类 AttributeSelectedClassifier
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.meta.AttributeSelectedClassifier
- 所有已实现的接口:
Serializable
,Cloneable
,AdditionalMeasureProducer
,CapabilitiesHandler
,Drawable
,OptionHandler
,RevisionHandler
,WeightedInstancesHandler
public class AttributeSelectedClassifier
extends SingleClassifierEnhancer
implements OptionHandler, Drawable, AdditionalMeasureProducer, WeightedInstancesHandler
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
Valid options are:
-E <attribute evaluator specification> Full class name of attribute evaluator, followed by its options. eg: "weka.attributeSelection.CfsSubsetEval -L" (default weka.attributeSelection.CfsSubsetEval)
-S <search method specification> Full class name of search method, followed by its options. eg: "weka.attributeSelection.BestFirst -D 1" (default weka.attributeSelection.BestFirst)
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
- 版本:
- $Revision: 1.26 $
- 作者:
- Mark Hall (mhall@cs.waikato.ac.nz)
- 另请参阅:
-
字段概要
从接口继承的字段 weka.core.Drawable
BayesNet, Newick, NOT_DRAWABLE, TREE
-
构造器概要
构造器 -
方法概要
修饰符和类型方法说明void
buildClassifier
(Instances data) Build the classifier on the dimensionally reduced data.double[]
distributionForInstance
(Instance instance) Classifies a given instance after attribute selectionReturns an enumeration of the additional measure namesReturns the tip text for this propertyReturns default capabilities of the classifier.Gets the attribute evaluator useddouble
getMeasure
(String additionalMeasureName) Returns the value of the named measureString[]
Gets the current settings of the Classifier.Returns the revision string.Gets the search method usedReturns a string describing this search methodgraph()
Returns graph describing the classifier (if possible).int
Returns the type of graph this classifier represents.Returns an enumeration describing the available options.static void
Main method for testing this class.double
Additional measure --- number of attributes selecteddouble
Additional measure --- time taken (milliseconds) to select the attributesdouble
Additional measure --- time taken (milliseconds) to select attributes and build the classifierReturns the tip text for this propertyvoid
setEvaluator
(ASEvaluation evaluator) Sets the attribute evaluatorvoid
setOptions
(String[] options) Parses a given list of options.void
Sets the search methodtoString()
Output a representation of this classifier从类继承的方法 weka.classifiers.SingleClassifierEnhancer
classifierTipText, getClassifier, setClassifier
从类继承的方法 weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
-
构造器详细资料
-
AttributeSelectedClassifier
public AttributeSelectedClassifier()Default constructor.
-
-
方法详细资料
-
globalInfo
Returns a string describing this search method- 返回:
- a description of the search method suitable for displaying in the explorer/experimenter gui
-
listOptions
Returns an enumeration describing the available options.- 指定者:
listOptions
在接口中OptionHandler
- 覆盖:
listOptions
在类中SingleClassifierEnhancer
- 返回:
- an enumeration of all the available options.
-
setOptions
Parses a given list of options. Valid options are:-E <attribute evaluator specification> Full class name of attribute evaluator, followed by its options. eg: "weka.attributeSelection.CfsSubsetEval -L" (default weka.attributeSelection.CfsSubsetEval)
-S <search method specification> Full class name of search method, followed by its options. eg: "weka.attributeSelection.BestFirst -D 1" (default weka.attributeSelection.BestFirst)
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
- 指定者:
setOptions
在接口中OptionHandler
- 覆盖:
setOptions
在类中SingleClassifierEnhancer
- 参数:
options
- the list of options as an array of strings- 抛出:
Exception
- if an option is not supported
-
getOptions
Gets the current settings of the Classifier.- 指定者:
getOptions
在接口中OptionHandler
- 覆盖:
getOptions
在类中SingleClassifierEnhancer
- 返回:
- an array of strings suitable for passing to setOptions
-
evaluatorTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
-
setEvaluator
Sets the attribute evaluator- 参数:
evaluator
- the evaluator with all options set.
-
getEvaluator
Gets the attribute evaluator used- 返回:
- the attribute evaluator
-
searchTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
-
setSearch
Sets the search method- 参数:
search
- the search method with all options set.
-
getSearch
Gets the search method used- 返回:
- the search method
-
getCapabilities
Returns default capabilities of the classifier.- 指定者:
getCapabilities
在接口中CapabilitiesHandler
- 覆盖:
getCapabilities
在类中SingleClassifierEnhancer
- 返回:
- the capabilities of this classifier
- 另请参阅:
-
buildClassifier
Build the classifier on the dimensionally reduced data.- 指定者:
buildClassifier
在类中Classifier
- 参数:
data
- the training data- 抛出:
Exception
- if the classifier could not be built successfully
-
distributionForInstance
Classifies a given instance after attribute selection- 覆盖:
distributionForInstance
在类中Classifier
- 参数:
instance
- the instance to be classified- 返回:
- the class distribution
- 抛出:
Exception
- if instance could not be classified successfully
-
graphType
public int graphType()Returns the type of graph this classifier represents. -
graph
Returns graph describing the classifier (if possible). -
toString
Output a representation of this classifier -
measureNumAttributesSelected
public double measureNumAttributesSelected()Additional measure --- number of attributes selected- 返回:
- the number of attributes selected
-
measureSelectionTime
public double measureSelectionTime()Additional measure --- time taken (milliseconds) to select the attributes- 返回:
- the time taken to select attributes
-
measureTime
public double measureTime()Additional measure --- time taken (milliseconds) to select attributes and build the classifier- 返回:
- the total time (select attributes + build classifier)
-
enumerateMeasures
Returns an enumeration of the additional measure names- 指定者:
enumerateMeasures
在接口中AdditionalMeasureProducer
- 返回:
- an enumeration of the measure names
-
getMeasure
Returns the value of the named measure- 指定者:
getMeasure
在接口中AdditionalMeasureProducer
- 参数:
additionalMeasureName
- the name of the measure to query for its value- 返回:
- the value of the named measure
- 抛出:
IllegalArgumentException
- if the named measure is not supported
-
getRevision
Returns the revision string.- 指定者:
getRevision
在接口中RevisionHandler
- 覆盖:
getRevision
在类中Classifier
- 返回:
- the revision
-
main
Main method for testing this class.- 参数:
argv
- should contain the following arguments: -t training file [-T test file] [-c class index]
-