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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 the XMLSerialiation 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 the XMLSerialiation 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 the ArffLoader or DataSource 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 from java.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 the ArffLoader or DataSource 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 (see sqrtm 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 offset off 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 the options 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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