Package unifeat.featureSelection.filter.unsupervised

Class TermVariance

java.lang.Object

unifeat.featureSelection.FeatureSelection

unifeat.featureSelection.FeatureWeighting

unifeat.featureSelection.filter.WeightedFilterApproach

unifeat.featureSelection.filter.unsupervised.TermVariance

public class TermVariance
extends WeightedFilterApproach

This java class is used to implement the term variance method.

Author:

Sina Tabakhi

See Also:

• WeightedFilterApproach
• FeatureWeighting
• FeatureSelection

Field Summary

Fields inherited from class unifeat.featureSelection.FeatureWeighting

featureValues

Fields inherited from class unifeat.featureSelection.FeatureSelection

numClass, numFeatures, numSelectedFeature, selectedFeatureSubset, trainSet

Constructor Summary

Constructors

Constructor	Description
TermVariance(int sizeSelectedFeatureSubset)	Initializes the parameters
TermVariance(Object... arguments)	Initializes the parameters

Method Summary

Modifier and Type	Method	Description
void	evaluateFeatures()	Starts the feature selection process by term variance(TV) method

Methods inherited from class unifeat.featureSelection.filter.WeightedFilterApproach

newMethod

Methods inherited from class unifeat.featureSelection.FeatureWeighting

getFeatureValues

Methods inherited from class unifeat.featureSelection.FeatureSelection

getSelectedFeatureSubset, loadDataSet, loadDataSet, setNumSelectedFeature, validate

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

TermVariance

public TermVariance(Object... arguments)

Initializes the parameters

Parameters:

arguments - array of parameter contains (sizeSelectedFeatureSubset) in which sizeSelectedFeatureSubset is the number of selected features

TermVariance

public TermVariance(int sizeSelectedFeatureSubset)

Initializes the parameters

Parameters:

sizeSelectedFeatureSubset - the number of selected features

Method Details

evaluateFeatures

public void evaluateFeatures()

Starts the feature selection process by term variance(TV) method

Specified by:

evaluateFeatures in class FeatureSelection