexpr_part;
boolexpr_part ::= boolexpr:e {: parser.setResult(e); :} ;
boolexpr ::= BOOLEAN
| true
| false
| expr < expr
| expr <= expr
| expr > expr
| expr >= expr
| expr = expr
| ( boolexpr )
| not boolexpr
| boolexpr and boolexpr
| boolexpr or boolexpr
| ATTRIBUTE is STRING
;
expr ::= NUMBER
| ATTRIBUTE
| ( expr )
| opexpr
| funcexpr
;
opexpr ::= expr + expr
| expr - expr
| expr * expr
| expr / expr
;
funcexpr ::= abs ( expr )
| sqrt ( expr )
| log ( expr )
| exp ( expr )
| sin ( expr )
| cos ( expr )
| tan ( expr )
| rint ( expr )
| floor ( expr )
| pow ( expr for base , expr for exponent )
| ceil ( expr )
;
Notes:
- NUMBER
any integer or floating point number
(but not in scientific notation!)
- STRING
any string surrounded by single quotes;
the string may not contain a single quote though.
- ATTRIBUTE
the following placeholders are recognized for
attribute values:
- CLASS for the class value in case a class attribute is set.
- ATTxyz with xyz a number from 1 to # of attributes in the
dataset, representing the value of indexed attribute.
Examples:
- extracting only mammals and birds from the 'zoo' UCI dataset:
(CLASS is 'mammal') or (CLASS is 'bird')
- extracting only animals with at least 2 legs from the 'zoo' UCI dataset:
(ATT14 >= 2)
- extracting only instances with non-missing 'wage-increase-second-year'
from the 'labor' UCI dataset:
not ismissing(ATT3) - SubsetByExpression() - 类的构造器 weka.filters.unsupervised.instance.SubsetByExpression
- subsetDL(double, double, double) - 类中的静态方法 weka.classifiers.rules.RuleStats
-
Subset description length:
S(t,k,p) = -k*log2(p)-(n-k)log2(1-p) Details see Quilan: "MDL and categorical theories (Continued)",ML95 - subsetEstimate(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Returns the estimate of optimal subset selection.
- SubsetEvaluator - weka.attributeSelection中的接口
-
Interface for attribute subset evaluators.
- subsetEvaluatorTipText() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Returns the tip text for this property
- subsetOfInterest() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- subsetSizeEvaluatorTipText() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the tip text for this property
- SubsetSizeForwardSelection - weka.attributeSelection中的类
-
SubsetSizeForwardSelection:
Extension of LinearForwardSelection. - SubsetSizeForwardSelection() - 类的构造器 weka.attributeSelection.SubsetSizeForwardSelection
-
Constructor
- SubspaceCluster - weka.datagenerators.clusterers中的类
-
A data generator that produces data points in hyperrectangular subspace clusters.
- SubspaceCluster() - 类的构造器 weka.datagenerators.clusterers.SubspaceCluster
-
initializes the generator, sets the number of clusters to 0, since user has to specify them explicitly
- SubspaceClusterDefinition - weka.datagenerators.clusterers中的类
-
A single cluster for the SubspaceCluster datagenerator
- SubspaceClusterDefinition() - 类的构造器 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
initializes the cluster, without a parent cluster (necessary for GOE)
- SubspaceClusterDefinition(ClusterGenerator) - 类的构造器 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
initializes the cluster with default values
- subSpaceSizeTipText() - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Returns the tip text for this property
- substitute(String) - 类中的方法 weka.core.Environment
-
Substitute a variable names for their values in the given string.
- substract(AlgVector) - 类中的方法 weka.core.AlgVector
-
Returns the difference of this vector minus another.
- subsumes(Rule) - 类中的方法 weka.associations.tertius.Rule
-
Test if this rule subsumes another rule.
- subsumptionTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- subtract(double) - 类中的方法 weka.experiment.Stats
-
Removes a value to the observed values (no checking is done that the value being removed was actually added).
- subtract(double[], double[]) - 类中的方法 weka.experiment.PairedStats
-
Removes an array of observed pair of values.
- subtract(double, double) - 类中的方法 weka.experiment.PairedStats
-
Removes an observed pair of values.
- subtract(double, double) - 类中的方法 weka.experiment.Stats
-
Subtracts a value that has been seen n times from the observed values
- subtract(AprioriItemSet) - 类中的方法 weka.associations.AprioriItemSet
-
Subtracts an item set from another one.
- subtract(Distribution) - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Subtracts the given distribution from this one.
- subtreeRaisingTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- subtreeRaisingTipText() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the tip text for this property
- subvector(int, int) - 类中的方法 weka.core.matrix.DoubleVector
-
Returns a subvector.
- subvector(int, int) - 类中的方法 weka.core.matrix.IntVector
-
Returns a subvector.
- subvector(IntVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Returns a subvector.
- subvector(IntVector) - 类中的方法 weka.core.matrix.IntVector
-
Returns a subvector as indexed by an IntVector.
- SUBVERSION - enum class 中的枚举常量 weka.core.RevisionUtils.Type
-
Subversion.
- sum - 类中的变量 weka.experiment.Stats
-
The sum of values seen
- sum() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the sum of all elements in the vector.
- sum(double[]) - 类中的静态方法 weka.core.Utils
-
Computes the sum of the elements of an array of doubles.
- sum(int[]) - 类中的静态方法 weka.core.Utils
-
Computes the sum of the elements of an array of integers.
- sum2() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns the squared sum of all elements in the vector.
- sum2(boolean) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Squared sum of columns or rows of a matrix
- sum2(int, int, int, boolean) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Squared sum of a column or row in a matrix
- sum2(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Returns ||u-v||^2
- Summarizable - weka.core中的接口
-
Interface to something that provides a short textual summary (as opposed to toString() which is usually a fairly complete description) of itself.
- sumOfWeights() - 类中的方法 weka.core.Instances
-
Computes the sum of all the instances' weights.
- sumSq - 类中的变量 weka.experiment.Stats
-
The sum of values squared seen
- SupervisedFilter - weka.filters中的接口
-
Interface for filters that make use of a class attribute.
- support() - 类中的方法 weka.associations.ItemSet
-
Outputs the support for an item set.
- support() - 类中的方法 weka.associations.LabeledItemSet
-
Outputs the support for an item set.
- supportPoints(DoubleVector, int) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Contructs the set of support points for mixture estimation.
- supportPoints(DoubleVector, int) - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Contructs the set of support points for mixture estimation.
- supportPoints(DoubleVector, int) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Contructs the set of support points for mixture estimation.
- supports(Capabilities) - 类中的方法 weka.core.Capabilities
-
Returns true if the currently set capabilities support at least all of the capabiliites of the given Capabilities object (checks only the enum!)
- supportsCustomEditor() - 类中的方法 weka.gui.CostMatrixEditor
-
Indicates whether the cost matrix can be edited in a GUI, which it can.
- supportsCustomEditor() - 类中的方法 weka.gui.FileEditor
-
Returns true because we do support a custom editor.
- supportsCustomEditor() - 类中的方法 weka.gui.GenericArrayEditor
-
Returns true because we do support a custom editor.
- supportsCustomEditor() - 类中的方法 weka.gui.GenericObjectEditor
-
Returns true because we do support a custom editor.
- supportsCustomEditor() - 类中的方法 weka.gui.SimpleDateFormatEditor
-
Indicates whether the date format can be edited in a GUI, which it can.
- supportsMaybe(Capabilities) - 类中的方法 weka.core.Capabilities
-
Returns true if the currently set capabilities support (or have a dependency) at least all of the capabilities of the given Capabilities object (checks only the enum!)
- svd() - 类中的方法 weka.core.matrix.Matrix
-
Singular Value Decomposition
- SVMAttributeEval - weka.attributeSelection中的类
-
SVMAttributeEval :
Evaluates the worth of an attribute by using an SVM classifier. - SVMAttributeEval() - 类的构造器 weka.attributeSelection.SVMAttributeEval
-
Constructor
- SVMLightLoader - weka.core.converters中的类
-
Reads a source that is in svm light format.
For more information about svm light see:
http://svmlight.joachims.org/ - SVMLightLoader() - 类的构造器 weka.core.converters.SVMLightLoader
- SVMLightSaver - weka.core.converters中的类
-
Writes to a destination that is in svm light format.
For more information about svm light see:
http://svmlight.joachims.org/ - SVMLightSaver() - 类的构造器 weka.core.converters.SVMLightSaver
-
Constructor.
- SVMOutput(int, Instance) - 类中的方法 weka.classifiers.functions.SMO.BinarySMO
-
Computes SVM output for given instance.
- SVMOutput(Instance) - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
- SVMTYPE_C_SVC - 类中的静态变量 weka.classifiers.functions.LibSVM
-
SVM type C-SVC (classification)
- SVMTYPE_EPSILON_SVR - 类中的静态变量 weka.classifiers.functions.LibSVM
-
SVM type epsilon-SVR (regression)
- SVMTYPE_L1LOSS_SVM_DUAL - 类中的静态变量 weka.classifiers.functions.LibLINEAR
-
SVM solver type L1-loss support vector machines (dual)
- SVMTYPE_L2_LR - 类中的静态变量 weka.classifiers.functions.LibLINEAR
-
SVM solver type L2-regularized logistic regression
- SVMTYPE_L2LOSS_SVM - 类中的静态变量 weka.classifiers.functions.LibLINEAR
-
SVM solver type L2-loss support vector machines (primal)
- SVMTYPE_L2LOSS_SVM_DUAL - 类中的静态变量 weka.classifiers.functions.LibLINEAR
-
SVM solver type L2-loss support vector machines (dual)
- SVMTYPE_MCSVM_CS - 类中的静态变量 weka.classifiers.functions.LibLINEAR
-
SVM solver type multi-class support vector machines by Crammer and Singer
- SVMTYPE_NU_SVC - 类中的静态变量 weka.classifiers.functions.LibSVM
-
SVM type nu-SVC (classification)
- SVMTYPE_NU_SVR - 类中的静态变量 weka.classifiers.functions.LibSVM
-
SVM type nu-SVR (regression)
- SVMTYPE_ONE_CLASS_SVM - 类中的静态变量 weka.classifiers.functions.LibSVM
-
SVM type one-class SVM (classification)
- SVMTypeTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- SVMTypeTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- swap(int, int) - 类中的方法 weka.core.FastVector
-
Swaps two elements in the vector.
- swap(int, int) - 类中的方法 weka.core.Instances
-
Swaps two instances in the set.
- swap(int, int) - 类中的方法 weka.core.matrix.DoubleVector
-
Swaps the values stored at i and j
- swap(int, int) - 类中的方法 weka.core.matrix.IntVector
-
Swaps the values stored at i and j
- SwapValues - weka.filters.unsupervised.attribute中的类
-
Swaps two values of a nominal attribute.
- SwapValues() - 类的构造器 weka.filters.unsupervised.attribute.SwapValues
- switchToAdvanced(Experiment) - 类中的方法 weka.gui.experiment.SetupModePanel
-
Switches to the advanced setup mode.
- switchToSimple(Experiment) - 类中的方法 weka.gui.experiment.SetupModePanel
-
Switches to the simple setup mode only if allowed to.
- sym - weka.core.mathematicalexpression中的接口
-
CUP generated interface containing symbol constants.
- sym - weka.filters.unsupervised.instance.subsetbyexpression中的接口
-
CUP generated interface containing symbol constants.
- symmetricalUncertainty(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Calculates the symmetrical uncertainty for base 2.
- SymmetricalUncertAttributeEval - weka.attributeSelection中的类
-
SymmetricalUncertAttributeEval :
Evaluates the worth of an attribute by measuring the symmetrical uncertainty with respect to the class. - SymmetricalUncertAttributeEval() - 类的构造器 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Constructor
- Sync(BayesNet) - 类中的方法 weka.classifiers.bayes.net.BIFReader
-
synchronizes the node ordering of this Bayes network with those in the other network (if possible).
- synopsis() - 类中的方法 weka.core.Option
-
Returns the option's synopsis.
- SysErrLog - weka.gui中的类
-
This Logger just sends messages to System.err.
- SysErrLog() - 类的构造器 weka.gui.SysErrLog
- SystemInfo - weka.core中的类
-
This class prints some information about the system setup, like Java version, JVM settings etc.
- SystemInfo() - 类的构造器 weka.core.SystemInfo
-
initializes the object and reads the system information
T
- TAB_INSTANCES - 类中的静态变量 weka.gui.arffviewer.ArffPanel
-
the name of the tab for instances that were set directly
- tableChanged(TableModelEvent) - 类中的方法 weka.gui.arffviewer.ArffTable
-
This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
- tableChanged(TableModelEvent) - 类中的方法 weka.gui.SortedTableModel
-
This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
- TableEntry(int, double, double, double, KStarCache.TableEntry) - 类的构造器 weka.classifiers.lazy.kstar.KStarCache.TableEntry
-
Constructor
- tableExists(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Checks that a given table exists.
- tableNameTipText() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the tip text for this property.
- tabuListTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.TabuSearch
- tabuListTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.TabuSearch
- TabuSearch - weka.classifiers.bayes.net.search.global中的类
-
This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.
- TabuSearch - weka.classifiers.bayes.net.search.local中的类
-
This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.
- TabuSearch() - 类的构造器 weka.classifiers.bayes.net.search.global.TabuSearch
- TabuSearch() - 类的构造器 weka.classifiers.bayes.net.search.local.TabuSearch
- Tag - weka.core中的类
-
A
Tag
simply associates a numeric ID with a String description. - Tag() - 类的构造器 weka.core.Tag
-
Creates a new default Tag
- Tag(int, String) - 类的构造器 weka.core.Tag
-
Creates a new
Tag
instance. - Tag(int, String, String) - 类的构造器 weka.core.Tag
-
Creates a new
Tag
instance. - Tag(int, String, String, boolean) - 类的构造器 weka.core.Tag
- TAG_ATTRIBUTE - 类中的静态变量 weka.core.xml.XMLInstances
-
the attribute element
- TAG_ATTRIBUTES - 类中的静态变量 weka.core.xml.XMLInstances
-
the attributes element
- TAG_BODY - 类中的静态变量 weka.core.xml.XMLInstances
-
the body element
- TAG_DATASET - 类中的静态变量 weka.core.xml.XMLInstances
-
the root element
- TAG_HEADER - 类中的静态变量 weka.core.xml.XMLInstances
-
the header element
- TAG_INSTANCE - 类中的静态变量 weka.core.xml.XMLInstances
-
the instance element
- TAG_INSTANCES - 类中的静态变量 weka.core.xml.XMLInstances
-
the data element
- TAG_LABEL - 类中的静态变量 weka.core.xml.XMLInstances
-
the label element
- TAG_LABELS - 类中的静态变量 weka.core.xml.XMLInstances
-
the labels element
- TAG_METADATA - 类中的静态变量 weka.core.xml.XMLInstances
-
the meta-data element
- TAG_NOTES - 类中的静态变量 weka.core.xml.XMLInstances
-
the notes element
- TAG_OBJECT - 类中的静态变量 weka.core.xml.XMLSerialization
-
the tag for an object
- TAG_OPTION - 类中的静态变量 weka.core.xml.XMLOptions
-
tag for a single option.
- TAG_OPTIONS - 类中的静态变量 weka.core.xml.XMLOptions
-
tag for a list of options.
- TAG_PROPERTY - 类中的静态变量 weka.core.xml.XMLInstances
-
the property element
- TAG_VALUE - 类中的静态变量 weka.core.xml.XMLInstances
-
the value element
- TAGS_ALGORITHM - 类中的静态变量 weka.filters.supervised.attribute.PLSFilter
-
the types of algorithm
- TAGS_ALGORITHM - 类中的静态变量 weka.filters.unsupervised.attribute.Wavelet
-
the types of algorithm
- TAGS_ALGORITHMTYPE - 类中的静态变量 weka.classifiers.mi.MILR
-
the types of algorithms
- TAGS_ATTRIBUTETYPE - 类中的静态变量 weka.filters.unsupervised.attribute.RemoveType
-
Tag allowing selection of attribute type to delete
- TAGS_CLUSTERSUBTYPE - 类中的静态变量 weka.datagenerators.clusterers.SubspaceCluster
-
the tags for the cluster types
- TAGS_CLUSTERTYPE - 类中的静态变量 weka.datagenerators.clusterers.SubspaceCluster
-
the tags for the cluster types
- TAGS_CV_TYPE - 类中的静态变量 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
-
the score types
- TAGS_DSTRS_TYPE - 类中的静态变量 weka.filters.unsupervised.attribute.RandomProjection
-
The types of distributions that can be used for calculating the random matrix
- TAGS_ESTIMATOR - 类中的静态变量 weka.classifiers.functions.PaceRegression
-
estimator types
- TAGS_EVAL - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
The evaluation modes
- TAGS_EVALUATION - 类中的静态变量 weka.classifiers.meta.GridSearch
-
evaluation
- TAGS_EVALUATION - 类中的静态变量 weka.classifiers.rules.DecisionTable
- TAGS_FILTER - 类中的静态变量 weka.classifiers.functions.GaussianProcesses
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.classifiers.functions.SMO
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.classifiers.functions.SMOreg
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.classifiers.mi.MDD
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.classifiers.mi.MIDD
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.classifiers.mi.MIEMDD
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.classifiers.mi.MIOptimalBall
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.classifiers.mi.MISMO
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.classifiers.mi.MISVM
-
The filter to apply to the training data
- TAGS_FILTER - 类中的静态变量 weka.filters.unsupervised.attribute.StringToWordVector
-
Specifies whether document's (instance's) word frequencies are to be normalized.
- TAGS_FORMAT - 类中的静态变量 weka.core.Debug.Clock
-
the output formats
- TAGS_GUI - 类中的静态变量 weka.gui.Main
-
GUI tags.
- TAGS_HYPER_METHOD - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
- TAGS_INPUTORDER - 类中的静态变量 weka.datagenerators.clusterers.BIRCHCluster
-
the input order tags
- TAGS_KERNELTYPE - 类中的静态变量 weka.classifiers.functions.LibSVM
-
the different kernel types
- TAGS_LINK_TYPE - 类中的静态变量 weka.clusterers.HierarchicalClusterer
- TAGS_MATRIX_SOURCE - 类中的静态变量 weka.attributeSelection.CostSensitiveASEvaluation
-
Specify possible sources of the cost matrix
- TAGS_MATRIX_SOURCE - 类中的静态变量 weka.classifiers.meta.CostSensitiveClassifier
-
Specify possible sources of the cost matrix
- TAGS_MATRIX_SOURCE - 类中的静态变量 weka.classifiers.meta.MetaCost
-
Specify possible sources of the cost matrix
- TAGS_MEASURE - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
the measure to use
- TAGS_METHOD - 类中的静态变量 weka.classifiers.meta.MultiClassClassifier
-
The error correction modes
- TAGS_MISSING - 类中的静态变量 weka.classifiers.lazy.KStar
-
Define possible missing value handling methods
- TAGS_MODEL - 类中的静态变量 weka.classifiers.trees.FT
-
possible model types.
- TAGS_OPTIMIZE - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
How to determine which class value to optimize for
- TAGS_PADDING - 类中的静态变量 weka.filters.unsupervised.attribute.Wavelet
-
the types of padding
- TAGS_PATTERN - 类中的静态变量 weka.datagenerators.clusterers.BIRCHCluster
-
the pattern tags
- TAGS_PREPROCESSING - 类中的静态变量 weka.filters.supervised.attribute.PLSFilter
-
the types of preprocessing
- TAGS_PRIOR - 类中的静态变量 weka.classifiers.bayes.BayesianLogisticRegression
- TAGS_PRUNETYPE - 类中的静态变量 weka.classifiers.meta.RacedIncrementalLogitBoost
-
The pruning types
- TAGS_PRUNING - 类中的静态变量 weka.classifiers.functions.supportVector.StringKernel
-
Pruning methods
- TAGS_PRUNING - 类中的静态变量 weka.classifiers.trees.BFTree
-
pruning strategy
- TAGS_RANGE - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
Type of correction applied to threshold range
- TAGS_RULES - 类中的静态变量 weka.classifiers.meta.Vote
-
combination rules
- TAGS_SCORE_TYPE - 类中的静态变量 weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
-
the score types
- TAGS_SEARCH_METHOD - 类中的静态变量 weka.attributeSelection.LinearForwardSelection
- TAGS_SEARCHPATH - 类中的静态变量 weka.classifiers.trees.ADTree
-
The search modes
- TAGS_SELECTION - 类中的静态变量 weka.associations.Apriori
-
Metric types.
- TAGS_SELECTION - 类中的静态变量 weka.associations.FPGrowth.AssociationRule
-
Tags for display in the GUI
- TAGS_SELECTION - 类中的静态变量 weka.attributeSelection.BestFirst
-
search directions
- TAGS_SELECTION - 类中的静态变量 weka.attributeSelection.RaceSearch
- TAGS_SELECTION - 类中的静态变量 weka.attributeSelection.ScatterSearchV1
- TAGS_SELECTION - 类中的静态变量 weka.classifiers.functions.LinearRegression
-
Attribute selection methods
- TAGS_SELECTION - 类中的静态变量 weka.classifiers.functions.SPegasos
-
Loss functions to choose from
- TAGS_SVMTYPE - 类中的静态变量 weka.classifiers.functions.LibLINEAR
-
SVM solver types
- TAGS_SVMTYPE - 类中的静态变量 weka.classifiers.functions.LibSVM
-
SVM types
- TAGS_TESTMETHOD - 类中的静态变量 weka.classifiers.mi.MIWrapper
-
the test methods
- TAGS_TRANSFORMMETHOD - 类中的静态变量 weka.classifiers.mi.SimpleMI
-
the transformation methods
- TAGS_TRAVERSAL - 类中的静态变量 weka.classifiers.meta.GridSearch
-
traversal
- TAGS_TYPE - 类中的静态变量 weka.attributeSelection.LinearForwardSelection
- TAGS_TYPE - 类中的静态变量 weka.attributeSelection.SubsetSizeForwardSelection
- TAGS_TYPE - 类中的静态变量 weka.filters.unsupervised.attribute.Add
-
the attribute type.
- TAGS_WEIGHTING - 类中的静态变量 weka.classifiers.lazy.IBk
-
possible instance weighting methods.
- TAGS_WEIGHTMETHOD - 类中的静态变量 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
weight methods
- TAN - weka.classifiers.bayes.net.search.global中的类
-
This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree.
For more information see:
N. - TAN - weka.classifiers.bayes.net.search.local中的类
-
This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree.
For more information see:
N. - TAN - 接口中的静态变量 weka.core.mathematicalexpression.sym
- TAN - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- TAN() - 类的构造器 weka.classifiers.bayes.net.search.global.TAN
- TAN() - 类的构造器 weka.classifiers.bayes.net.search.local.TAN
- target(double[], double[][], int, double[]) - 类中的方法 weka.classifiers.mi.MINND
-
Compute the target function to minimize in gradient descent The formula is:
1/2*sum[i=1..p](f(X, Xi)-var(Y, Yi))^2 - TargetMetaInfo - weka.core.pmml中的类
-
Class to encapsulate information about a Target.
- Task - weka.experiment中的接口
-
Interface to something that can be remotely executed as a task.
- taskFinished() - 类中的方法 weka.gui.LogPanel
-
Record a task ending
- taskFinished() - 接口中的方法 weka.gui.TaskLogger
-
Tells the task logger that a task has completed
- taskFinished() - 类中的方法 weka.gui.WekaTaskMonitor
-
Tells the panel that a task has completed
- TaskLogger - weka.gui中的接口
-
Interface for objects that display log and display information on running tasks.
- taskStarted() - 类中的方法 weka.gui.LogPanel
-
Record the starting of a new task
- taskStarted() - 接口中的方法 weka.gui.TaskLogger
-
Tells the task logger that a new task has been started
- taskStarted() - 类中的方法 weka.gui.WekaTaskMonitor
-
Tells the panel that a new task has been started
- TaskStatusInfo - weka.experiment中的类
-
A class holding information for tasks being executed on RemoteEngines.
- TaskStatusInfo() - 类的构造器 weka.experiment.TaskStatusInfo
- tauVal(double[][]) - 类中的静态方法 weka.core.ContingencyTables
-
Computes Goodman and Kruskal's tau-value for a contingency table.
- TechnicalInformation - weka.core中的类
-
Used for paper references in the Javadoc and for BibTex generation.
- TechnicalInformation(TechnicalInformation.Type) - 类的构造器 weka.core.TechnicalInformation
-
Initializes the information with the given type
- TechnicalInformation(TechnicalInformation.Type, String) - 类的构造器 weka.core.TechnicalInformation
-
Initializes the information with the given type
- TechnicalInformation.Field - weka.core中的Enum Class
-
the possible fields
- TechnicalInformation.Type - weka.core中的Enum Class
-
the different types of information
- TechnicalInformationHandler - weka.core中的接口
-
For classes that are based on some kind of publications.
- TechnicalInformationHandlerJavadoc - weka.core中的类
-
Generates Javadoc comments from the TechnicalInformationHandler's data.
- TechnicalInformationHandlerJavadoc() - 类的构造器 weka.core.TechnicalInformationHandlerJavadoc
-
default constructor
- TECHREPORT - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
A report published by a school or other institution, usually numbered within a series.
- Tee - weka.core中的类
-
This class pipelines print/println's to several PrintStreams.
- Tee() - 类的构造器 weka.core.Tee
-
initializes the object, with a default printstream.
- Tee(PrintStream) - 类的构造器 weka.core.Tee
-
initializes the object with the given default printstream, e.g., System.out.
- Tertius - weka.associations中的类
-
Finds rules according to confirmation measure (Tertius-type algorithm).
For more information see:
P. - Tertius() - 类的构造器 weka.associations.Tertius
-
Constructor that sets the options to the default values.
- test(String[]) - 类中的静态方法 weka.core.Instances
-
Method for testing this class.
- test(Attribute) - 类中的方法 weka.core.Capabilities
-
Test the given attribute, whether it can be processed by the handler, given its capabilities.
- test(Attribute, boolean) - 类中的方法 weka.core.Capabilities
-
Test the given attribute, whether it can be processed by the handler, given its capabilities.
- test(Instances) - 类中的方法 weka.core.Capabilities
-
Tests the given data, whether it can be processed by the handler, given its capabilities.
- test(Instances, int, int) - 类中的方法 weka.core.Capabilities
-
Tests a certain range of attributes of the given data, whether it can be processed by the handler, given its capabilities.
- Test - weka.datagenerators中的类
-
Class to represent a test.
- Test(int, double, Instances) - 类的构造器 weka.datagenerators.Test
-
Constructor
- Test(int, double, Instances, boolean) - 类的构造器 weka.datagenerators.Test
-
Constructor
- TEST - 类中的静态变量 weka.gui.beans.BatchClustererEvent
- testCapabilities(Instances, int) - 类中的方法 weka.estimators.Estimator
-
Test if the estimator can handle the data.
- testCV(int, int) - 类中的方法 weka.core.Instances
-
Creates the test set for one fold of a cross-validation on the dataset.
- Tester - weka.experiment中的接口
-
Interface for different kinds of Testers in the Experimenter.
- TestInstances - weka.core中的类
-
Generates artificial datasets for testing.
- TestInstances() - 类的构造器 weka.core.TestInstances
-
the default constructor
- TESTMETHOD_ARITHMETIC - 类中的静态变量 weka.classifiers.mi.MIWrapper
-
arithmetic average
- TESTMETHOD_GEOMETRIC - 类中的静态变量 weka.classifiers.mi.MIWrapper
-
geometric average
- TESTMETHOD_MAXPROB - 类中的静态变量 weka.classifiers.mi.MIWrapper
-
max probability of positive bag
- TestSetEvent - weka.gui.beans中的类
-
Event encapsulating a test set
- TestSetEvent(Object, Instances) - 类的构造器 weka.gui.beans.TestSetEvent
-
Creates a new
TestSetEvent
- TestSetEvent(Object, Instances, int, int) - 类的构造器 weka.gui.beans.TestSetEvent
-
Creates a new
TestSetEvent
- TestSetEvent(Object, Instances, int, int, int, int) - 类的构造器 weka.gui.beans.TestSetEvent
-
Creates a new
TestSetEvent
- TestSetListener - weka.gui.beans中的接口
-
Interface to something that can accpet test set events
- TestSetMaker - weka.gui.beans中的类
-
Bean that accepts data sets and produces test sets
- TestSetMaker() - 类的构造器 weka.gui.beans.TestSetMaker
- TestSetMakerBeanInfo - weka.gui.beans中的类
-
Bean info class for the test set maker bean.
- TestSetMakerBeanInfo() - 类的构造器 weka.gui.beans.TestSetMakerBeanInfo
- TestSetProducer - weka.gui.beans中的接口
-
Interface to something that can produce test sets
- testType() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
returns the test type
- testWithFail(Attribute) - 类中的方法 weka.core.Capabilities
-
tests the given attribute by calling the test(Attribute,boolean) method and throws an exception if the test fails.
- testWithFail(Attribute, boolean) - 类中的方法 weka.core.Capabilities
-
tests the given attribute by calling the test(Attribute,boolean) method and throws an exception if the test fails.
- testWithFail(Instances) - 类中的方法 weka.core.Capabilities
-
tests the given data by calling the test(Instances) method and throws an exception if the test fails.
- testWithFail(Instances, int, int) - 类中的方法 weka.core.Capabilities
-
tests the given data by calling the test(Instances,int,int) method and throws an exception if the test fails.
- TEXT - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for TEXT used for reading, e.g., text blobs.
- TextDirectoryLoader - weka.core.converters中的类
-
Loads all text files in a directory and uses the subdirectory names as class labels.
- TextDirectoryLoader() - 类的构造器 weka.core.converters.TextDirectoryLoader
-
default constructor
- TextEvent - weka.gui.beans中的类
-
Event that encapsulates some textual information
- TextEvent(Object, String, String) - 类的构造器 weka.gui.beans.TextEvent
-
Creates a new
TextEvent
instance. - TextListener - weka.gui.beans中的接口
-
Interface to something that can process a TextEvent
- TextViewer - weka.gui.beans中的类
-
Bean that collects and displays pieces of text
- TextViewer() - 类的构造器 weka.gui.beans.TextViewer
- TextViewerBeanInfo - weka.gui.beans中的类
-
Bean info class for the text viewer
- TextViewerBeanInfo() - 类的构造器 weka.gui.beans.TextViewerBeanInfo
- TFTransformTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- theoryDL(int) - 类中的方法 weka.classifiers.rules.RuleStats
-
The description length of the theory for a given rule.
- Threshold - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Threshold for binary classification of probabilisitic estimate
- THRESHOLD_NAME - 类中的静态变量 weka.classifiers.evaluation.CostCurve
-
attribute name: Threshold
- THRESHOLD_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: Threshold
- ThresholdCurve - weka.classifiers.evaluation中的类
-
Generates points illustrating prediction tradeoffs that can be obtained by varying the threshold value between classes.
- ThresholdCurve() - 类的构造器 weka.classifiers.evaluation.ThresholdCurve
- ThresholdDataEvent - weka.gui.beans中的类
-
Event encapsulating classifier performance data based on varying a threshold over the classifier's predicted probabilities
- ThresholdDataEvent(Object, PlotData2D) - 类的构造器 weka.gui.beans.ThresholdDataEvent
- ThresholdDataEvent(Object, PlotData2D, Attribute) - 类的构造器 weka.gui.beans.ThresholdDataEvent
- ThresholdDataListener - weka.gui.beans中的接口
-
Interface to something that can accept ThresholdDataEvents
- ThresholdSelector - weka.classifiers.meta中的类
-
A metaclassifier that selecting a mid-point threshold on the probability output by a Classifier.
- ThresholdSelector() - 类的构造器 weka.classifiers.meta.ThresholdSelector
-
Constructor.
- thresholdTipText() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
Returns the tip text for this property
- thresholdTipText() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns the tip text for this property
- thresholdTipText() - 类中的方法 weka.attributeSelection.Ranker
-
Returns the tip text for this property
- thresholdTipText() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Returns the tip text for this property
- thresholdTipText() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns the tip text for this property
- thresholdTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- thresholdTipText() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Returns the tip text for this property
- thresholdTipText() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns the tip text for this property
- thresholdTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveMisclassified
-
Returns the tip text for this property
- ThresholdVisualizePanel - weka.gui.visualize中的类
-
This panel is a VisualizePanel, with the added ablility to display the area under the ROC curve if an ROC curve is chosen.
- ThresholdVisualizePanel() - 类的构造器 weka.gui.visualize.ThresholdVisualizePanel
-
default constructor
- TIE_STRING - 类中的变量 weka.experiment.ResultMatrix
-
tie string
- TIME - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for TIME used for reading TIME columns.
- times(double) - 类中的方法 weka.core.matrix.DoubleVector
-
Multiplies a scalar
- times(double) - 类中的方法 weka.core.matrix.Matrix
-
Multiply a matrix by a scalar, C = s*A
- times(int, int, int, PaceMatrix, int) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Multiplication between a row (or part of a row) of the first matrix and a column (or part or a column) of the second matrix.
- times(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Multiplies another DoubleVector element by element
- times(Matrix) - 类中的方法 weka.core.matrix.Matrix
-
Linear algebraic matrix multiplication, A * B
- TIMES - 接口中的静态变量 weka.core.mathematicalexpression.sym
- TIMES - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- timesEquals(double) - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
All function values are multiplied by a double
- timesEquals(double) - 类中的方法 weka.core.matrix.DoubleVector
-
Multiply a vector by a scalar in place, u = s * u
- timesEquals(double) - 类中的方法 weka.core.matrix.Matrix
-
Multiply a matrix by a scalar in place, A = s*A
- timesEquals(DoubleVector) - 类中的方法 weka.core.matrix.DoubleVector
-
Multiplies another DoubleVector element by element in place
- TimeSeriesDelta - weka.filters.unsupervised.attribute中的类
-
An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the difference between the current value and the equivalent attribute attribute value of some previous (or future) instance.
- TimeSeriesDelta() - 类的构造器 weka.filters.unsupervised.attribute.TimeSeriesDelta
- TimeSeriesTranslate - weka.filters.unsupervised.attribute中的类
-
An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the equivalent attribute values of some previous (or future) instance.
- TimeSeriesTranslate() - 类的构造器 weka.filters.unsupervised.attribute.TimeSeriesTranslate
- Timestamp() - 类的构造器 weka.core.Debug.Timestamp
-
creates a timestamp with the current date and time and the default format.
- Timestamp(String) - 类的构造器 weka.core.Debug.Timestamp
-
creates a timestamp with the current date and time and the specified format.
- Timestamp(Date) - 类的构造器 weka.core.Debug.Timestamp
-
creates a timestamp with the given date and the default format.
- Timestamp(Date, String) - 类的构造器 weka.core.Debug.Timestamp
-
creates a timestamp with the given date and format.
- TIMESTAMP - 类中的静态变量 weka.experiment.DatabaseUtils
-
Type mapping for TIMESTAMP used for reading java.sql.Timestamp columns
- TIMESTAMP_FIELD_NAME - 类中的静态变量 weka.experiment.CrossValidationResultProducer
-
The name of the result field containing the timestamp
- TIMESTAMP_FIELD_NAME - 类中的静态变量 weka.experiment.RandomSplitResultProducer
-
The name of the result field containing the timestamp
- TITLE - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The work's title, typed as explained in the LaTeX book.
- TO_BE_RUN - 类中的静态变量 weka.experiment.TaskStatusInfo
- toArray() - 类中的方法 weka.core.FastVector
-
Returns all the elements of this vector as an array
- toArray() - 类中的方法 weka.core.Trie
-
Returns an array containing all of the elements in this collection.
- toArray() - 类中的方法 weka.core.xml.XMLOptions
-
returns the current DOM document as string array.
- toArray() - 类中的方法 weka.gui.CheckBoxList.CheckBoxListModel
-
Returns an array containing all of the elements in this list in the correct order.
- toArray(T[]) - 类中的方法 weka.core.Trie
-
Returns an array containing all of the elements in this collection; the runtime type of the returned array is that of the specified array.
- toBibTex() - 类中的方法 weka.core.TechnicalInformation
-
Returns a BibTex string representing this technical information.
- toClassDetailsString() - 类中的方法 weka.classifiers.Evaluation
-
Generates a breakdown of the accuracy for each class (with default title), incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
- toClassDetailsString(String) - 类中的方法 weka.classifiers.Evaluation
-
Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
- toCommandLine() - 类中的方法 weka.core.xml.XMLOptions
-
returns the given DOM document as command line.
- toCumulativeMarginDistributionString() - 类中的方法 weka.classifiers.Evaluation
-
Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.
- toDoubleArray() - 类中的方法 weka.core.BinarySparseInstance
-
Returns the values of each attribute as an array of doubles.
- toDoubleArray() - 类中的方法 weka.core.Instance
-
Returns the values of each attribute as an array of doubles.
- toDoubleArray() - 类中的方法 weka.core.SparseInstance
-
Returns the values of each attribute as an array of doubles.
- tokenize(String) - 类中的方法 weka.core.tokenizers.AlphabeticTokenizer
-
Sets the string to tokenize.
- tokenize(String) - 类中的方法 weka.core.tokenizers.NGramTokenizer
-
Sets the string to tokenize.
- tokenize(String) - 类中的方法 weka.core.tokenizers.Tokenizer
-
Sets the string to tokenize.
- tokenize(String) - 类中的方法 weka.core.tokenizers.WordTokenizer
-
Sets the string to tokenize.
- tokenize(String) - 类中的方法 weka.gui.HierarchyPropertyParser
-
Tokenize the given string based on the seperator and put the tokens into an array of strings
- tokenize(Tokenizer, String[]) - 类中的静态方法 weka.core.tokenizers.Tokenizer
-
initializes the given tokenizer with the given options and runs the tokenizer over all the remaining strings in the options array.
- Tokenizer - weka.core.tokenizers中的类
-
A superclass for all tokenizer algorithms.
- Tokenizer() - 类的构造器 weka.core.tokenizers.Tokenizer
- tokenizerTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- Tolerance - 类中的变量 weka.classifiers.bayes.BayesianLogisticRegression
-
Tolerance criteria for the stopping criterion.
- toleranceParameterTipText() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Returns a tip text for this property suitable for display in the GUI
- toleranceParameterTipText() - 类中的方法 weka.classifiers.functions.SMO
-
Returns the tip text for this property
- toleranceParameterTipText() - 类中的方法 weka.classifiers.mi.MISMO
-
Returns the tip text for this property
- toleranceTipText() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Returns the tip text for this property
- toleranceTipText() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Returns the tip text for this property
- toMatlab() - 类中的方法 weka.classifiers.CostMatrix
-
converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
- toMatlab() - 类中的方法 weka.core.matrix.Matrix
-
converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
- toMatlab() - 类中的方法 weka.core.Matrix
-
已过时。converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
- toMatrixString() - 类中的方法 weka.classifiers.Evaluation
-
Calls toMatrixString() with a default title.
- toMatrixString(String) - 类中的方法 weka.classifiers.Evaluation
-
Outputs the performance statistics as a classification confusion matrix.
- toMegaByte(long) - 类中的静态方法 weka.core.Memory
-
returns the amount of bytes as MB
- toNominalString(Instances) - 类中的方法 weka.associations.gsp.Element
-
Returns a String representation of an Element where the numeric value of each event/item is represented by its respective nominal value.
- toNominalString(Instances) - 类中的方法 weka.associations.gsp.Sequence
-
Returns a String representation of a Sequences where the numeric value of each event/item is represented by its respective nominal value.
- toOptionList(Tag[]) - 类中的静态方法 weka.core.Tag
-
returns a list that can be used in the listOption methods to list all the available ID strings, e.g.: <0|1|2> or <what|ever>
- toOptionSynopsis(Tag[]) - 类中的静态方法 weka.core.Tag
-
returns a string that can be used in the listOption methods to list all the available options, i.e., "\t\tID = Text\n" for each option
- toOutput() - 类中的方法 weka.gui.visualize.JComponentWriter
-
saves the current component to the currently set file.
- toOutput(JComponentWriter, JComponent, File) - 类中的静态方法 weka.gui.visualize.JComponentWriter
-
outputs the given component with the given writer in the specified file
- toOutput(JComponentWriter, JComponent, File, int, int) - 类中的静态方法 weka.gui.visualize.JComponentWriter
-
outputs the given component with the given writer in the specified file.
- TopDownConstructor - weka.core.neighboursearch.balltrees中的类
-
The class implementing the TopDown construction method of ball trees.
- TopDownConstructor() - 类的构造器 weka.core.neighboursearch.balltrees.TopDownConstructor
-
Creates a new instance of TopDownConstructor.
- topOfTree() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Returns the top of the tree.
- toPrologString() - 类中的方法 weka.datagenerators.Test
-
Returns the test represented by a string in Prolog notation.
- toResultsString() - 类中的方法 weka.attributeSelection.AttributeSelection
-
get a description of the attribute selection
- toSource(String) - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns the boosted model as Java source code.
- toSource(String) - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the boosted model as Java source code.
- toSource(String) - 类中的方法 weka.classifiers.rules.OneR
-
Returns a string that describes the classifier as source.
- toSource(String) - 类中的方法 weka.classifiers.rules.ZeroR
-
Returns a string that describes the classifier as source.
- toSource(String) - 接口中的方法 weka.classifiers.Sourcable
-
Returns a string that describes the classifier as source.
- toSource(String) - 类中的方法 weka.classifiers.trees.DecisionStump
-
Returns the decision tree as Java source code.
- toSource(String) - 类中的方法 weka.classifiers.trees.Id3
-
Returns a string that describes the classifier as source.
- toSource(String) - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Returns source code for the tree as an if-then statement.
- toSource(String) - 类中的方法 weka.classifiers.trees.J48
-
Returns tree as an if-then statement.
- toSource(String) - 类中的方法 weka.classifiers.trees.J48graft
-
Returns tree as an if-then statement.
- toSource(String) - 类中的方法 weka.classifiers.trees.REPTree
-
Returns the tree as if-then statements.
- toSource(String) - 类中的方法 weka.core.Capabilities
-
turns the capabilities object into source code.
- toSource(String, int) - 类中的方法 weka.core.Capabilities
-
turns the capabilities object into source code.
- toSource(String, Instances) - 类中的方法 weka.filters.AllFilter
-
Returns a string that describes the filter as source.
- toSource(String, Instances) - 接口中的方法 weka.filters.Sourcable
-
Returns a string that describes the filter as source.
- toSource(String, Instances) - 类中的方法 weka.filters.unsupervised.attribute.Center
-
Returns a string that describes the filter as source.
- toSource(String, Instances) - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns a string that describes the filter as source.
- toSource(String, Instances) - 类中的方法 weka.filters.unsupervised.attribute.ReplaceMissingValues
-
Returns a string that describes the filter as source.
- toSource(String, Instances) - 类中的方法 weka.filters.unsupervised.attribute.Standardize
-
Returns a string that describes the filter as source.
- toString() - 类中的方法 weka.associations.Apriori
-
Outputs the size of all the generated sets of itemsets and the rules.
- toString() - 类中的方法 weka.associations.AssociatorEvaluation
-
returns the current result
- toString() - 类中的方法 weka.associations.FilteredAssociator
-
Output a representation of this associator
- toString() - enum class中的方法 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
- toString() - 类中的方法 weka.associations.FPGrowth.AssociationRule
-
Get a textual description of this rule.
- toString() - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
A string representation of this item.
- toString() - 类中的方法 weka.associations.FPGrowth
-
Output the association rules.
- toString() - 类中的方法 weka.associations.GeneralizedSequentialPatterns
-
Returns a String containing the result information of the algorithm.
- toString() - 类中的方法 weka.associations.gsp.Element
-
Returns a String representation of an Element.
- toString() - 类中的方法 weka.associations.gsp.Sequence
-
Returns a String representation of a Sequence.
- toString() - 类中的方法 weka.associations.PredictiveApriori
-
Outputs the association rules.
- toString() - 类中的方法 weka.associations.tertius.AttributeValueLiteral
- toString() - 类中的方法 weka.associations.tertius.Body
-
Gives a String representation of this set of literals as a conjunction.
- toString() - 类中的方法 weka.associations.tertius.Head
-
Gives a String representation of this set of literals as a disjunction.
- toString() - 类中的方法 weka.associations.tertius.Literal
- toString() - 类中的方法 weka.associations.tertius.LiteralSet
-
Gives a String representation for this set of literals.
- toString() - 类中的方法 weka.associations.tertius.Predicate
- toString() - 类中的方法 weka.associations.tertius.Rule
-
Retrun a String for this rule.
- toString() - 类中的方法 weka.associations.tertius.SimpleLinkedList
- toString() - 类中的方法 weka.associations.Tertius
-
Outputs the best rules found with their confirmation value and number of counter-instances.
- toString() - 类中的方法 weka.attributeSelection.BestFirst.Link2
- toString() - 类中的方法 weka.attributeSelection.BestFirst
-
returns a description of the search as a String
- toString() - 类中的方法 weka.attributeSelection.CfsSubsetEval
-
returns a string describing CFS
- toString() - 类中的方法 weka.attributeSelection.ChiSquaredAttributeEval
-
Describe the attribute evaluator
- toString() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Returns a string describing classifierSubsetEval
- toString() - 类中的方法 weka.attributeSelection.ConsistencySubsetEval
-
returns a description of the evaluator
- toString() - 类中的方法 weka.attributeSelection.CostSensitiveASEvaluation
-
Output a representation of this evaluator
- toString() - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
prints a description of the search
- toString() - 类中的方法 weka.attributeSelection.FilteredAttributeEval
-
Describe the attribute evaluator
- toString() - 类中的方法 weka.attributeSelection.FilteredSubsetEval
-
Describe the attribute evaluator
- toString() - 类中的方法 weka.attributeSelection.GainRatioAttributeEval
-
Return a description of the evaluator
- toString() - 类中的方法 weka.attributeSelection.GeneticSearch
-
returns a description of the search
- toString() - 类中的方法 weka.attributeSelection.GreedyStepwise
-
returns a description of the search.
- toString() - 类中的方法 weka.attributeSelection.InfoGainAttributeEval
-
Describe the attribute evaluator
- toString() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns a description of this attribute transformer
- toString() - 类中的方法 weka.attributeSelection.LFSMethods.Link2
- toString() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
returns a description of the search as a String
- toString() - 类中的方法 weka.attributeSelection.OneRAttributeEval
-
Return a description of the evaluator
- toString() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns a description of this attribute transformer
- toString() - 类中的方法 weka.attributeSelection.RaceSearch
-
Returns a string represenation
- toString() - 类中的方法 weka.attributeSelection.RandomSearch
-
prints a description of the search
- toString() - 类中的方法 weka.attributeSelection.Ranker
-
returns a description of the search as a String
- toString() - 类中的方法 weka.attributeSelection.RankSearch
-
returns a description of the search as a String
- toString() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Return a description of the ReliefF attribute evaluator.
- toString() - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
returns a description of the search.
- toString() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
returns a description of the search as a String
- toString() - 类中的方法 weka.attributeSelection.SVMAttributeEval
-
Return a description of the evaluator
- toString() - 类中的方法 weka.attributeSelection.SymmetricalUncertAttributeEval
-
Return a description of the evaluator
- toString() - 类中的方法 weka.attributeSelection.WrapperSubsetEval
-
Returns a string describing the wrapper
- toString() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.BayesianLogisticRegression
-
Outputs the linear regression model as a string.
- toString() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.ComplementNaiveBayes
-
Prints out the internal model built by the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.DMNBtext.DNBBinary
-
Returns a string representation of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Returns a string representation of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.HNB
-
returns a string representation of the classifier
- toString() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomial
-
Returns a string representation of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
-
Returns a string representation of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.NaiveBayesSimple
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.bayes.net.BayesNetGenerator
-
Returns either the net (if BIF format) or the generated instances
- toString() - 类中的方法 weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
-
Display a representation of this estimator
- toString() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
- toString() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
- toString() - 类中的方法 weka.classifiers.bayes.net.search.SearchAlgorithm
-
a string representation of the algorithm
- toString() - 类中的方法 weka.classifiers.bayes.WAODE
-
returns a string representation of the classifier
- toString() - 类中的方法 weka.classifiers.BVDecompose
-
Returns description of the bias-variance decomposition results.
- toString() - 类中的方法 weka.classifiers.BVDecomposeSegCVSub
-
Returns description of the bias-variance decomposition results.
- toString() - 类中的方法 weka.classifiers.CostMatrix
-
Converts a matrix to a string.
- toString() - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Calls toString() with a default title.
- toString() - 类中的方法 weka.classifiers.evaluation.NominalPrediction
-
Gets a human readable representation of this prediction.
- toString() - 类中的方法 weka.classifiers.evaluation.NumericPrediction
-
Gets a human readable representation of this prediction.
- toString() - 类中的方法 weka.classifiers.evaluation.TwoClassStats
-
Returns a string containing the various performance measures for the current object
- toString() - 类中的方法 weka.classifiers.functions.GaussianProcesses
-
Prints out the classifier.
- toString() - 类中的方法 weka.classifiers.functions.IsotonicRegression
-
Returns a description of this classifier as a string
- toString() - 类中的方法 weka.classifiers.functions.LeastMedSq
-
Returns a string representing the best LinearRegression classifier found.
- toString() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
returns a string representation
- toString() - 类中的方法 weka.classifiers.functions.LibSVM
-
returns a string representation
- toString() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Outputs the linear regression model as a string.
- toString() - 类中的方法 weka.classifiers.functions.Logistic
-
Gets a string describing the classifier.
- toString() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- toString() - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Converts to a string
- toString() - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Converts the discrete function to string.
- toString() - 类中的方法 weka.classifiers.functions.pace.MixtureDistribution
-
Converts to a string
- toString() - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Converts to a string
- toString() - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Converts matrix to string
- toString() - 类中的方法 weka.classifiers.functions.PaceRegression
-
Outputs the linear regression model as a string.
- toString() - 类中的方法 weka.classifiers.functions.PLSClassifier
-
returns a string representation of the classifier
- toString() - 类中的方法 weka.classifiers.functions.RBFNetwork
-
Returns a description of this classifier as a String
- toString() - 类中的方法 weka.classifiers.functions.SimpleLinearRegression
-
Returns a description of this classifier as a string
- toString() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns a description of the logistic model (attributes/coefficients).
- toString() - 类中的方法 weka.classifiers.functions.SMO.BinarySMO
-
Prints out the classifier.
- toString() - 类中的方法 weka.classifiers.functions.SMO
-
Prints out the classifier.
- toString() - 类中的方法 weka.classifiers.functions.SMOreg
-
Prints out the classifier.
- toString() - 类中的方法 weka.classifiers.functions.SPegasos
-
Prints out the classifier.
- toString() - 类中的方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
returns the current result
- toString() - 类中的方法 weka.classifiers.functions.supportVector.NormalizedPolyKernel
-
returns a string representation for the Kernel
- toString() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
returns a string representation for the Kernel
- toString() - 类中的方法 weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
-
returns a string representation for the Kernel
- toString() - 类中的方法 weka.classifiers.functions.supportVector.Puk
-
returns a string representation for the Kernel
- toString() - 类中的方法 weka.classifiers.functions.supportVector.RBFKernel
-
returns a string representation for the Kernel
- toString() - 类中的方法 weka.classifiers.functions.supportVector.RegOptimizer
-
Prints out the classifier.
- toString() - 类中的方法 weka.classifiers.functions.VotedPerceptron
-
Returns textual description of classifier.
- toString() - 类中的方法 weka.classifiers.functions.Winnow
-
Returns textual description of the classifier.
- toString() - 类中的方法 weka.classifiers.lazy.IB1
-
Returns a description of this classifier.
- toString() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns a description of this classifier.
- toString() - 类中的方法 weka.classifiers.lazy.KStar
-
Returns a description of this classifier.
- toString() - 类中的方法 weka.classifiers.lazy.LBR
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns a description of this classifier.
- toString() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns description of the boosted classifier.
- toString() - 类中的方法 weka.classifiers.meta.AdditiveRegression
-
Returns textual description of the classifier.
- toString() - 类中的方法 weka.classifiers.meta.AttributeSelectedClassifier
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.meta.Bagging
-
Returns description of the bagged classifier.
- toString() - 类中的方法 weka.classifiers.meta.ClassificationViaClustering
-
Returns a string representation of the classifier.
- toString() - 类中的方法 weka.classifiers.meta.ClassificationViaRegression
-
Prints the classifiers.
- toString() - 类中的方法 weka.classifiers.meta.CostSensitiveClassifier
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
Returns description of the cross-validated classifier.
- toString() - 类中的方法 weka.classifiers.meta.Dagging
-
Returns description of the classifier.
- toString() - 类中的方法 weka.classifiers.meta.Decorate
-
Returns description of the Decorate classifier.
- toString() - 类中的方法 weka.classifiers.meta.END
-
Returns description of the committee.
- toString() - 类中的方法 weka.classifiers.meta.FilteredClassifier
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.meta.Grading
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.meta.GridSearch
-
returns a string representation of the classifier
- toString() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns description of the boosted classifier.
- toString() - 类中的方法 weka.classifiers.meta.MetaCost
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.meta.MultiBoostAB
-
Returns description of the boosted classifier.
- toString() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
-
Prints the classifiers.
- toString() - 类中的方法 weka.classifiers.meta.MultiScheme
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ClassBalancedND
-
Outputs the classifier as a string.
- toString() - 类中的方法 weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
-
Outputs the classifier as a string.
- toString() - 类中的方法 weka.classifiers.meta.nestedDichotomies.ND
-
Outputs the classifier as a string.
- toString() - 类中的方法 weka.classifiers.meta.OrdinalClassClassifier
-
Prints the classifiers.
- toString() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Returns description of the boosted classifier.
- toString() - 类中的方法 weka.classifiers.meta.RandomCommittee
-
Returns description of the committee.
- toString() - 类中的方法 weka.classifiers.meta.RandomSubSpace
-
Returns description of the bagged classifier.
- toString() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.meta.RotationForest
-
Returns description of the Rotation Forest classifier.
- toString() - 类中的方法 weka.classifiers.meta.Stacking
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.meta.StackingC
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.meta.ThresholdSelector
-
Returns description of the cross-validated classifier.
- toString() - 类中的方法 weka.classifiers.meta.Vote
-
Output a representation of this classifier
- toString() - 类中的方法 weka.classifiers.mi.CitationKNN
-
returns a string representation of the classifier
- toString() - 类中的方法 weka.classifiers.mi.MDD
-
Gets a string describing the classifier.
- toString() - 类中的方法 weka.classifiers.mi.MIBoost
-
Gets a string describing the classifier.
- toString() - 类中的方法 weka.classifiers.mi.MIDD
-
Gets a string describing the classifier.
- toString() - 类中的方法 weka.classifiers.mi.MIEMDD
-
Gets a string describing the classifier.
- toString() - 类中的方法 weka.classifiers.mi.MILR
-
Gets a string describing the classifier.
- toString() - 类中的方法 weka.classifiers.mi.MISMO
-
Prints out the classifier.
- toString() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Gets a string describing the classifier.
- toString() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Gets a string describing the classifier.
- toString() - 类中的方法 weka.classifiers.misc.HyperPipes
-
Returns a description of this classifier.
- toString() - 类中的方法 weka.classifiers.misc.SerializedClassifier
-
Returns a string representation of the classifier
- toString() - 类中的方法 weka.classifiers.misc.VFI
-
Returns a description of this classifier.
- toString() - 类中的方法 weka.classifiers.pmml.consumer.GeneralRegression
-
Return a textual description of this general regression.
- toString() - 类中的方法 weka.classifiers.pmml.consumer.NeuralNetwork
- toString() - 类中的方法 weka.classifiers.pmml.consumer.Regression
-
Return a textual description of this Regression model.
- toString() - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Prints this rule
- toString() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.rules.DTNB
- toString() - 类中的方法 weka.classifiers.rules.JRip.Antd
- toString() - 类中的方法 weka.classifiers.rules.JRip.NominalAntd
-
Prints this antecedent
- toString() - 类中的方法 weka.classifiers.rules.JRip.NumericAntd
-
Prints this antecedent
- toString() - 类中的方法 weka.classifiers.rules.JRip
-
Prints the all the rules of the rule learner.
- toString() - 类中的方法 weka.classifiers.rules.NNge
-
Returns a description of this classifier.
- toString() - 类中的方法 weka.classifiers.rules.OneR
-
Returns a description of the classifier
- toString() - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Prints rules.
- toString() - 类中的方法 weka.classifiers.rules.part.MakeDecList
-
Outputs the classifier into a string.
- toString() - 类中的方法 weka.classifiers.rules.PART
-
Returns a description of the classifier
- toString() - 类中的方法 weka.classifiers.rules.Prism
-
Prints a description of the classifier.
- toString() - 类中的方法 weka.classifiers.rules.Ridor
-
Prints the all the rules of the rule learner.
- toString() - 类中的方法 weka.classifiers.rules.ZeroR
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.ADTree
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.BFTree
-
Prints the decision tree using the protected toString method from below.
- toString() - 类中的方法 weka.classifiers.trees.DecisionStump
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.ft.FTtree
-
Returns a description of the Functional tree (tree structure and logistic models)
- toString() - 类中的方法 weka.classifiers.trees.FT
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.Id3
-
Prints the decision tree using the private toString method from below.
- toString() - 类中的方法 weka.classifiers.trees.j48.C45PruneableClassifierTreeG
-
Prints tree structure.
- toString() - 类中的方法 weka.classifiers.trees.j48.ClassifierTree
-
Prints tree structure.
- toString() - 类中的方法 weka.classifiers.trees.j48.NBTreeClassifierTree
-
Prints tree structure.
- toString() - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Return a textual description of the node
- toString() - 类中的方法 weka.classifiers.trees.J48
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.LADTree
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Returns a description of the logistic model tree (tree structure and logistic models)
- toString() - 类中的方法 weka.classifiers.trees.lmt.LogisticBase
-
Returns a description of the logistic model (i.e., attributes and coefficients).
- toString() - 类中的方法 weka.classifiers.trees.LMT
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.m5.Impurity
-
Converts an Impurity object to a string
- toString() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns a description of the classifier
- toString() - 类中的方法 weka.classifiers.trees.m5.PreConstructedLinearModel
-
Returns a textual description of this linear model
- toString() - 类中的方法 weka.classifiers.trees.m5.Rule
-
Return a description of the m5 tree or rule
- toString() - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
print the linear model at this node
- toString() - 类中的方法 weka.classifiers.trees.m5.Values
-
Converts the stats to a string
- toString() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns a description of the classifier.
- toString() - 类中的方法 weka.classifiers.trees.RandomForest
-
Outputs a description of this classifier.
- toString() - 类中的方法 weka.classifiers.trees.RandomTree
-
Outputs the decision tree.
- toString() - 类中的方法 weka.classifiers.trees.REPTree
-
Outputs the decision tree.
- toString() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Prints the decision tree using the protected toString method from below.
- toString() - 类中的方法 weka.classifiers.trees.UserClassifier
- toString() - 类中的方法 weka.clusterers.CLOPE
-
return a string describing this clusterer
- toString() - 类中的方法 weka.clusterers.Cobweb
-
Returns a description of the clusterer as a string.
- toString() - 类中的方法 weka.clusterers.DBSCAN
-
Returns a description of the clusterer
- toString() - 类中的方法 weka.clusterers.EM
-
Outputs the generated clusters into a string.
- toString() - 类中的方法 weka.clusterers.FarthestFirst
-
return a string describing this clusterer
- toString() - 类中的方法 weka.clusterers.FilteredClusterer
-
Output a representation of this clusterer.
- toString() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
- toString() - 类中的方法 weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
- toString() - 类中的方法 weka.clusterers.HierarchicalClusterer
- toString() - 类中的方法 weka.clusterers.MakeDensityBasedClusterer
-
Returns a description of the clusterer.
- toString() - 类中的方法 weka.clusterers.OPTICS
-
Returns a description of the clusterer
- toString() - 类中的方法 weka.clusterers.sIB
- toString() - 类中的方法 weka.clusterers.SimpleKMeans
-
return a string describing this clusterer
- toString() - 类中的方法 weka.clusterers.XMeans
-
Return a string describing this clusterer.
- toString() - 类中的方法 weka.core.AlgVector
-
Converts a vector to a string
- toString() - 类中的方法 weka.core.Attribute
-
Returns a description of this attribute in ARFF format.
- toString() - 类中的方法 weka.core.AttributeExpression
- toString() - 类中的方法 weka.core.AttributeLocator
-
returns a string representation of this object
- toString() - 类中的方法 weka.core.AttributeStats
-
Returns a human readable representation of this AttributeStats instance.
- toString() - 类中的方法 weka.core.BinarySparseInstance
-
Returns the description of one instance in sparse format.
- toString() - enum class中的方法 weka.core.Capabilities.Capability
-
returns the display string of the capability
- toString() - 类中的方法 weka.core.Capabilities
-
returns a string representation of the capabilities
- toString() - 类中的方法 weka.core.Debug.Clock
-
returns the elapsed time, getStop() - getStart(), as string
- toString() - 类中的方法 weka.core.Debug.Log
-
returns a string representation of the logger
- toString() - 类中的方法 weka.core.Debug.Random
-
returns a string representation of this number generator
- toString() - 类中的方法 weka.core.Debug.SimpleLog
-
returns a string representation of the logger
- toString() - 类中的方法 weka.core.Debug.Timestamp
-
returns the timestamp as string in the specified format
- toString() - 类中的方法 weka.core.Instance
-
Returns the description of one instance.
- toString() - 类中的方法 weka.core.Instances
-
Returns the dataset as a string in ARFF format.
- toString() - 类中的方法 weka.core.matrix.DoubleVector
-
Convert the DoubleVecor to a string
- toString() - 类中的方法 weka.core.matrix.IntVector
-
Converts the IntVecor to a string
- toString() - 类中的方法 weka.core.matrix.LinearRegression
-
returns the coefficients in a string representation
- toString() - 类中的方法 weka.core.matrix.Matrix
-
Converts a matrix to a string.
- toString() - 类中的方法 weka.core.Matrix
-
已过时。Converts a matrix to a string
- toString() - 类中的方法 weka.core.NormalizableDistance
-
Returns an empty string.
- toString() - 类中的方法 weka.core.pmml.BuiltInArithmetic
- toString() - 类中的方法 weka.core.pmml.BuiltInMath
- toString() - 类中的方法 weka.core.pmml.BuiltInString
- toString() - 类中的方法 weka.core.pmml.DefineFunction
- toString() - 类中的方法 weka.core.pmml.DerivedFieldMetaInfo
- toString() - 类中的方法 weka.core.pmml.Expression
- toString() - enum class中的方法 weka.core.pmml.FieldMetaInfo.Interval.Closure
- toString() - 类中的方法 weka.core.pmml.FieldMetaInfo.Interval
- toString() - enum class中的方法 weka.core.pmml.FieldMetaInfo.Optype
- toString() - enum class中的方法 weka.core.pmml.FieldMetaInfo.Value.Property
- toString() - 类中的方法 weka.core.pmml.FieldMetaInfo.Value
- toString() - 类中的方法 weka.core.pmml.Function
- toString() - 类中的方法 weka.core.pmml.MiningFieldMetaInfo
-
Return a textual representation of this MiningField.
- toString() - 类中的方法 weka.core.pmml.MiningSchema
-
Get a textual description of the mining schema.
- toString() - 类中的方法 weka.core.PropertyPath.Path
-
returns the structure again as a dot-path
- toString() - 类中的方法 weka.core.PropertyPath.PathElement
-
returns the element once again as string
- toString() - 类中的方法 weka.core.Queue
-
Produces textual description of queue.
- toString() - 类中的方法 weka.core.Range
-
Constructs a representation of the current range.
- toString() - 类中的方法 weka.core.SelectedTag
-
returns the selected tag in string representation
- toString() - 类中的方法 weka.core.SingleIndex
-
Constructs a representation of the current range.
- toString() - 类中的方法 weka.core.SparseInstance
-
Returns the description of one instance in sparse format.
- toString() - 类中的方法 weka.core.stemmers.LovinsStemmer
-
returns a string representation of the stemmer
- toString() - 类中的方法 weka.core.stemmers.NullStemmer
-
returns a string representation of the stemmer
- toString() - 类中的方法 weka.core.stemmers.SnowballStemmer
-
returns a string representation of the stemmer.
- toString() - 类中的方法 weka.core.Stopwords
-
returns the current stopwords in a string
- toString() - 类中的方法 weka.core.SystemInfo
-
returns a string representation of all the system properties
- toString() - 类中的方法 weka.core.Tag
-
returns the IDStr
- toString() - enum class中的方法 weka.core.TechnicalInformation.Field
-
returns the display string of the Type
- toString() - 类中的方法 weka.core.TechnicalInformation
-
Returns a plain-text string representing this technical information.
- toString() - enum class中的方法 weka.core.TechnicalInformation.Type
-
returns the display string of the Type
- toString() - 类中的方法 weka.core.Tee
-
returns only the classname and the number of streams.
- toString() - 类中的方法 weka.core.TestInstances
-
returns a string representation of the object
- toString() - 类中的方法 weka.core.Trie
-
returns the trie in string representation
- toString() - 类中的方法 weka.core.Trie.TrieNode
-
returns the node in a string representation
- toString() - 类中的方法 weka.core.Version
-
returns the current version as string
- toString() - 类中的方法 weka.core.xml.MethodHandler
-
returns the internal Hashtable (propety/class - method relationship) in a string representation
- toString() - 类中的方法 weka.core.xml.XMLDocument
-
returns the current DOM document as XML-string.
- toString() - 类中的方法 weka.core.xml.XMLOptions
-
returns the object in a string representation (as indented XML output).
- toString() - 类中的方法 weka.core.xml.XMLSerializationMethodHandler
-
returns the read and write method handlers as string
- toString() - 类中的方法 weka.datagenerators.ClusterDefinition
-
returns a string representation of the cluster
- toString() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Make a string from the cluster features.
- toString() - 类中的方法 weka.datagenerators.Test
-
Returns the test represented by a string.
- toString() - 类中的方法 weka.estimators.DDConditionalEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.DiscreteEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.DKConditionalEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.DNConditionalEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.KDConditionalEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.KernelEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.KKConditionalEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.MahalanobisEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.NDConditionalEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.NNConditionalEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.NormalEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.estimators.PoissonEstimator
-
Display a representation of this estimator
- toString() - 类中的方法 weka.experiment.AveragingResultProducer
-
Gets a text descrption of the result producer.
- toString() - 类中的方法 weka.experiment.ClassifierSplitEvaluator
-
Returns a text description of the split evaluator.
- toString() - 类中的方法 weka.experiment.CostSensitiveClassifierSplitEvaluator
-
Returns a text description of the split evaluator.
- toString() - 类中的方法 weka.experiment.CrossValidationResultProducer
-
Gets a text descrption of the result producer.
- toString() - 类中的方法 weka.experiment.DatabaseResultProducer
-
Gets a text descrption of the result producer.
- toString() - 类中的方法 weka.experiment.DensityBasedClustererSplitEvaluator
-
Returns a text description of the split evaluator.
- toString() - 类中的方法 weka.experiment.Experiment
-
Gets a string representation of the experiment configuration.
- toString() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Gets a text descrption of the result producer.
- toString() - 类中的方法 weka.experiment.PairedStats
-
Returns statistics on the paired comparison.
- toString() - 类中的方法 weka.experiment.PropertyNode
-
Returns a string description of this property.
- toString() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Gets a text descrption of the result producer.
- toString() - 类中的方法 weka.experiment.RegressionSplitEvaluator
-
Returns a text description of the split evaluator.
- toString() - 类中的方法 weka.experiment.RemoteExperiment
-
Overides toString in Experiment
- toString() - 类中的方法 weka.experiment.ResultMatrix
-
returns the matrix as a string
- toString() - 类中的方法 weka.experiment.Stats
-
Returns a string summarising the stats so far.
- toString() - 类中的方法 weka.filters.Filter
-
Returns a description of the filter, by default only the classname.
- toString() - 类中的方法 weka.gui.arffviewer.ArffViewer
-
returns only the classname
- toString() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
returns only the classname
- toString() - 类中的方法 weka.gui.GenericObjectEditor.GOETreeNode
-
returns a string representation of this treenode.
- toString() - 类中的方法 weka.gui.graphvisualizer.GraphEdge
- toString() - 类中的方法 weka.gui.SortedTableModel.SortContainer
-
Returns a string representation of the sort container.
- toString() - 类中的方法 weka.gui.sql.event.ConnectionEvent
-
returns the event in a string representation
- toString() - 类中的方法 weka.gui.sql.event.HistoryChangedEvent
-
returns the event in a string representation
- toString() - 类中的方法 weka.gui.sql.event.QueryExecuteEvent
-
returns the event in a string representation
- toString() - 类中的方法 weka.gui.sql.event.ResultChangedEvent
-
returns the event in a string representation
- toString(boolean) - 类中的方法 weka.associations.FPGrowth.BinaryItem
-
A string representation of this item.
- toString(double, double) - enum class中的方法 weka.core.pmml.FieldMetaInfo.Interval.Closure
- toString(int) - 类中的方法 weka.core.Instance
-
Returns the description of one value of the instance as a string.
- toString(int, boolean) - 类中的方法 weka.classifiers.functions.pace.PaceMatrix
-
Converts matrix to string
- toString(int, boolean) - 类中的方法 weka.core.matrix.DoubleVector
-
Convert the DoubleVecor to a string
- toString(int, boolean) - 类中的方法 weka.core.matrix.IntVector
-
Convert the IntVecor to a string
- toString(String) - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Outputs the performance statistics as a classification confusion matrix.
- toString(String) - 类中的方法 weka.core.pmml.BuiltInArithmetic
- toString(String) - 类中的方法 weka.core.pmml.Constant
- toString(String) - 类中的方法 weka.core.pmml.DefineFunction
- toString(String) - 类中的方法 weka.core.pmml.Discretize
- toString(String) - 类中的方法 weka.core.pmml.Expression
- toString(String) - 类中的方法 weka.core.pmml.FieldRef
- toString(String) - 类中的方法 weka.core.pmml.Function
- toString(String) - 类中的方法 weka.core.pmml.NormContinuous
- toString(String) - 类中的方法 weka.core.pmml.NormDiscrete
- toString(String, String) - 类中的方法 weka.classifiers.rules.ConjunctiveRule
-
Prints this rule with the specified class label
- toString(Attribute) - 类中的方法 weka.classifiers.rules.JRip.RipperRule
-
Prints this rule
- toString(Attribute) - 类中的方法 weka.core.Instance
-
Returns the description of one value of the instance as a string.
- toString(Instances) - 类中的方法 weka.associations.AprioriItemSet
-
Returns the contents of an item set as a string.
- toString(Instances) - 类中的方法 weka.associations.ItemSet
-
Returns the contents of an item set as a string.
- toString(Instances) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
-
method for returning information about this GraftSplit
- toString(Instances) - 类中的方法 weka.classifiers.trees.m5.YongSplitInfo
-
Converts the spliting information to string
- toString(Instances, int) - 类中的方法 weka.attributeSelection.ConsistencySubsetEval.hashKey
-
Convert a hash entry to a string
- toString(Instances, int) - 类中的方法 weka.classifiers.rules.DecisionTableHashKey
-
Convert a hash entry to a string
- toStringHeader() - 类中的方法 weka.experiment.ResultMatrix
-
returns the header of the matrix as a string
- toStringHeader() - 类中的方法 weka.experiment.ResultMatrixCSV
-
returns the header of the matrix as a string
- toStringHeader() - 类中的方法 weka.experiment.ResultMatrixGnuPlot
-
returns the header of the matrix as a string
- toStringHeader() - 类中的方法 weka.experiment.ResultMatrixHTML
-
returns the header of the matrix as a string
- toStringHeader() - 类中的方法 weka.experiment.ResultMatrixLatex
-
returns the header of the matrix as a string
- toStringHeader() - 类中的方法 weka.experiment.ResultMatrixPlainText
-
returns the header of the matrix as a string
- toStringHeader() - 类中的方法 weka.experiment.ResultMatrixSignificance
-
returns the header of the matrix as a string
- toStringKey() - 类中的方法 weka.experiment.ResultMatrix
-
returns returns a key for all the col names, for better readability if the names got cut off
- toStringKey() - 类中的方法 weka.experiment.ResultMatrixCSV
-
returns returns a key for all the col names, for better readability if the names got cut off
- toStringKey() - 类中的方法 weka.experiment.ResultMatrixGnuPlot
-
returns returns a key for all the col names, for better readability if the names got cut off
- toStringKey() - 类中的方法 weka.experiment.ResultMatrixHTML
-
returns returns a key for all the col names, for better readability if the names got cut off
- toStringKey() - 类中的方法 weka.experiment.ResultMatrixLatex
-
returns returns a key for all the col names, for better readability if the names got cut off
- toStringKey() - 类中的方法 weka.experiment.ResultMatrixPlainText
-
returns returns a key for all the col names, for better readability if the names got cut off
- toStringKey() - 类中的方法 weka.experiment.ResultMatrixSignificance
-
returns returns a key for all the col names, for better readability if the names got cut off
- toStringMatrix() - 类中的方法 weka.experiment.ResultMatrix
-
returns the matrix as a string
- toStringMatrix() - 类中的方法 weka.experiment.ResultMatrixCSV
-
returns the matrix in CSV format
- toStringMatrix() - 类中的方法 weka.experiment.ResultMatrixGnuPlot
-
returns the matrix in CSV format
- toStringMatrix() - 类中的方法 weka.experiment.ResultMatrixHTML
-
returns the matrix in an HTML table
- toStringMatrix() - 类中的方法 weka.experiment.ResultMatrixLatex
-
returns the matrix as latex table
- toStringMatrix() - 类中的方法 weka.experiment.ResultMatrixPlainText
-
returns the matrix as plain text
- toStringMatrix() - 类中的方法 weka.experiment.ResultMatrixSignificance
-
returns the matrix as plain text
- toStringMetric(int, int, int, int) - enum class中的方法 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
- toStringRanking() - 类中的方法 weka.experiment.ResultMatrix
-
returns the ranking in a string representation
- toStringRanking() - 类中的方法 weka.experiment.ResultMatrixCSV
-
returns the ranking in a string representation
- toStringRanking() - 类中的方法 weka.experiment.ResultMatrixGnuPlot
-
returns the ranking in a string representation
- toStringRanking() - 类中的方法 weka.experiment.ResultMatrixHTML
-
returns the ranking in a string representation
- toStringRanking() - 类中的方法 weka.experiment.ResultMatrixLatex
-
returns the ranking in a string representation
- toStringRanking() - 类中的方法 weka.experiment.ResultMatrixPlainText
-
returns the ranking in a string representation
- toStringRanking() - 类中的方法 weka.experiment.ResultMatrixSignificance
-
returns the ranking in a string representation
- toStringSummary() - 类中的方法 weka.experiment.ResultMatrix
-
returns the summary as string
- toStringSummary() - 类中的方法 weka.experiment.ResultMatrixCSV
-
returns the summary as string
- toStringSummary() - 类中的方法 weka.experiment.ResultMatrixGnuPlot
-
returns the summary as string
- toStringSummary() - 类中的方法 weka.experiment.ResultMatrixHTML
-
returns the summary as string
- toStringSummary() - 类中的方法 weka.experiment.ResultMatrixLatex
-
returns the summary as string
- toStringSummary() - 类中的方法 weka.experiment.ResultMatrixPlainText
-
returns the summary as string
- toStringSummary() - 类中的方法 weka.experiment.ResultMatrixSignificance
-
returns the summary as string
- toSummaryString() - 类中的方法 weka.associations.AssociatorEvaluation
-
returns a summary string of the evaluation with a no title
- toSummaryString() - 类中的方法 weka.classifiers.Evaluation
-
Calls toSummaryString() with no title and no complexity stats
- toSummaryString() - 类中的方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
returns a summary string of the evaluation with a no title
- toSummaryString() - 类中的方法 weka.classifiers.meta.CVParameterSelection
-
A concise description of the model.
- toSummaryString() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns a string that summarizes the object.
- toSummaryString() - 类中的方法 weka.classifiers.rules.PART
-
Returns a superconcise version of the model
- toSummaryString() - 类中的方法 weka.classifiers.trees.J48
-
Returns a superconcise version of the model
- toSummaryString() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns a superconcise version of the model
- toSummaryString() - 类中的方法 weka.classifiers.trees.NBTree
-
Returns a superconcise version of the model
- toSummaryString() - 类中的方法 weka.core.Instances
-
Generates a string summarizing the set of instances.
- toSummaryString() - 接口中的方法 weka.core.Summarizable
-
Returns a string that summarizes the object.
- toSummaryString(boolean) - 类中的方法 weka.classifiers.Evaluation
-
Calls toSummaryString() with a default title.
- toSummaryString(String) - 类中的方法 weka.associations.AssociatorEvaluation
-
returns a summary string of the evaluation with a default title
- toSummaryString(String) - 类中的方法 weka.classifiers.functions.supportVector.KernelEvaluation
-
returns a summary string of the evaluation with a default title
- toSummaryString(String, boolean) - 类中的方法 weka.classifiers.Evaluation
-
Outputs the performance statistics in summary form.
- total() - 类中的方法 weka.classifiers.evaluation.ConfusionMatrix
-
Gets the number of predictions that were made (actually the sum of the weights of predictions where the class value was known).
- total() - 类中的方法 weka.classifiers.trees.j48.Distribution
-
Returns total number of (possibly fractional) instances.
- TOTAL_UNIFORM - 类中的静态变量 weka.datagenerators.clusterers.SubspaceCluster
-
cluster type: total uniform
- totalCost() - 类中的方法 weka.classifiers.Evaluation
-
Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
- totalCount - 类中的变量 weka.core.AttributeStats
-
The total number of values (i.e.
- totalForSubset(int) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- totalForSubsetOfInterest() - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- toXML() - 类中的方法 weka.associations.FPGrowth.AssociationRule
- toXML() - 类中的方法 weka.associations.FPGrowth.BinaryItem
- toXML(int, int, int, int) - enum class中的方法 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
- toXML(Object) - 类中的方法 weka.core.xml.XMLSerialization
-
extracts all accesible properties from the given object
- toXMLBIF03() - 类中的方法 weka.classifiers.bayes.BayesNet
-
Returns a description of the classifier in XML BIF 0.3 format.
- toXMLBIF03() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
returns network in XMLBIF format
- toXMLBIF03() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator
- toXMLBIF03(FastVector) - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
return fragment of network in XMLBIF format
- TP_RATE - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
true-positive rate
- TP_RATE_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: True Positive Rate
- trace() - 类中的方法 weka.core.matrix.Matrix
-
Matrix trace.
- trainCV(int, int) - 类中的方法 weka.core.Instances
-
Creates the training set for one fold of a cross-validation on the dataset.
- trainCV(int, int, Random) - 类中的方法 weka.core.Instances
-
Creates the training set for one fold of a cross-validation on the dataset.
- TRAINING - 类中的静态变量 weka.gui.beans.BatchClustererEvent
- TrainingSetEvent - weka.gui.beans中的类
-
Event encapsulating a training set
- TrainingSetEvent(Object, Instances) - 类的构造器 weka.gui.beans.TrainingSetEvent
-
Creates a new
TrainingSetEvent
- TrainingSetEvent(Object, Instances, int, int) - 类的构造器 weka.gui.beans.TrainingSetEvent
-
Creates a new
TrainingSetEvent
- TrainingSetEvent(Object, Instances, int, int, int, int) - 类的构造器 weka.gui.beans.TrainingSetEvent
-
Creates a new
TrainingSetEvent
- TrainingSetListener - weka.gui.beans中的接口
-
Interface to something that can accept and process training set events
- TrainingSetMaker - weka.gui.beans中的类
-
Bean that accepts a data sets and produces a training set
- TrainingSetMaker() - 类的构造器 weka.gui.beans.TrainingSetMaker
- TrainingSetMakerBeanInfo - weka.gui.beans中的类
-
Bean info class for the training set maker bean
- TrainingSetMakerBeanInfo() - 类的构造器 weka.gui.beans.TrainingSetMakerBeanInfo
- TrainingSetProducer - weka.gui.beans中的接口
-
Interface to something that can produce a training set
- trainingTimeTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- trainPercentTipText() - 类中的方法 weka.experiment.RandomSplitResultProducer
-
Returns the tip text for this property
- trainPercentTipText() - 类中的方法 weka.gui.beans.TrainTestSplitMaker
-
Tip text info for this property
- TrainTestSplitMaker - weka.gui.beans中的类
-
Bean that accepts data sets, training sets, test sets and produces both a training and test set by randomly spliting the data
- TrainTestSplitMaker() - 类的构造器 weka.gui.beans.TrainTestSplitMaker
- TrainTestSplitMakerBeanInfo - weka.gui.beans中的类
-
Bean info class for the train test split maker bean
- TrainTestSplitMakerBeanInfo() - 类的构造器 weka.gui.beans.TrainTestSplitMakerBeanInfo
- TrainTestSplitMakerCustomizer - weka.gui.beans中的类
-
GUI customizer for the train test split maker bean
- TrainTestSplitMakerCustomizer() - 类的构造器 weka.gui.beans.TrainTestSplitMakerCustomizer
- transactionsMustContainTipText() - 类中的方法 weka.associations.FPGrowth
-
Returns the tip text for this property
- transform(AffineTransform) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- transform(Instances) - 类中的方法 weka.classifiers.mi.SimpleMI
-
Implements MITransform (3 type of transformation) 1.arithmatic average; 2.geometric centor; 3.merge minima and maxima attribute value together
- transformAllValuesTipText() - 类中的方法 weka.filters.supervised.attribute.NominalToBinary
-
Returns the tip text for this property
- transformAllValuesTipText() - 类中的方法 weka.filters.unsupervised.attribute.NominalToBinary
-
Returns the tip text for this property
- transformBackToOriginalTipText() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns the tip text for this property
- transformedData(Instances) - 接口中的方法 weka.attributeSelection.AttributeTransformer
-
Transform the supplied data set (assumed to be the same format as the training data)
- transformedData(Instances) - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Transform the supplied data set (assumed to be the same format as the training data)
- transformedData(Instances) - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Gets the transformed training data.
- transformedHeader() - 接口中的方法 weka.attributeSelection.AttributeTransformer
-
Returns just the header for the transformed data (ie.
- transformedHeader() - 类中的方法 weka.attributeSelection.LatentSemanticAnalysis
-
Returns just the header for the transformed data (ie.
- transformedHeader() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns just the header for the transformed data (ie.
- TRANSFORMMETHOD_ARITHMETIC - 类中的静态变量 weka.classifiers.mi.SimpleMI
-
arithmetic average
- TRANSFORMMETHOD_GEOMETRIC - 类中的静态变量 weka.classifiers.mi.SimpleMI
-
geometric average
- TRANSFORMMETHOD_MINIMAX - 类中的静态变量 weka.classifiers.mi.SimpleMI
-
using minimax combined features of a bag
- transformMethodTipText() - 类中的方法 weka.classifiers.mi.SimpleMI
-
Returns the tip text for this property
- translate(double, double) - 类中的方法 weka.gui.visualize.PostscriptGraphics
- translate(int, int) - 类中的方法 weka.gui.visualize.PostscriptGraphics
-
Translates the origin of the graphics context to the point (x, y) in the current coordinate system.
- translateDBColumnType(String) - 类中的方法 weka.experiment.DatabaseUtils
-
translates the column data type string to an integer value that indicates which data type / get()-Method to use in order to retrieve values from the database (see DatabaseUtils.Properties, InstanceQuery()).
- translationTipText() - 类中的方法 weka.filters.unsupervised.attribute.Normalize
-
Returns the tip text for this property.
- transpose() - 类中的方法 weka.core.matrix.Matrix
-
Matrix transpose.
- transpose() - 类中的方法 weka.core.Matrix
-
已过时。Returns the transpose of a matrix.
- transProb() - 类中的方法 weka.classifiers.lazy.kstar.KStarNominalAttribute
-
Calculates the probability of the indexed nominal attribute of the test instance transforming into the indexed nominal attribute of the training instance.
- transProb() - 类中的方法 weka.classifiers.lazy.kstar.KStarNumericAttribute
-
Calculates the transformation probability of the attribute indexed "m_AttrIndex" in test instance "m_Test" to the same attribute in the train instance "m_Train".
- TRAVERSAL_BY_COLUMN - 类中的静态变量 weka.classifiers.meta.GridSearch
-
column-wise grid traversal
- TRAVERSAL_BY_ROW - 类中的静态变量 weka.classifiers.meta.GridSearch
-
row-wise grid traversal
- traversalTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- TREE - 接口中的静态变量 weka.core.Drawable
- TreeBuild - weka.gui.treevisualizer中的类
-
This class will parse a dotty file and construct a tree structure from it with Edge's and Node's
- TreeBuild() - 类的构造器 weka.gui.treevisualizer.TreeBuild
-
Upon construction this will only setup the color table for quick reference of a color.
- TreeDisplayEvent - weka.gui.treevisualizer中的类
-
An event containing the user selection from the tree display
- TreeDisplayEvent(int, String) - 类的构造器 weka.gui.treevisualizer.TreeDisplayEvent
-
Constructs an event with the specified command and what the command is applied to.
- TreeDisplayListener - weka.gui.treevisualizer中的接口
-
Interface implemented by classes that wish to recieve user selection events from a tree displayer.
- treeErrors() - 类中的方法 weka.classifiers.trees.lmt.LMTNode
-
Updates the numIncorrectTree field for all nodes.
- treeErrors() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Updates the numIncorrectTree field for all nodes.
- TreePerformanceStats - weka.core.neighboursearch中的类
-
The class that measures the performance of a tree based nearest neighbour search algorithm.
- TreePerformanceStats() - 类的构造器 weka.core.neighboursearch.TreePerformanceStats
-
Default constructor.
- treeToString(int) - 类中的方法 weka.classifiers.trees.m5.RuleNode
-
Recursively builds a textual description of the tree
- TreeVisualizePlugin - weka.gui.visualize.plugins中的接口
-
Interface implemented by classes loaded dynamically to visualize classifier results in the explorer.
- TreeVisualizer - weka.gui.treevisualizer中的类
-
Class for displaying a Node structure in Swing.
- TreeVisualizer(TreeDisplayListener, String, NodePlace) - 类的构造器 weka.gui.treevisualizer.TreeVisualizer
-
Constructs Displayer to display a tree provided in a dot format.
- TreeVisualizer(TreeDisplayListener, Node, NodePlace) - 类的构造器 weka.gui.treevisualizer.TreeVisualizer
-
Constructs Displayer with the specified Node as the top of the tree, and uses the NodePlacer to place the Nodes.
- TRIANGLEDOWN_SHAPE - 类中的静态变量 weka.gui.visualize.Plot2D
- TRIANGLEUP_SHAPE - 类中的静态变量 weka.gui.visualize.Plot2D
- Trie - weka.core中的类
-
A class representing a Trie data structure for strings.
- Trie() - 类的构造器 weka.core.Trie
-
initializes the data structure
- Trie.TrieIterator - weka.core中的类
-
Represents an iterator over a trie
- Trie.TrieNode - weka.core中的类
-
Represents a node in the trie.
- TrieIterator(Trie.TrieNode) - 类的构造器 weka.core.Trie.TrieIterator
-
initializes the iterator
- TrieNode(char) - 类的构造器 weka.core.Trie.TrieNode
-
initializes the node
- TrieNode(Character) - 类的构造器 weka.core.Trie.TrieNode
-
initializes the node
- trim() - 类中的方法 weka.gui.LogWindow
-
trims the JTextPane, if too big
- trim(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.ChisqMixture
-
Trims the small values of the estaimte
- trim(DoubleVector) - 类中的方法 weka.classifiers.functions.pace.NormalMixture
-
Trims the small values of the estaimte
- trimToSize() - 类中的方法 weka.core.FastVector
-
Sets the vector's capacity to its size.
- TRUE - 接口中的静态变量 weka.core.mathematicalexpression.sym
- TRUE - 接口中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.sym
- TRUE_NEG - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
true-negative
- TRUE_NEG_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: True Negatives
- TRUE_POS - 类中的静态变量 weka.classifiers.meta.ThresholdSelector
-
true-positive
- TRUE_POS_NAME - 类中的静态变量 weka.classifiers.evaluation.ThresholdCurve
-
attribute name: True Positives
- trueNegativeRate(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the true negative rate with respect to a particular class.
- truePositiveRate(int) - 类中的方法 weka.classifiers.Evaluation
-
Calculate the true positive rate with respect to a particular class.
- TStartTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.SimulatedAnnealing
- TStartTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.SimulatedAnnealing
- turnChecksOff() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Turns off checks for missing values, etc.
- turnChecksOff() - 类中的方法 weka.classifiers.functions.SMO
-
Turns off checks for missing values, etc.
- turnChecksOff() - 类中的方法 weka.classifiers.mi.MISMO
-
Turns off checks for missing values, etc.
- turnChecksOn() - 类中的方法 weka.classifiers.functions.LinearRegression
-
Turns on checks for missing values, etc.
- turnChecksOn() - 类中的方法 weka.classifiers.functions.SMO
-
Turns on checks for missing values, etc.
- turnChecksOn() - 类中的方法 weka.classifiers.mi.MISMO
-
Turns on checks for missing values, etc.
- TwoClassStats - weka.classifiers.evaluation中的类
-
Encapsulates performance functions for two-class problems.
- TwoClassStats(double, double, double, double) - 类的构造器 weka.classifiers.evaluation.TwoClassStats
-
Creates the TwoClassStats with the given initial performance values.
- TwoWayNominalSplit - weka.classifiers.trees.adtree中的类
-
Class representing a two-way split on a nominal attribute, of the form: either 'is some_value' or 'is not some_value'.
- TwoWayNominalSplit(int, int) - 类的构造器 weka.classifiers.trees.adtree.TwoWayNominalSplit
-
Creates a new two-way nominal splitter.
- TwoWayNumericSplit - weka.classifiers.trees.adtree中的类
-
Class representing a two-way split on a numeric attribute, of the form: either 'is < some_value' or 'is >= some_value'.
- TwoWayNumericSplit(int, double) - 类的构造器 weka.classifiers.trees.adtree.TwoWayNumericSplit
-
Creates a new two-way numeric splitter.
- type() - 类中的方法 weka.core.Attribute
-
Returns the attribute's type as an integer.
- TYPE - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The type of a technical report---for example, ``Research Note''.
- typeIsNumeric(int) - 类中的静态方法 weka.gui.sql.ResultSetHelper
-
returns whether the SQL type is numeric (and therefore the justification should be right).
- typeName(int) - 类中的静态方法 weka.experiment.DatabaseUtils
-
Returns the name associated with a SQL type.
- typeTipText() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the tip text for this property
- typeTipText() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the tip text for this property
- typeToClass(int) - 类中的静态方法 weka.gui.sql.ResultSetHelper
-
Returns the class associated with a SQL type.
U
- uminus() - 类中的方法 weka.core.matrix.Matrix
-
Unary minus
- UNARY_ATTRIBUTES - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle unary attributes
- UNARY_CLASS - enum class 中的枚举常量 weka.core.Capabilities.Capability
-
can handle unary classes
- UnassignedClassException - weka.core中的异常错误
-
Exception that is raised when trying to use some data that has no class assigned to it, but a class is needed to perform the operation.
- UnassignedClassException() - 异常错误的构造器 weka.core.UnassignedClassException
-
Creates a new UnassignedClassException with no message.
- UnassignedClassException(String) - 异常错误的构造器 weka.core.UnassignedClassException
-
Creates a new UnassignedClassException.
- UnassignedDatasetException - weka.core中的异常错误
-
Exception that is raised when trying to use something that has no reference to a dataset, when one is required.
- UnassignedDatasetException() - 异常错误的构造器 weka.core.UnassignedDatasetException
-
Creates a new UnassignedDatasetException with no message.
- UnassignedDatasetException(String) - 异常错误的构造器 weka.core.UnassignedDatasetException
-
Creates a new UnassignedDatasetException.
- unbackQuoteChars(String) - 类中的静态方法 weka.core.Utils
-
The inverse operation of backQuoteChars().
- unclassified() - 类中的方法 weka.classifiers.Evaluation
-
Gets the number of instances not classified (that is, for which no prediction was made by the classifier).
- UNCLASSIFIED - 接口中的静态变量 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
- UNCONNECTED - 类中的静态变量 weka.classifiers.functions.neural.NeuralConnection
-
This unit is not connected to any others.
- UNDEFINED - 接口中的静态变量 weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
- undefinedDistribution - 类中的静态变量 weka.core.matrix.Maths
-
Distribution type: undefined
- undo() - 类中的方法 weka.classifiers.bayes.net.EditableBayesNet
-
undo the last edit action performed on the network.
- undo() - 接口中的方法 weka.core.Undoable
-
undoes the last action
- undo() - 类中的方法 weka.gui.arffviewer.ArffPanel
-
performs an undo action
- undo() - 类中的方法 weka.gui.arffviewer.ArffSortedTableModel
-
undoes the last action
- undo() - 类中的方法 weka.gui.arffviewer.ArffTableModel
-
undoes the last action
- undo() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
undoes the last action
- undo() - 类中的方法 weka.gui.explorer.PreprocessPanel
-
Reverts to the last backed up version of the dataset.
- Undoable - weka.core中的接口
-
Interface implemented by classes that support undo.
- UNHANDLED_DIALOG - 类中的静态变量 weka.gui.ConverterFileChooser
-
unhandled type of dialog
- UNIFORM_RANDOM - 类中的静态变量 weka.datagenerators.clusterers.SubspaceCluster
-
cluster type: uniform/random
- unique() - 类中的方法 weka.classifiers.functions.pace.DiscreteFunction
-
Makes each individual point value unique
- uniqueCount - 类中的变量 weka.core.AttributeStats
-
The number of values that only appear once
- UNKNOWN - enum class 中的枚举常量 weka.core.RevisionUtils.Type
-
unknown source control revision.
- UNKNOWN_NOMINAL_VALUE - 类中的静态变量 weka.core.pmml.MappingInfo
-
Index for incoming nominal values that are not defined in the mining schema.
- unnormalizedKernel(char[], char[]) - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
evaluates the unnormalized kernel between s and t.
- unpivoting(IntVector, int) - 类中的方法 weka.core.matrix.DoubleVector
-
Returns a vector from the pivoting indices.
- unprunedTipText() - 类中的方法 weka.classifiers.rules.PART
-
Returns the tip text for this property
- unprunedTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- unprunedTipText() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the tip text for this property
- unprunedTipText() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns the tip text for this property
- UNPUBLISHED - enum class 中的枚举常量 weka.core.TechnicalInformation.Type
-
A document having an author and title, but not formally published.
- unquote(String) - 类中的静态方法 weka.core.Utils
-
unquotes are previously quoted string (but only if necessary), i.e., it removes the single quotes around it.
- UNSET - 类中的静态变量 weka.filters.unsupervised.attribute.ClassAssigner
-
unset the class attribute.
- unsorted() - 类中的方法 weka.core.matrix.DoubleVector
-
Returns true if vector not sorted
- UnsupervisedAttributeEvaluator - weka.attributeSelection中的类
-
Abstract unsupervised attribute evaluator.
- UnsupervisedAttributeEvaluator() - 类的构造器 weka.attributeSelection.UnsupervisedAttributeEvaluator
- UnsupervisedFilter - weka.filters中的接口
-
Interface for filters that do not need a class attribute.
- UnsupervisedSubsetEvaluator - weka.attributeSelection中的类
-
Abstract unsupervised attribute subset evaluator.
- UnsupervisedSubsetEvaluator() - 类的构造器 weka.attributeSelection.UnsupervisedSubsetEvaluator
- UnsupportedAttributeTypeException - weka.core中的异常错误
-
Exception that is raised by an object that is unable to process some of the attribute types it has been passed.
- UnsupportedAttributeTypeException() - 异常错误的构造器 weka.core.UnsupportedAttributeTypeException
-
Creates a new UnsupportedAttributeTypeException with no message.
- UnsupportedAttributeTypeException(String) - 异常错误的构造器 weka.core.UnsupportedAttributeTypeException
-
Creates a new UnsupportedAttributeTypeException.
- UnsupportedClassTypeException - weka.core中的异常错误
-
Exception that is raised by an object that is unable to process the class type of the data it has been passed.
- UnsupportedClassTypeException() - 异常错误的构造器 weka.core.UnsupportedClassTypeException
-
Creates a new UnsupportedClassTypeException with no message.
- UnsupportedClassTypeException(String) - 异常错误的构造器 weka.core.UnsupportedClassTypeException
-
Creates a new UnsupportedClassTypeException.
- update(double) - 类中的方法 weka.core.matrix.FlexibleDecimalFormat
- update(int, Instances, double, double, double[], double) - 类中的方法 weka.classifiers.bayes.blr.GaussianPriorImpl
-
Update function specific to Laplace Prior.
- update(int, Instances, double, double, double[], double) - 类中的方法 weka.classifiers.bayes.blr.LaplacePriorImpl
-
Update function specific to Laplace Prior.
- update(int, Instances, double, double, double[], double) - 类中的方法 weka.classifiers.bayes.blr.Prior
-
Interface for the update functions for different types of priors.
- update(Graphics) - 类中的方法 weka.gui.SplashWindow
-
Updates the display area of the window.
- update(String) - 类中的方法 weka.experiment.DatabaseUtils
-
Executes a SQL DDL query or an INSERT, DELETE or UPDATE.
- update(MarginCalculator.JunctionTreeNode) - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator
-
marginalize junciontTreeNode node over all nodes outside the separator set
- update(Instance) - 接口中的方法 weka.core.DistanceFunction
-
Update the distance function (if necessary) for the newly added instance.
- update(Instance) - 类中的方法 weka.core.neighboursearch.BallTree
-
Adds one instance to the BallTree.
- update(Instance) - 类中的方法 weka.core.neighboursearch.CoverTree
-
Adds an instance to the cover tree.
- update(Instance) - 类中的方法 weka.core.neighboursearch.KDTree
-
Adds one instance to the KDTree.
- update(Instance) - 类中的方法 weka.core.neighboursearch.LinearNNSearch
-
Updates the LinearNNSearch to cater for the new added instance.
- update(Instance) - 类中的方法 weka.core.neighboursearch.NearestNeighbourSearch
-
Updates the NearNeighbourSearch algorithm for the new added instance.
- update(Instance) - 类中的方法 weka.core.NormalizableDistance
-
Update the distance function (if necessary) for the newly added instance.
- upDate(Instances) - 类中的方法 weka.associations.tertius.LiteralSet
-
Update the number of counter-instances of this set in the dataset.
- upDate(Instances) - 类中的方法 weka.associations.tertius.Rule
-
Update the number of counter-instances of this rule in the dataset.
- UpdateableClassifier - weka.classifiers中的接口
-
Interface to incremental classification models that can learn using one instance at a time.
- UpdateableClusterer - weka.clusterers中的接口
-
Interface to incremental cluster models that can learn using one instance at a time.
- updateChildPropertySheet() - 类中的方法 weka.gui.GenericObjectEditor.GOEPanel
-
Updates the child property sheet, and creates if needed.
- updateClassifier(BayesNet, Instance) - 类中的方法 weka.classifiers.bayes.net.estimate.BayesNetEstimator
-
Updates the classifier with the given instance.
- updateClassifier(BayesNet, Instance) - 类中的方法 weka.classifiers.bayes.net.estimate.BMAEstimator
-
Updates the classifier with the given instance.
- updateClassifier(BayesNet, Instance) - 类中的方法 weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
-
Updates the classifier with the given instance.
- updateClassifier(BayesNet, Instance) - 类中的方法 weka.classifiers.bayes.net.estimate.SimpleEstimator
-
Updates the classifier with the given instance.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.bayes.AODE
-
Updates the classifier with the given instance.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.bayes.AODEsr
-
Updates the classifier with the given instance.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.bayes.BayesNet
-
Updates the classifier with the given instance.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.bayes.DMNBtext.DNBBinary
- updateClassifier(Instance) - 类中的方法 weka.classifiers.bayes.DMNBtext
-
Updates the classifier with the given instance.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Updates the classifier with the given instance.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
-
Updates the classifier with the given instance.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.functions.SPegasos
-
Updates the classifier with the given instance.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.functions.Winnow
-
Updates the classifier with a new learning example
- updateClassifier(Instance) - 类中的方法 weka.classifiers.lazy.IB1
-
Updates the classifier.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.lazy.IBk
-
Adds the supplied instance to the training set.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.lazy.KStar
-
Adds the supplied instance to the training set
- updateClassifier(Instance) - 类中的方法 weka.classifiers.lazy.LWL
-
Adds the supplied instance to the training set.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
-
Updates the classifier.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.misc.HyperPipes
-
Updates the classifier.
- updateClassifier(Instance) - 类中的方法 weka.classifiers.rules.NNge
-
Updates the classifier using the given instance.
- updateClassifier(Instance) - 接口中的方法 weka.classifiers.UpdateableClassifier
-
Updates a classifier using the given instance.
- updateClusterer(Instance) - 类中的方法 weka.clusterers.Cobweb
-
Adds an instance to the clusterer.
- updateClusterer(Instance) - 接口中的方法 weka.clusterers.UpdateableClusterer
-
Adds an instance to the clusterer.
- upDateCounter(Instance) - 类中的方法 weka.associations.ItemSet
-
Updates counter of item set with respect to given transaction.
- upDateCounter(Instance, Instance) - 类中的方法 weka.associations.LabeledItemSet
-
Updates counter of item set with respect to given transaction.
- updateCounters(ItemSet) - 类中的方法 weka.associations.PriorEstimation
-
updates the support count of an item set
- upDateCounters(FastVector, Instances) - 类中的静态方法 weka.associations.ItemSet
-
Updates counters for a set of item sets and a set of instances.
- upDateCounters(FastVector, Instances, Instances) - 类中的静态方法 weka.associations.LabeledItemSet
-
Updates counter of a specific item set
- updateFinished() - 类中的方法 weka.clusterers.Cobweb
-
Singals the end of the updating.
- updateFinished() - 接口中的方法 weka.clusterers.UpdateableClusterer
-
Signals the end of the updating.
- updateFrameTitle() - 类中的方法 weka.gui.arffviewer.ArffViewerMainPanel
-
sets the title of the parent frame, if one was provided
- updateFromChild() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator
-
marginalize junciontTreeNode node over all nodes outside the separator set of the child clique
- updateFromParent() - 类中的方法 weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator
-
marginalize junciontTreeNode node over all nodes outside the separator set of the parent clique
- updateJavadoc() - 类中的方法 weka.core.Javadoc
-
generates the Javadoc and returns it applied to the source file if one was provided, otherwise an empty string.
- updateNormalization(Instance) - 类中的方法 weka.classifiers.mi.CitationKNN
-
Updates the normalization of each attribute.
- updatePointCount(int) - 类中的方法 weka.core.neighboursearch.PerformanceStats
-
adds the given number to the point count.
- updatePriors(Instance) - 类中的方法 weka.classifiers.Evaluation
-
Updates the class prior probabilities (when incrementally training)
- UpdateQueue - weka.clusterers.forOPTICSAndDBScan.Utils中的类
-
UpdateQueue.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 27, 2004
Time: 5:36:35 PM
$ Revision 1.4 $ - UpdateQueue() - 类的构造器 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue
-
Creates a new PriorityQueue (backed on a binary heap) with the ability to efficiently update the priority of the stored objects in the heap.
- UpdateQueueElement - weka.clusterers.forOPTICSAndDBScan.Utils中的类
-
UpdateQueueElement.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 31, 2004
Time: 6:43:18 PM
$ Revision 1.4 $ - UpdateQueueElement(double, Object, String) - 类的构造器 weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueueElement
- updateRanges(Instance) - 类中的方法 weka.core.NormalizableDistance
-
Update the ranges if a new instance comes.
- updateRanges(Instance, double[][]) - 类中的方法 weka.core.NormalizableDistance
-
Updates the ranges given a new instance.
- updateRanges(Instance, int, double[][]) - 类中的方法 weka.core.NormalizableDistance
-
Updates the minimum and maximum and width values for all the attributes based on a new instance.
- updateRangesFirst(Instance, int, double[][]) - 类中的方法 weka.core.NormalizableDistance
-
Used to initialize the ranges.
- UpdateReferenceSet(int, int) - 类中的方法 weka.attributeSelection.ScatterSearchV1
-
Update the ReferenceSet putting the new obtained Solutions there
- updateResult(String) - 类中的方法 weka.gui.ResultHistoryPanel
-
Tells any component currently displaying the named result that the contents of the result text in the StringBuffer have been updated.
- updateSupportCount(FastVector, FastVector) - 类中的静态方法 weka.associations.gsp.Sequence
-
Updates the support count of a set of Sequence candidates according to a given set of data sequences.
- updateWeights(double, double) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this function to update the weight values at this unit.
- updateWeights(double, double) - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Call this function to update the weight values at this unit.
- updateWeights(NeuralNode, double, double) - 类中的方法 weka.classifiers.functions.neural.LinearUnit
-
This function will calculate what the change in weights should be and also update them.
- updateWeights(NeuralNode, double, double) - 接口中的方法 weka.classifiers.functions.neural.NeuralMethod
-
This function will calculate what the change in weights should be and also update them.
- updateWeights(NeuralNode, double, double) - 类中的方法 weka.classifiers.functions.neural.SigmoidUnit
-
This function will calculate what the change in weights should be and also update them.
- upperBoundMinSupportTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- upperBoundMinSupportTipText() - 类中的方法 weka.associations.FPGrowth
-
Returns the tip text for this property
- upperNumericBoundIsOpen() - 类中的方法 weka.core.Attribute
-
Returns whether the upper numeric bound of the attribute is open.
- upperSizeTipText() - 类中的方法 weka.experiment.LearningRateResultProducer
-
Returns the tip text for this property
- URL - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The WWW Universal Resource Locator that points to the item being referenced.
- URLSourcedLoader - weka.core.converters中的接口
-
Interface to a loader that can load from a http url
- urlTipText() - 类中的方法 weka.core.converters.DatabaseLoader
-
the tip text for this property
- urlTipText() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the tip text for this property.
- USE_DYNAMIC - 类中的静态变量 weka.gui.GenericPropertiesCreator
-
name of property whether to use the dynamic approach or the old GenericObjectEditor.props file
- useADTreeTipText() - 类中的方法 weka.classifiers.bayes.BayesNet
- useAICTipText() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the tip text for this property
- useAICTipText() - 类中的方法 weka.classifiers.trees.FT
-
Returns the tip text for this property
- useAICTipText() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the tip text for this property
- useArcReversalTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.HillClimber
- useArcReversalTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.HillClimber
- useBetterEncodingTipText() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns the tip text for this property
- useCrossOverTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- useCrossOverTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- useCrossValidationTipText() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the tip text for this property
- useDefaultVisual() - 类中的方法 weka.gui.beans.AbstractDataSink
-
Use the default images for a data source
- useDefaultVisual() - 类中的方法 weka.gui.beans.AbstractDataSource
-
Use the default images for a data source
- useDefaultVisual() - 类中的方法 weka.gui.beans.AbstractEvaluator
-
Use the default images for an evaluator
- useDefaultVisual() - 类中的方法 weka.gui.beans.AbstractTestSetProducer
-
Use the default visual for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.AbstractTrainAndTestSetProducer
-
Use the default visual for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.AbstractTrainingSetProducer
-
Use the default visual for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.Associator
-
Use the default visual appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.AttributeSummarizer
-
Use the default appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.ClassAssigner
- useDefaultVisual() - 类中的方法 weka.gui.beans.Classifier
-
Use the default visual appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.ClassValuePicker
- useDefaultVisual() - 类中的方法 weka.gui.beans.Clusterer
-
Use the default visual appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.CostBenefitAnalysis
- useDefaultVisual() - 类中的方法 weka.gui.beans.DataVisualizer
-
Use the default appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.Filter
-
Use the default visual appearance
- useDefaultVisual() - 类中的方法 weka.gui.beans.GraphViewer
-
Use the default visual appearance
- useDefaultVisual() - 类中的方法 weka.gui.beans.InstanceStreamToBatchMaker
-
Use the default visual appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.MetaBean
-
Use the default visual appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.ModelPerformanceChart
-
Use the default appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.PredictionAppender
-
Use the default images for a data source
- useDefaultVisual() - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Use the default images for this bean.
- useDefaultVisual() - 类中的方法 weka.gui.beans.StripChart
-
Use the default visual appearance for this bean
- useDefaultVisual() - 类中的方法 weka.gui.beans.TextViewer
-
Use the default visual appearance for this bean
- useDefaultVisual() - 接口中的方法 weka.gui.beans.Visible
-
Use the default visual representation
- useDynamic() - 类中的方法 weka.gui.GenericPropertiesCreator
-
gets whether the dynamic approach should be used or not
- useEqualFrequencyTipText() - 类中的方法 weka.classifiers.meta.RegressionByDiscretization
-
Returns the tip text for this property
- useEqualFrequencyTipText() - 类中的方法 weka.filters.unsupervised.attribute.Discretize
-
Returns the tip text for this property
- useEqualFrequencyTipText() - 类中的方法 weka.filters.unsupervised.attribute.PKIDiscretize
-
Returns the tip text for this property
- useErrorRateTipText() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the tip text for this property
- useFilter(Instances, Filter) - 类中的静态方法 weka.filters.Filter
-
Filters an entire set of instances through a filter and returns the new set.
- useGiniTipText() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the tip text for this property
- useIBkTipText() - 类中的方法 weka.classifiers.rules.DecisionTable
-
Returns the tip text for this property
- useKDTreeTipText() - 类中的方法 weka.clusterers.XMeans
-
Returns the tip text for this property.
- useKernelEstimatorTipText() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns the tip text for this property
- useKononenkoTipText() - 类中的方法 weka.filters.supervised.attribute.Discretize
-
Returns the tip text for this property
- useLaplaceTipText() - 类中的方法 weka.classifiers.bayes.AODEsr
-
Returns the tip text for this property
- useLaplaceTipText() - 类中的方法 weka.classifiers.trees.J48
-
Returns the tip text for this property
- useLaplaceTipText() - 类中的方法 weka.classifiers.trees.J48graft
-
Returns the tip text for this property
- useLeastValuesTipText() - 类中的方法 weka.filters.unsupervised.instance.RemoveFrequentValues
-
Returns the tip text for this property
- useLowerOrderTipText() - 类中的方法 weka.classifiers.functions.supportVector.PolyKernel
-
Returns the tip text for this property
- useMEstimatesTipText() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns the tip text for this property
- useMissingTipText() - 类中的方法 weka.filters.unsupervised.attribute.AddNoise
-
Returns the tip text for this property
- useMutationTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- useMutationTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- useNoPriors() - 类中的方法 weka.classifiers.Evaluation
-
disables the use of priors, e.g., in case of de-serialized schemes that have no access to the original training set, but are evaluated on a set set.
- useNormalizationTipText() - 类中的方法 weka.classifiers.functions.supportVector.StringKernel
-
Returns the tip text for this property
- useOneSETipText() - 类中的方法 weka.classifiers.trees.BFTree
-
Returns the tip text for this property
- useOneSETipText() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Returns the tip text for this property
- useORForMustContainListTipText() - 类中的方法 weka.associations.FPGrowth
-
Returns the tip text for this property
- usePairwiseCouplingTipText() - 类中的方法 weka.classifiers.meta.MultiClassClassifier
- useProbTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
- usePruneTipText() - 类中的方法 weka.classifiers.trees.SimpleCart
-
Return the tip text for this property
- usePruningTipText() - 类中的方法 weka.classifiers.rules.JRip
-
Returns the tip text for this property
- UserClassifier - weka.classifiers.trees中的类
-
Interactively classify through visual means.
- UserClassifier() - 类的构造器 weka.classifiers.trees.UserClassifier
-
Constructor
- userCommand(TreeDisplayEvent) - 类中的方法 weka.classifiers.trees.UserClassifier
-
Receives user choices from the tree view, and then deals with these choices.
- userCommand(TreeDisplayEvent) - 接口中的方法 weka.gui.treevisualizer.TreeDisplayListener
-
Gets called when the user selects something, in the tree display.
- userDataEvent(VisualizePanelEvent) - 类中的方法 weka.classifiers.trees.UserClassifier
-
This receives shapes from the data view.
- userDataEvent(VisualizePanelEvent) - 接口中的方法 weka.gui.visualize.VisualizePanelListener
-
This method receives an object containing the shapes, instances inside and outside these shapes and the attributes these shapes were created in.
- useRelativePathTipText() - 类中的方法 weka.core.converters.AbstractFileLoader
-
Tip text suitable for displaying int the GUI
- useRelativePathTipText() - 类中的方法 weka.core.converters.AbstractFileSaver
-
Tip text suitable for displaying int the GUI
- useResamplingTipText() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns the tip text for this property
- useResamplingTipText() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the tip text for this property
- useResamplingTipText() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
- usernameTipText() - 类中的方法 weka.experiment.DatabaseUtils
-
Returns the tip text for this property.
- UserRequestAcceptor - weka.gui.beans中的接口
-
Interface to something that can accept requests from a user to perform some action
- userTipText() - 类中的方法 weka.core.converters.DatabaseLoader
-
the tip text for this property
- userTipText() - 类中的方法 weka.core.converters.DatabaseSaver
-
Returns the tip text for this property.
- useStemmer(Stemmer, String[]) - 类中的静态方法 weka.core.stemmers.Stemming
-
Applies the given stemmer according to the given options.
- useStoplistTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- useSupervisedDiscretizationTipText() - 类中的方法 weka.classifiers.bayes.NaiveBayes
-
Returns the tip text for this property
- useTournamentSelectionTipText() - 类中的方法 weka.classifiers.bayes.net.search.global.GeneticSearch
- useTournamentSelectionTipText() - 类中的方法 weka.classifiers.bayes.net.search.local.GeneticSearch
- useTrainingTipText() - 类中的方法 weka.attributeSelection.ClassifierSubsetEval
-
Returns the tip text for this property
- useUnsmoothedTipText() - 类中的方法 weka.classifiers.trees.m5.M5Base
-
Returns the tip text for this property
- useVariant1TipText() - 类中的方法 weka.classifiers.functions.supportVector.RegSMOImproved
-
Returns the tip text for this property
- Utils - weka.core中的类
-
Class implementing some simple utility methods.
- Utils() - 类的构造器 weka.core.Utils
V
- VAL_ANIMATEDICONPATH - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the animatedIconPath property
- VAL_ASSOCIATEDCONNECTIONS - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the associatedConnections property
- VAL_BEAN - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the bean property
- VAL_BEANCONTEXT - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the beanContext property
- VAL_BLUE - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the blue property
- VAL_CELLS - 类中的静态变量 weka.core.xml.XMLBasicSerialization
-
the matrix cells
- VAL_COLOR - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the color property
- VAL_CUSTOM_NAME - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the customName property
- VAL_DATE - 类中的静态变量 weka.core.xml.XMLInstances
-
the value for date
- VAL_DIR - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the dir property
- VAL_EVENTNAME - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the eventname property
- VAL_FILE - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the file property
- VAL_FONT - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the font property
- VAL_GREEN - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the green property
- VAL_HEIGHT - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the height property
- VAL_HIDDEN - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the hidden property
- VAL_ICONPATH - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the iconpath property
- VAL_ID - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the id property
- VAL_INPUTS - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the input property
- VAL_INPUTSID - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the input id property
- VAL_KEY - 类中的静态变量 weka.core.xml.XMLBasicSerialization
-
the value for a mapping-key, e.g., Maps
- VAL_LOADER - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the loader property
- VAL_LOCATION - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the location property
- VAL_MAPPING - 类中的静态变量 weka.core.xml.XMLBasicSerialization
-
the value for mapping, e.g., Maps
- VAL_NAME - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the value property
- VAL_NO - 类中的静态变量 weka.core.xml.XMLDocument
-
the value "no".
- VAL_NO - 类中的静态变量 weka.core.xml.XMLSerialization
-
the value "no" for the primitive and array attribute
- VAL_NOMINAL - 类中的静态变量 weka.core.xml.XMLInstances
-
the value for nominal
- VAL_NORMAL - 类中的静态变量 weka.core.xml.XMLInstances
-
the value for normal
- VAL_NUMERIC - 类中的静态变量 weka.core.xml.XMLInstances
-
the value for numeric
- VAL_OPTIONS - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the options property
- VAL_ORIGINALCOORDS - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the originalCoords property
- VAL_OUTPUTS - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the outputs id property
- VAL_OUTPUTSID - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the outputs property
- VAL_PREFIX - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the prefix property
- VAL_RED - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the red property
- VAL_RELATIONAL - 类中的静态变量 weka.core.xml.XMLInstances
-
the value for relational
- VAL_RELATIONNAMEFORFILENAME - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the relationNameForFilename property (Saver)
- VAL_RELATIVE_PATH - 类中的静态变量 weka.gui.beans.xml.XMLBeans
- VAL_ROOT - 类中的静态变量 weka.core.xml.XMLSerialization
-
the value of the name for the root node
- VAL_SAVER - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the saver property
- VAL_SIZE - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the size property
- VAL_SOURCEID - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the source property
- VAL_SPARSE - 类中的静态变量 weka.core.xml.XMLInstances
-
the value for sparse
- VAL_STRING - 类中的静态变量 weka.core.xml.XMLInstances
-
the value for string
- VAL_STYLE - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the style property
- VAL_SUBFLOW - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the subFlow property
- VAL_TARGETID - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the target property
- VAL_TEXT - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the text property
- VAL_TYPE_CLASSIFIER - 类中的静态变量 weka.core.xml.XMLOptions
-
a value of the type attribute.
- VAL_TYPE_FLAG - 类中的静态变量 weka.core.xml.XMLOptions
-
a value of the type attribute.
- VAL_TYPE_HYPHENS - 类中的静态变量 weka.core.xml.XMLOptions
-
a value of the type attribute.
- VAL_TYPE_OPTIONHANDLER - 类中的静态变量 weka.core.xml.XMLOptions
-
a value of the type attribute.
- VAL_TYPE_QUOTES - 类中的静态变量 weka.core.xml.XMLOptions
-
a value of the type attribute.
- VAL_TYPE_SINGLE - 类中的静态变量 weka.core.xml.XMLOptions
-
a value of the type attribute.
- VAL_VALUE - 类中的静态变量 weka.core.xml.XMLBasicSerialization
-
the value for mapping-value, e.g., Maps
- VAL_WIDTH - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the width property
- VAL_X - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the x property
- VAL_Y - 类中的静态变量 weka.gui.beans.xml.XMLBeans
-
the value of the y property
- VAL_YES - 类中的静态变量 weka.core.xml.XMLDocument
-
the value "yes".
- VAL_YES - 类中的静态变量 weka.core.xml.XMLSerialization
-
the value "yes" for the primitive and array attribute
- VALID - enum class 中的枚举常量 weka.core.pmml.FieldMetaInfo.Value.Property
- validateFileFormat(Tag) - 类中的方法 weka.gui.beans.SerializedModelSaver
-
Validate the file format.
- validationChunkSizeTipText() - 类中的方法 weka.classifiers.meta.RacedIncrementalLogitBoost
- validationSetSizeTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- validationThresholdTipText() - 类中的方法 weka.classifiers.functions.MultilayerPerceptron
- value - 类中的变量 weka.classifiers.lazy.kstar.KStarCache.TableEntry
-
scale factor or stop parameter
- value - 类中的变量 weka.experiment.PropertyNode
-
The current property value
- value(int) - 类中的方法 weka.core.Attribute
-
Returns a value of a nominal or string attribute.
- value(int) - 类中的方法 weka.core.BinarySparseInstance
-
Returns an instance's attribute value in internal format.
- value(int) - 类中的方法 weka.core.Instance
-
Returns an instance's attribute value in internal format.
- value(int) - 类中的方法 weka.core.SparseInstance
-
Returns an instance's attribute value in internal format.
- value(Attribute) - 类中的方法 weka.core.Instance
-
Returns an instance's attribute value in internal format.
- valueIndicesTipText() - 类中的方法 weka.filters.unsupervised.attribute.MakeIndicator
- valueIsSmallerEqual(Instance, int, double) - 类中的方法 weka.core.EuclideanDistance
-
Returns true if the value of the given dimension is smaller or equal the value to be compared with.
- valueOf(String) - enum class中的静态方法 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
-
Returns the enum constant of this class with the specified name.
- valueOf(String) - enum class中的静态方法 weka.core.Capabilities.Capability
-
Returns the enum constant of this class with the specified name.
- valueOf(String) - enum class中的静态方法 weka.core.logging.Logger.Level
-
Returns the enum constant of this class with the specified name.
- valueOf(String) - enum class中的静态方法 weka.core.pmml.FieldMetaInfo.Interval.Closure
-
Returns the enum constant of this class with the specified name.
- valueOf(String) - enum class中的静态方法 weka.core.pmml.FieldMetaInfo.Optype
-
Returns the enum constant of this class with the specified name.
- valueOf(String) - enum class中的静态方法 weka.core.pmml.FieldMetaInfo.Value.Property
-
Returns the enum constant of this class with the specified name.
- valueOf(String) - enum class中的静态方法 weka.core.RevisionUtils.Type
-
Returns the enum constant of this class with the specified name.
- valueOf(String) - enum class中的静态方法 weka.core.TechnicalInformation.Field
-
Returns the enum constant of this class with the specified name.
- valueOf(String) - enum class中的静态方法 weka.core.TechnicalInformation.Type
-
Returns the enum constant of this class with the specified name.
- values() - enum class中的静态方法 weka.associations.FPGrowth.AssociationRule.METRIC_TYPE
-
Returns an array containing the constants of this enum class, in the order they are declared.
- values() - enum class中的静态方法 weka.core.Capabilities.Capability
-
Returns an array containing the constants of this enum class, in the order they are declared.
- values() - enum class中的静态方法 weka.core.logging.Logger.Level
-
Returns an array containing the constants of this enum class, in the order they are declared.
- values() - enum class中的静态方法 weka.core.pmml.FieldMetaInfo.Interval.Closure
-
Returns an array containing the constants of this enum class, in the order they are declared.
- values() - enum class中的静态方法 weka.core.pmml.FieldMetaInfo.Optype
-
Returns an array containing the constants of this enum class, in the order they are declared.
- values() - enum class中的静态方法 weka.core.pmml.FieldMetaInfo.Value.Property
-
Returns an array containing the constants of this enum class, in the order they are declared.
- values() - enum class中的静态方法 weka.core.RevisionUtils.Type
-
Returns an array containing the constants of this enum class, in the order they are declared.
- values() - enum class中的静态方法 weka.core.TechnicalInformation.Field
-
Returns an array containing the constants of this enum class, in the order they are declared.
- values() - enum class中的静态方法 weka.core.TechnicalInformation.Type
-
Returns an array containing the constants of this enum class, in the order they are declared.
- Values - weka.classifiers.trees.m5中的类
-
Stores some statistics.
- Values(int, int, int, Instances) - 类的构造器 weka.classifiers.trees.m5.Values
-
Constructs an object which stores some statistics of the instances such as sum, squared sum, variance, standard deviation
- valuesListTipText() - 类中的方法 weka.datagenerators.clusterers.SubspaceClusterDefinition
-
Returns the tip text for this property
- valuesOutputTipText() - 类中的方法 weka.associations.Tertius
-
Returns the tip text for this property.
- valueSparse(int) - 类中的方法 weka.core.BinarySparseInstance
-
Returns an instance's attribute value in internal format.
- valueSparse(int) - 类中的方法 weka.core.Instance
-
Returns an instance's attribute value in internal format.
- valuesToString() - 类中的方法 weka.associations.tertius.Rule
-
Return a String giving the confirmation and optimistic estimate of this rule.
- VARIABLE - 接口中的静态变量 weka.core.mathematicalexpression.sym
- variance(double[]) - 类中的静态方法 weka.core.Utils
-
Computes the variance for an array of doubles.
- variance(int) - 类中的方法 weka.core.Instances
-
Computes the variance for a numeric attribute.
- variance(Attribute) - 类中的方法 weka.core.Instances
-
Computes the variance for a numeric attribute.
- varianceCoveredTipText() - 类中的方法 weka.attributeSelection.PrincipalComponents
-
Returns the tip text for this property
- varianceCoveredTipText() - 类中的方法 weka.filters.unsupervised.attribute.PrincipalComponents
-
Returns the tip text for this property.
- VaryNode - weka.classifiers.bayes.net中的类
-
Part of ADTree implementation.
- VaryNode(int) - 类的构造器 weka.classifiers.bayes.net.VaryNode
-
Creates new VaryNode
- VERBOSE - 类中的静态变量 weka.core.ClassDiscovery
-
whether to output some debug information.
- VERBOSE - 类中的静态变量 weka.gui.GenericPropertiesCreator
-
whether to output some debug information
- verboseTipText() - 类中的方法 weka.associations.Apriori
-
Returns the tip text for this property
- verboseTipText() - 类中的方法 weka.attributeSelection.ExhaustiveSearch
-
Returns the tip text for this property
- verboseTipText() - 类中的方法 weka.attributeSelection.LinearForwardSelection
-
Returns the tip text for this property
- verboseTipText() - 类中的方法 weka.attributeSelection.RandomSearch
-
Returns the tip text for this property
- verboseTipText() - 类中的方法 weka.attributeSelection.SubsetSizeForwardSelection
-
Returns the tip text for this property
- verboseTipText() - 类中的方法 weka.classifiers.meta.Dagging
-
Returns the tip text for this property
- Version - weka.core中的类
-
This class contains the version number of the current WEKA release and some methods for comparing another version string.
- Version() - 类的构造器 weka.core.Version
- VERSION - 类中的静态变量 weka.core.Version
-
the complete version
- VERSION_FILE - 类中的静态变量 weka.core.Version
-
the version file
- VFI - weka.classifiers.misc中的类
-
Classification by voting feature intervals.
- VFI() - 类的构造器 weka.classifiers.misc.VFI
- ViewerDialog - weka.gui中的类
-
A downsized version of the ArffViewer, displaying only one Instances-Object.
- ViewerDialog(Frame) - 类的构造器 weka.gui.ViewerDialog
-
initializes the dialog with the given parent
- Visible - weka.gui.beans中的接口
-
Interface to something that has a visible (via BeanVisual) reprentation
- VisualizableErrorEvent - weka.gui.beans中的类
-
Event encapsulating error information for a learning scheme that can be visualized in the DataVisualizer
- VisualizableErrorEvent(Object, PlotData2D) - 类的构造器 weka.gui.beans.VisualizableErrorEvent
- VisualizableErrorListener - weka.gui.beans中的接口
-
Interface to something that can accept VisualizableErrorEvents
- VisualizePanel - weka.gui.explorer中的类
-
A slightly extended MatrixPanel for better support in the Explorer.
- VisualizePanel - weka.gui.visualize中的类
-
This panel allows the user to visualize a dataset (and if provided) a classifier's/clusterer's predictions in two dimensions.
- VisualizePanel() - 类的构造器 weka.gui.explorer.VisualizePanel
- VisualizePanel() - 类的构造器 weka.gui.visualize.VisualizePanel
-
Constructor
- VisualizePanel(VisualizePanelListener) - 类的构造器 weka.gui.visualize.VisualizePanel
-
This constructor allows a VisualizePanelListener to be set.
- VisualizePanelEvent - weka.gui.visualize中的类
-
This event Is fired to a listeners 'userDataEvent' function when The user on the VisualizePanel clicks submit.
- VisualizePanelEvent(FastVector, Instances, Instances, int, int) - 类的构造器 weka.gui.visualize.VisualizePanelEvent
-
This constructor creates the event with all the parameters set.
- VisualizePanelListener - weka.gui.visualize中的接口
-
Interface implemented by a class that is interested in receiving submited shapes from a visualize panel.
- VisualizePlugin - weka.gui.visualize.plugins中的接口
-
Interface implemented by classes loaded dynamically to visualize classifier results in the explorer.
- VisualizeUtils - weka.gui.visualize中的类
-
This class contains utility routines for visualization
- VisualizeUtils() - 类的构造器 weka.gui.visualize.VisualizeUtils
- VLINE - 类中的静态变量 weka.gui.visualize.VisualizePanelEvent
- VOLUME - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The volume of a journal or multi-volume book.
- Vote - weka.classifiers.meta中的类
-
Class for combining classifiers.
- Vote() - 类的构造器 weka.classifiers.meta.Vote
- VotedPerceptron - weka.classifiers.functions中的类
-
Implementation of the voted perceptron algorithm by Freund and Schapire.
- VotedPerceptron() - 类的构造器 weka.classifiers.functions.VotedPerceptron
- voteFlagTipText() - 类中的方法 weka.datagenerators.classifiers.classification.RDG1
-
Returns the tip text for this property
W
- waitUntilFinished() - 类中的方法 weka.gui.beans.FlowRunner
-
Waits until all flows have finished executing before returning
- WAODE - weka.classifiers.bayes中的类
-
WAODE contructs the model called Weightily Averaged One-Dependence Estimators.
For more information, see
L. - WAODE() - 类的构造器 weka.classifiers.bayes.WAODE
- WARNING - enum class 中的枚举常量 weka.core.logging.Logger.Level
-
WARNING level.
- WARNING - 类中的静态变量 weka.core.Debug
-
the log level Warning
- Wavelet - weka.filters.unsupervised.attribute中的类
-
A filter for wavelet transformation.
For more information see:
Wikipedia (2004). - Wavelet() - 类的构造器 weka.filters.unsupervised.attribute.Wavelet
-
default constructor
- weight() - 类中的方法 weka.classifiers.evaluation.NominalPrediction
-
Gets the weight assigned to this prediction.
- weight() - 类中的方法 weka.classifiers.evaluation.NumericPrediction
-
Gets the weight assigned to this prediction.
- weight() - 接口中的方法 weka.classifiers.evaluation.Prediction
-
Gets the weight assigned to this prediction.
- weight() - 类中的方法 weka.core.Attribute
-
Returns the attribute's weight.
- weight() - 类中的方法 weka.core.Instance
-
Returns the instance's weight.
- weight(Instance) - 类中的方法 weka.classifiers.rules.part.ClassifierDecList
-
Returns the weight a rule assigns to an instance.
- WEIGHT_INVERSE - 类中的静态变量 weka.classifiers.lazy.IBk
-
weight by 1/distance.
- WEIGHT_NONE - 类中的静态变量 weka.classifiers.lazy.IBk
-
no weighting.
- WEIGHT_SIMILARITY - 类中的静态变量 weka.classifiers.lazy.IBk
-
weight by 1-distance.
- weightByConfidenceTipText() - 类中的方法 weka.classifiers.misc.VFI
-
Returns the tip text for this property
- weightByDistanceTipText() - 类中的方法 weka.attributeSelection.ReliefFAttributeEval
-
Returns the tip text for this property
- weightedAreaUnderROC() - 类中的方法 weka.classifiers.Evaluation
-
Calculates the weighted (by class size) AUC.
- weightedFalseNegativeRate() - 类中的方法 weka.classifiers.Evaluation
-
Calculates the weighted (by class size) false negative rate.
- weightedFalsePositiveRate() - 类中的方法 weka.classifiers.Evaluation
-
Calculates the weighted (by class size) false positive rate.
- weightedFMeasure() - 类中的方法 weka.classifiers.Evaluation
-
Calculates the weighted (by class size) F-Measure.
- WeightedInstancesHandler - weka.core中的接口
-
Interface to something that makes use of the information provided by instance weights.
- weightedPrecision() - 类中的方法 weka.classifiers.Evaluation
-
Calculates the weighted (by class size) false precision.
- weightedRecall() - 类中的方法 weka.classifiers.Evaluation
-
Calculates the weighted (by class size) recall.
- weightedTrueNegativeRate() - 类中的方法 weka.classifiers.Evaluation
-
Calculates the weighted (by class size) true negative rate.
- weightedTruePositiveRate() - 类中的方法 weka.classifiers.Evaluation
-
Calculates the weighted (by class size) true positive rate.
- weightingKernelTipText() - 类中的方法 weka.classifiers.lazy.LWL
-
Returns the tip text for this property.
- WEIGHTMETHOD_1 - 类中的静态变量 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
weight method: 1.0
- WEIGHTMETHOD_INVERSE1 - 类中的静态变量 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
weight method: 1.0 / Total # of prop.
- WEIGHTMETHOD_INVERSE2 - 类中的静态变量 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
weight method: Total # of prop.
- WEIGHTMETHOD_ORIGINAL - 类中的静态变量 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
weight method: keep the weight to be the same as the original value
- weightMethodTipText() - 类中的方法 weka.classifiers.mi.MIWrapper
-
Returns the tip text for this property
- weightMethodTipText() - 类中的方法 weka.filters.unsupervised.attribute.MultiInstanceToPropositional
-
Returns the tip text for this property
- weights(Instance) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Returns weights if instance is assigned to more than one subset.
- weights(Instance) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns weights if instance is assigned to more than one subset.
- weights(Instance) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Returns weights if instance is assigned to more than one subset.
- weights(Instance) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- weights(Instance) - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Always returns null because there is only one subset.
- weights(Instance) - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Returns weights if instance is assigned to more than one subset.
- weights(Instance) - 类中的方法 weka.classifiers.trees.j48.NoSplit
-
Always returns null because there is only one subset.
- weights(Instance) - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
-
Method not in use
- weightsTipText() - 类中的方法 weka.classifiers.functions.LibLINEAR
-
Returns the tip text for this property
- weightsTipText() - 类中的方法 weka.classifiers.functions.LibSVM
-
Returns the tip text for this property
- weightThresholdTipText() - 类中的方法 weka.classifiers.meta.AdaBoostM1
-
Returns the tip text for this property
- weightThresholdTipText() - 类中的方法 weka.classifiers.meta.LogitBoost
-
Returns the tip text for this property
- weightTipText() - 类中的方法 weka.classifiers.bayes.AODE
-
Returns the tip text for this property
- weightTrimBetaTipText() - 类中的方法 weka.classifiers.functions.SimpleLogistic
-
Returns the tip text for this property
- weightTrimBetaTipText() - 类中的方法 weka.classifiers.trees.FT
-
Returns the tip text for this property
- weightTrimBetaTipText() - 类中的方法 weka.classifiers.trees.LMT
-
Returns the tip text for this property
- weightValue(int) - 类中的方法 weka.classifiers.functions.neural.NeuralConnection
-
Call this to get the weight value on a particular connection.
- weightValue(int) - 类中的方法 weka.classifiers.functions.neural.NeuralNode
-
Call this to get the weight value on a particular connection.
- weka.associations - 程序包 weka.associations
- weka.associations.gsp - 程序包 weka.associations.gsp
- weka.associations.tertius - 程序包 weka.associations.tertius
- weka.attributeSelection - 程序包 weka.attributeSelection
- weka.classifiers - 程序包 weka.classifiers
- weka.classifiers.bayes - 程序包 weka.classifiers.bayes
- weka.classifiers.bayes.blr - 程序包 weka.classifiers.bayes.blr
- weka.classifiers.bayes.net - 程序包 weka.classifiers.bayes.net
- weka.classifiers.bayes.net.estimate - 程序包 weka.classifiers.bayes.net.estimate
- weka.classifiers.bayes.net.search - 程序包 weka.classifiers.bayes.net.search
- weka.classifiers.bayes.net.search.ci - 程序包 weka.classifiers.bayes.net.search.ci
- weka.classifiers.bayes.net.search.fixed - 程序包 weka.classifiers.bayes.net.search.fixed
- weka.classifiers.bayes.net.search.global - 程序包 weka.classifiers.bayes.net.search.global
- weka.classifiers.bayes.net.search.local - 程序包 weka.classifiers.bayes.net.search.local
- weka.classifiers.evaluation - 程序包 weka.classifiers.evaluation
- weka.classifiers.functions - 程序包 weka.classifiers.functions
- weka.classifiers.functions.neural - 程序包 weka.classifiers.functions.neural
- weka.classifiers.functions.pace - 程序包 weka.classifiers.functions.pace
- weka.classifiers.functions.supportVector - 程序包 weka.classifiers.functions.supportVector
- weka.classifiers.lazy - 程序包 weka.classifiers.lazy
- weka.classifiers.lazy.kstar - 程序包 weka.classifiers.lazy.kstar
- weka.classifiers.meta - 程序包 weka.classifiers.meta
- weka.classifiers.meta.nestedDichotomies - 程序包 weka.classifiers.meta.nestedDichotomies
- weka.classifiers.mi - 程序包 weka.classifiers.mi
- weka.classifiers.mi.supportVector - 程序包 weka.classifiers.mi.supportVector
- weka.classifiers.misc - 程序包 weka.classifiers.misc
- weka.classifiers.pmml.consumer - 程序包 weka.classifiers.pmml.consumer
- weka.classifiers.rules - 程序包 weka.classifiers.rules
- weka.classifiers.rules.part - 程序包 weka.classifiers.rules.part
- weka.classifiers.trees - 程序包 weka.classifiers.trees
- weka.classifiers.trees.adtree - 程序包 weka.classifiers.trees.adtree
- weka.classifiers.trees.ft - 程序包 weka.classifiers.trees.ft
- weka.classifiers.trees.j48 - 程序包 weka.classifiers.trees.j48
- weka.classifiers.trees.lmt - 程序包 weka.classifiers.trees.lmt
- weka.classifiers.trees.m5 - 程序包 weka.classifiers.trees.m5
- weka.classifiers.xml - 程序包 weka.classifiers.xml
- weka.clusterers - 程序包 weka.clusterers
- weka.clusterers.forOPTICSAndDBScan.Databases - 程序包 weka.clusterers.forOPTICSAndDBScan.Databases
- weka.clusterers.forOPTICSAndDBScan.DataObjects - 程序包 weka.clusterers.forOPTICSAndDBScan.DataObjects
- weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI - 程序包 weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI
- weka.clusterers.forOPTICSAndDBScan.Utils - 程序包 weka.clusterers.forOPTICSAndDBScan.Utils
- weka.core - 程序包 weka.core
- weka.core.converters - 程序包 weka.core.converters
- weka.core.logging - 程序包 weka.core.logging
- weka.core.mathematicalexpression - 程序包 weka.core.mathematicalexpression
- weka.core.matrix - 程序包 weka.core.matrix
- weka.core.neighboursearch - 程序包 weka.core.neighboursearch
- weka.core.neighboursearch.balltrees - 程序包 weka.core.neighboursearch.balltrees
- weka.core.neighboursearch.covertrees - 程序包 weka.core.neighboursearch.covertrees
- weka.core.neighboursearch.kdtrees - 程序包 weka.core.neighboursearch.kdtrees
- weka.core.pmml - 程序包 weka.core.pmml
- weka.core.stemmers - 程序包 weka.core.stemmers
- weka.core.tokenizers - 程序包 weka.core.tokenizers
- weka.core.xml - 程序包 weka.core.xml
- weka.datagenerators - 程序包 weka.datagenerators
- weka.datagenerators.classifiers.classification - 程序包 weka.datagenerators.classifiers.classification
- weka.datagenerators.classifiers.regression - 程序包 weka.datagenerators.classifiers.regression
- weka.datagenerators.clusterers - 程序包 weka.datagenerators.clusterers
- weka.estimators - 程序包 weka.estimators
- weka.experiment - 程序包 weka.experiment
- weka.experiment.xml - 程序包 weka.experiment.xml
- weka.filters - 程序包 weka.filters
- weka.filters.supervised.attribute - 程序包 weka.filters.supervised.attribute
- weka.filters.supervised.instance - 程序包 weka.filters.supervised.instance
- weka.filters.unsupervised.attribute - 程序包 weka.filters.unsupervised.attribute
- weka.filters.unsupervised.instance - 程序包 weka.filters.unsupervised.instance
- weka.filters.unsupervised.instance.subsetbyexpression - 程序包 weka.filters.unsupervised.instance.subsetbyexpression
- weka.gui - 程序包 weka.gui
- weka.gui.arffviewer - 程序包 weka.gui.arffviewer
- weka.gui.beans - 程序包 weka.gui.beans
- weka.gui.beans.xml - 程序包 weka.gui.beans.xml
- weka.gui.boundaryvisualizer - 程序包 weka.gui.boundaryvisualizer
- weka.gui.experiment - 程序包 weka.gui.experiment
- weka.gui.explorer - 程序包 weka.gui.explorer
- weka.gui.graphvisualizer - 程序包 weka.gui.graphvisualizer
- weka.gui.hierarchyvisualizer - 程序包 weka.gui.hierarchyvisualizer
- weka.gui.sql - 程序包 weka.gui.sql
- weka.gui.sql.event - 程序包 weka.gui.sql.event
- weka.gui.streams - 程序包 weka.gui.streams
- weka.gui.treevisualizer - 程序包 weka.gui.treevisualizer
- weka.gui.visualize - 程序包 weka.gui.visualize
- weka.gui.visualize.plugins - 程序包 weka.gui.visualize.plugins
- WekaException - weka.core中的异常错误
-
Class for Weka-specific exceptions.
- WekaException() - 异常错误的构造器 weka.core.WekaException
-
Creates a new WekaException with no message.
- WekaException(String) - 异常错误的构造器 weka.core.WekaException
-
Creates a new WekaException.
- wekaStaticWrapper(Sourcable, String) - 类中的静态方法 weka.classifiers.Evaluation
-
Wraps a static classifier in enough source to test using the weka class libraries.
- wekaStaticWrapper(Sourcable, String, Instances, Instances) - 类中的静态方法 weka.filters.Filter
-
generates source code from the filter
- WekaTaskMonitor - weka.gui中的类
-
This panel records the number of weka tasks running and displays a simple bird animation while their are active tasks
- WekaTaskMonitor() - 类的构造器 weka.gui.WekaTaskMonitor
-
Constructor
- WekaWrapper - weka.gui.beans中的接口
-
Interface to something that can wrap around a class of Weka algorithms (classifiers, filters etc).
- WEST_CONNECTOR - 类中的静态变量 weka.gui.beans.BeanVisual
- whichSubset(Instance) - 类中的方法 weka.classifiers.trees.j48.BinC45Split
-
Returns index of subset instance is assigned to.
- whichSubset(Instance) - 类中的方法 weka.classifiers.trees.j48.C45Split
-
Returns index of subset instance is assigned to.
- whichSubset(Instance) - 类中的方法 weka.classifiers.trees.j48.ClassifierSplitModel
-
Returns index of subset instance is assigned to.
- whichSubset(Instance) - 类中的方法 weka.classifiers.trees.j48.GraftSplit
- whichSubset(Instance) - 类中的方法 weka.classifiers.trees.j48.NBTreeNoSplit
-
Always returns 0 because only there is only one subset.
- whichSubset(Instance) - 类中的方法 weka.classifiers.trees.j48.NBTreeSplit
-
Returns index of subset instance is assigned to.
- whichSubset(Instance) - 类中的方法 weka.classifiers.trees.j48.NoSplit
-
Always returns 0 because only there is only one subset.
- whichSubset(Instance) - 类中的方法 weka.classifiers.trees.lmt.ResidualSplit
- wholeDataErrTipText() - 类中的方法 weka.classifiers.rules.Ridor
-
Returns the tip text for this property
- width() - 类中的方法 weka.core.matrix.ExponentialFormat
- width() - 类中的方法 weka.core.matrix.FlexibleDecimalFormat
- width() - 类中的方法 weka.core.matrix.FloatingPointFormat
- WIDTH - 类中的静态变量 weka.core.neighboursearch.KDTree
-
The index of WIDTH (MAX-MIN) value in attributes' range array.
- WIDTH - 类中的静态变量 weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Index of width value (max-min) in an array of attributes' range.
- WIDTH - 类中的静态变量 weka.gui.arffviewer.ArffViewerMainPanel
-
default width
- WIDTH - 类中的静态变量 weka.gui.sql.SqlViewer
-
the width property in the history file.
- WIN_STRING - 类中的变量 weka.experiment.ResultMatrix
-
win string
- windowActivated(WindowEvent) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
invoked when a window is activated
- windowClosed(WindowEvent) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
invoked when a window is closed
- windowClosing(WindowEvent) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
invoked when a window is in the process of closing
- windowDeactivated(WindowEvent) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
invoked when a window is deactivated
- windowDeiconified(WindowEvent) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
invoked when a window is deiconified
- windowIconified(WindowEvent) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
invoked when a window is iconified
- windowListChanged() - 类中的方法 weka.gui.Main
-
is called when window list changed somehow (add or remove).
- windowOpened(WindowEvent) - 类中的方法 weka.gui.arffviewer.ArffViewer
-
invoked when a window is has been opened
- windowSizeTipText() - 类中的方法 weka.classifiers.lazy.IBk
-
Returns the tip text for this property.
- Winnow - weka.classifiers.functions中的类
-
Implements Winnow and Balanced Winnow algorithms by Littlestone.
For more information, see
N. - Winnow() - 类的构造器 weka.classifiers.functions.Winnow
- WITHIN_BATCH - 类中的静态变量 weka.gui.beans.IncrementalClassifierEvent
- wordsToKeepTipText() - 类中的方法 weka.filters.unsupervised.attribute.StringToWordVector
-
Returns the tip text for this property.
- WordTokenizer - weka.core.tokenizers中的类
-
A simple tokenizer that is using the java.util.StringTokenizer class to tokenize the strings.
- WordTokenizer() - 类的构造器 weka.core.tokenizers.WordTokenizer
- WrapperSubsetEval - weka.attributeSelection中的类
-
WrapperSubsetEval:
Evaluates attribute sets by using a learning scheme. - WrapperSubsetEval() - 类的构造器 weka.attributeSelection.WrapperSubsetEval
-
Constructor.
- write() - 类中的方法 weka.core.xml.XMLSerializationMethodHandler
-
returns the handler for write methods
- write(byte[], int, int) - 类中的方法 weka.core.Tee
-
Writes
len
bytes from the specified byte array starting at offsetoff
to this stream. - write(int) - 类中的方法 weka.core.Tee
-
Writes the specified byte to this stream.
- write(BufferedWriter) - 类中的方法 weka.core.Stopwords
-
Writes the current stopwords to the given writer.
- write(File) - 类中的方法 weka.core.Stopwords
-
Writes the current stopwords to the given file
- write(File) - 类中的方法 weka.core.xml.XMLDocument
-
writes the current DOM document into the given file.
- write(File, Object) - 类中的静态方法 weka.core.xml.KOML
-
write the XML-serialized object to the given file
- write(File, Object) - 类中的方法 weka.core.xml.XMLSerialization
-
writes the given object into the file
- write(File, Object) - 类中的静态方法 weka.core.xml.XStream
-
write the XML-serialized object to the given file
- write(OutputStream) - 类中的方法 weka.core.xml.XMLDocument
-
writes the current DOM document into the given stream.
- write(OutputStream, Object) - 类中的静态方法 weka.core.SerializationHelper
-
serializes the given object to the specified stream.
- write(OutputStream, Object) - 类中的静态方法 weka.core.xml.KOML
-
writes the XML-serialized object to a stream
- write(OutputStream, Object) - 类中的方法 weka.core.xml.XMLSerialization
-
writes the given object into the stream
- write(OutputStream, Object) - 类中的静态方法 weka.core.xml.XStream
-
writes the XML-serialized object to the given output stream
- write(OutputStream, Instances) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSink
-
writes the data to the given stream (always in ARFF format).
- write(Writer) - 类中的方法 weka.classifiers.CostMatrix
-
Writes out a matrix.
- write(Writer) - 类中的方法 weka.core.matrix.Matrix
-
Writes out a matrix.
- write(Writer) - 类中的方法 weka.core.Matrix
-
已过时。Writes out a matrix.
- write(Writer) - 类中的方法 weka.core.xml.XMLDocument
-
writes the current DOM document into the given writer.
- write(Writer, Object) - 类中的方法 weka.core.xml.XMLSerialization
-
writes the given object into the writer
- write(Writer, Object) - 类中的静态方法 weka.core.xml.XStream
-
writes the XML-serialized object to the given Writer
- write(String) - 类中的方法 weka.core.Stopwords
-
Writes the current stopwords to the given file
- write(String) - 类中的方法 weka.core.xml.XMLDocument
-
writes the current DOM document into the given file.
- write(String, Object) - 类中的静态方法 weka.core.SerializationHelper
-
serializes the given object to the specified file.
- write(String, Object) - 类中的静态方法 weka.core.xml.KOML
-
writes the XML-serialized object to the given file
- write(String, Object) - 类中的方法 weka.core.xml.XMLSerialization
-
writes the given object into the file
- write(String, Object) - 类中的静态方法 weka.core.xml.XStream
-
writes the XML-serialized object to the given file
- write(String, Instances) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSink
-
writes the data to the given file.
- write(String, Experiment) - 类中的静态方法 weka.experiment.Experiment
-
Writes the experiment to disk.
- write(Saver, Instances) - 类中的静态方法 weka.core.converters.ConverterUtils.DataSink
-
writes the data via the given saver.
- write(Instances) - 类中的方法 weka.core.converters.ConverterUtils.DataSink
-
writes the given data either via the saver or to the defined output stream (depending on the constructor).
- writeAll(OutputStream, Object[]) - 类中的静态方法 weka.core.SerializationHelper
-
serializes the given objects to the specified stream.
- writeAll(String, Object[]) - 类中的静态方法 weka.core.SerializationHelper
-
serializes the given objects to the specified file.
- writeBatch() - 类中的方法 weka.core.converters.AbstractSaver
-
Writes to a file in batch mode To be overridden.
- writeBatch() - 类中的方法 weka.core.converters.ArffSaver
-
Writes a Batch of instances
- writeBatch() - 类中的方法 weka.core.converters.C45Saver
-
Writes a Batch of instances
- writeBatch() - 类中的方法 weka.core.converters.CSVSaver
-
Writes a Batch of instances
- writeBatch() - 类中的方法 weka.core.converters.DatabaseSaver
-
Writes a Batch of instances.
- writeBatch() - 类中的方法 weka.core.converters.LibSVMSaver
-
Writes a Batch of instances
- writeBatch() - 接口中的方法 weka.core.converters.Saver
-
Writes to a destination in batch mode
- writeBatch() - 类中的方法 weka.core.converters.SerializedInstancesSaver
-
Writes a Batch of instances.
- writeBatch() - 类中的方法 weka.core.converters.SVMLightSaver
-
Writes a Batch of instances.
- writeBatch() - 类中的方法 weka.core.converters.XRFFSaver
-
Writes a Batch of instances
- writeBeanConnection(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given BeanConncetion to a DOM structure.
- writeBeanInstance(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given BeanInstance to a DOM structure.
- writeBeanLoader(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given Loader (a bean) to a DOM structure.
- writeBeanSaver(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given Saver (a bean) to a DOM structure.
- writeBeanVisual(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given BeanVisual to a DOM structure.
- writeCollection(Element, Object, String) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
adds the given Collection to a DOM structure.
- writeColor(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given Color to a DOM structure.
- writeColorUIResource(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given ColorUIResource to a DOM structure.
- writeCostMatrixOld(Element, Object, String) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
adds the given CostMatrix (old) to a DOM structure.
- writeCurve(String, Estimator, double, double, int) - 类中的静态方法 weka.estimators.EstimatorUtils
-
Output of an n points of a density curve.
- writeCurve(String, Estimator, Estimator, double, double, double, int) - 类中的静态方法 weka.estimators.EstimatorUtils
-
Output of an n points of a density curve.
- writeDefaultListModel(Element, Object, String) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
adds the given DefaultListModel to a DOM structure.
- writeDimension(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given Dimension to a DOM structure.
- writeDOT(String, String, FastVector, FastVector) - 类中的静态方法 weka.gui.graphvisualizer.DotParser
-
This method saves a graph in a file in DOT format.
- writeFont(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given Font to a DOM structure.
- writeFontUIResource(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given FontUIResource to a DOM structure.
- writeIncremental(Instance) - 类中的方法 weka.core.converters.AbstractSaver
-
Method for incremental saving.
- writeIncremental(Instance) - 类中的方法 weka.core.converters.ArffSaver
-
Saves an instances incrementally.
- writeIncremental(Instance) - 类中的方法 weka.core.converters.C45Saver
-
Saves an instances incrementally.
- writeIncremental(Instance) - 类中的方法 weka.core.converters.CSVSaver
-
Saves an instances incrementally.
- writeIncremental(Instance) - 类中的方法 weka.core.converters.DatabaseSaver
-
Saves an instances incrementally.
- writeIncremental(Instance) - 类中的方法 weka.core.converters.LibSVMSaver
-
Saves an instances incrementally.
- writeIncremental(Instance) - 接口中的方法 weka.core.converters.Saver
-
Writes to a destination in incremental mode.
- writeIncremental(Instance) - 类中的方法 weka.core.converters.SVMLightSaver
-
Saves an instances incrementally.
- writeLoader(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given Loader to a DOM structure.
- writeMap(Element, Object, String) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
adds the given Map to a DOM structure.
- writeMatrix(Element, Object, String) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
adds the given Matrix to a DOM structure.
- writeMatrixOld(Element, Object, String) - 类中的方法 weka.core.xml.XMLBasicSerialization
-
adds the given Matrix (old) to a DOM structure.
- writeMetaBean(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given MetaBean to a DOM structure.
- writeOPTICSresultsTipText() - 类中的方法 weka.clusterers.OPTICS
-
Returns the tip text for this property
- writePoint(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given Point to a DOM structure.
- writePropertyNode(Element, Object, String) - 类中的方法 weka.experiment.xml.XMLExperiment
-
adds the given PropertyNode to a DOM structure.
- writeSaver(Element, Object, String) - 类中的方法 weka.gui.beans.xml.XMLBeans
-
adds the given Saver to a DOM structure.
- writeToFile(String, Object) - 类中的静态方法 weka.core.Debug
-
Writes the given object to the specified file.
- writeToFile(String, Object, boolean) - 类中的静态方法 weka.core.Debug
-
Writes the given object to the specified file.
- writeToFile(String, String) - 类中的静态方法 weka.core.Debug
-
Writes the given message to the specified file.
- writeToFile(String, String, boolean) - 类中的静态方法 weka.core.Debug
-
Writes the given message to the specified file.
- writeToXML(Element, Object, String) - 类中的方法 weka.core.xml.XMLSerialization
-
adds the given Object to a DOM structure.
- writeXMLBIF03(String, String, FastVector, FastVector) - 类中的静态方法 weka.gui.graphvisualizer.BIFParser
-
This method writes a graph in XMLBIF ver.
X
- x - 类中的变量 weka.gui.graphvisualizer.GraphNode
-
The x and y position of the node
- X_SHAPE - 类中的静态变量 weka.gui.visualize.Plot2D
- XBaseTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- XExpressionTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- xLabelFreqTipText() - 类中的方法 weka.gui.beans.StripChart
-
GUI Tip text
- xlogx(int) - 类中的静态方法 weka.core.Utils
-
Returns c*log2(c) for a given integer value c.
- XMaxTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- XMeans - weka.clusterers中的类
-
Cluster data using the X-means algorithm.
X-Means is K-Means extended by an Improve-Structure part In this part of the algorithm the centers are attempted to be split in its region. - XMeans() - 类的构造器 weka.clusterers.XMeans
-
the default constructor.
- XMinTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- XMLBasicSerialization - weka.core.xml中的类
-
This serializer contains some read/write methods for common classes that are not beans-conform.
- XMLBasicSerialization() - 类的构造器 weka.core.xml.XMLBasicSerialization
-
initializes the serialization
- XMLBeans - weka.gui.beans.xml中的类
-
This class serializes and deserializes a KnowledgeFlow setup to and fro XML.
- XMLBeans(JComponent, BeanContextSupport) - 类的构造器 weka.gui.beans.xml.XMLBeans
-
initializes the serialization for layouts
- XMLBeans(JComponent, BeanContextSupport, int) - 类的构造器 weka.gui.beans.xml.XMLBeans
-
initializes the serialization for different types of data
- XMLClassifier - weka.classifiers.xml中的类
-
This class serializes and deserializes a Classifier instance to and fro XML.
- XMLClassifier() - 类的构造器 weka.classifiers.xml.XMLClassifier
-
initializes the serialization
- XMLDocument - weka.core.xml中的类
-
This class offers some methods for generating, reading and writing XML documents.
It can only handle UTF-8. - XMLDocument() - 类的构造器 weka.core.xml.XMLDocument
-
initializes the factory with non-validating parser.
- XMLDocument(File) - 类的构造器 weka.core.xml.XMLDocument
-
Creates a new instance of XMLDocument.
- XMLDocument(InputStream) - 类的构造器 weka.core.xml.XMLDocument
-
Creates a new instance of XMLDocument.
- XMLDocument(Reader) - 类的构造器 weka.core.xml.XMLDocument
-
Creates a new instance of XMLDocument.
- XMLDocument(String) - 类的构造器 weka.core.xml.XMLDocument
-
Creates a new instance of XMLDocument.
- XMLExperiment - weka.experiment.xml中的类
-
This class serializes and deserializes an Experiment instance to and fro XML.
It omits theoptions
from the Experiment, since these are handled by the get/set-methods. - XMLExperiment() - 类的构造器 weka.experiment.xml.XMLExperiment
-
initializes the serialization
- XMLInstances - weka.core.xml中的类
-
XML representation of the Instances class.
- XMLInstances() - 类的构造器 weka.core.xml.XMLInstances
-
the default constructor
- XMLInstances(Reader) - 类的构造器 weka.core.xml.XMLInstances
-
generates the Instances directly from the reader containing the XML data.
- XMLInstances(Instances) - 类的构造器 weka.core.xml.XMLInstances
-
generates the XML structure based on the given data
- XMLOptions - weka.core.xml中的类
-
A class for transforming options listed in XML to a regular WEKA command line string.
- XMLOptions() - 类的构造器 weka.core.xml.XMLOptions
-
Creates a new instance of XMLOptions.
- XMLOptions(File) - 类的构造器 weka.core.xml.XMLOptions
-
Creates a new instance of XMLOptions.
- XMLOptions(InputStream) - 类的构造器 weka.core.xml.XMLOptions
-
Creates a new instance of XMLOptions.
- XMLOptions(Reader) - 类的构造器 weka.core.xml.XMLOptions
-
Creates a new instance of XMLOptions.
- XMLOptions(String) - 类的构造器 weka.core.xml.XMLOptions
-
Creates a new instance of XMLOptions.
- xmlRules() - 类中的方法 weka.associations.FPGrowth
- XMLSerialization - weka.core.xml中的类
-
With this class objects can be serialized to XML instead into a binary format.
- XMLSerialization() - 类的构造器 weka.core.xml.XMLSerialization
-
initializes the serialization
- XMLSerializationMethodHandler - weka.core.xml中的类
-
This class handles relationships between display names of properties (or classes) and Methods that are associated with them.
- XMLSerializationMethodHandler(Object) - 类的构造器 weka.core.xml.XMLSerializationMethodHandler
-
initializes the method handling, executes also
clear()
, which adds initial methods automatically. - XPropertyTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- XRFFLoader - weka.core.converters中的类
-
Reads a source that is in the XML version of the ARFF format.
- XRFFLoader() - 类的构造器 weka.core.converters.XRFFLoader
- XRFFSaver - weka.core.converters中的类
-
Writes to a destination that is in the XML version of the ARFF format.
- XRFFSaver() - 类的构造器 weka.core.converters.XRFFSaver
-
Constructor
- xStats - 类中的变量 weka.experiment.PairedStats
-
The stats associated with the data in column 1
- XStepTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- XStream - weka.core.xml中的类
-
This class is a helper class for XML serialization using XStream .
- XStream() - 类的构造器 weka.core.xml.XStream
- XSTREAM - 类中的静态变量 weka.gui.beans.SerializedModelSaver
- XVALTAGS_SELECTION - 类中的静态变量 weka.attributeSelection.RaceSearch
- xySum - 类中的变量 weka.experiment.PairedStats
-
The sum of the products
Y
- y - 类中的变量 weka.gui.graphvisualizer.GraphNode
-
The x and y position of the node
- YBaseTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- YEAR - enum class 中的枚举常量 weka.core.TechnicalInformation.Field
-
The year of publication or, for an unpublished work, the year it was written.
- YExpressionTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- YMaxTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- YMinTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- YongSplitInfo - weka.classifiers.trees.m5中的类
-
Stores split information.
- YongSplitInfo(int, int, int) - 类的构造器 weka.classifiers.trees.m5.YongSplitInfo
-
Constructs an object which contains the split information
- YPropertyTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- yStats - 类中的变量 weka.experiment.PairedStats
-
The stats associated with the data in column 2
- YStepTipText() - 类中的方法 weka.classifiers.meta.GridSearch
-
Returns the tip text for this property
- yybegin(int) - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Enters a new lexical state
- yybegin(int) - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Enters a new lexical state
- yycharat(int) - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Returns the character at position pos from the matched text.
- yycharat(int) - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Returns the character at position pos from the matched text.
- yyclose() - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Closes the input stream.
- yyclose() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Closes the input stream.
- YYEOF - 类中的静态变量 weka.core.mathematicalexpression.Scanner
-
This character denotes the end of file
- YYEOF - 类中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
This character denotes the end of file
- YYINITIAL - 类中的静态变量 weka.core.mathematicalexpression.Scanner
-
lexical states
- YYINITIAL - 类中的静态变量 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
- yylength() - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Returns the length of the matched text region.
- yylength() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Returns the length of the matched text region.
- yypushback(int) - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Pushes the specified amount of characters back into the input stream.
- yypushback(int) - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Pushes the specified amount of characters back into the input stream.
- yyreset(Reader) - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Resets the scanner to read from a new input stream.
- yyreset(Reader) - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Resets the scanner to read from a new input stream.
- yystate() - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Returns the current lexical state.
- yystate() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Returns the current lexical state.
- yytext() - 类中的方法 weka.core.mathematicalexpression.Scanner
-
Returns the text matched by the current regular expression.
- yytext() - 类中的方法 weka.filters.unsupervised.instance.subsetbyexpression.Scanner
-
Returns the text matched by the current regular expression.
Z
- ZeroR - weka.classifiers.rules中的类
-
Class for building and using a 0-R classifier.
- ZeroR() - 类的构造器 weka.classifiers.rules.ZeroR
- zipit(String, String) - 类中的方法 weka.experiment.OutputZipper
-
Saves a string to either an individual gzipped file or as an entry in a zip file.
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