Package unifeat.featureSelection.filter.supervised

Class SymmetricalUncertainty

java.lang.Object

unifeat.featureSelection.FeatureSelection

unifeat.featureSelection.FeatureWeighting

unifeat.featureSelection.filter.WeightedFilterApproach

unifeat.featureSelection.filter.supervised.SymmetricalUncertainty

public class SymmetricalUncertainty
extends WeightedFilterApproach

This java class is used to implement the symmetrical uncertainty method.

Author:

Sina Tabakhi

See Also:

• WeightedFilterApproach
• FeatureWeighting
• FeatureSelection

Field Summary

Fields

Modifier and Type	Field	Description
private final double	ERROR_DENOMINATOR

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
SymmetricalUncertainty(int sizeSelectedFeatureSubset)	Initializes the parameters
SymmetricalUncertainty(Object... arguments)	Initializes the parameters

Method Summary

Modifier and Type	Method	Description
private double	computeEntropy(int indexStart, int indexEnd)	Computes the entropy of the data given by start and end indices
void	evaluateFeatures()	Starts the feature selection process by symmetrical uncertainty(SU) 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

Field Details

ERROR_DENOMINATOR

private final double ERROR_DENOMINATOR

See Also:

• Constant Field Values

Constructor Details

SymmetricalUncertainty

public SymmetricalUncertainty(Object... arguments)

Initializes the parameters

Parameters:

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

SymmetricalUncertainty

public SymmetricalUncertainty(int sizeSelectedFeatureSubset)

Initializes the parameters

Parameters:

sizeSelectedFeatureSubset - the number of selected features

Method Details

computeEntropy

private double computeEntropy(int indexStart,
 int indexEnd)

Computes the entropy of the data given by start and end indices

Parameters:

indexStart - the start index of the dataset

indexEnd - the end index of the dataset

Returns:

the entropy value

evaluateFeatures

public void evaluateFeatures()

Starts the feature selection process by symmetrical uncertainty(SU) method

Specified by:

evaluateFeatures in class FeatureSelection