Package unifeat.featureSelection.embedded.SVMBasedMethods

Class SVM_RFE

java.lang.Object

unifeat.featureSelection.FeatureSelection

unifeat.featureSelection.embedded.EmbeddedApproach

unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods

unifeat.featureSelection.embedded.SVMBasedMethods.SVM_RFE

public class SVM_RFE
extends SVMBasedMethods

This java class is used to implement support vector machine method based on recursive feature elimination (SVM_RFE).

Author:

Sina Tabakhi

See Also:

• SVMBasedMethods
• EmbeddedApproach
• FeatureSelection

Field Summary

Fields inherited from class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods

classLabelInTrainSet, kernelType, parameterC, TEMP_PATH

Fields inherited from class unifeat.featureSelection.embedded.EmbeddedApproach

classLabel, nameFeatures, PROJECT_PATH

Fields inherited from class unifeat.featureSelection.FeatureSelection

numClass, numFeatures, numSelectedFeature, selectedFeatureSubset, trainSet

Constructor Summary

Constructors

Constructor	Description
SVM_RFE(Object... arguments)	Initializes the parameters
SVM_RFE(String path, SVMKernelType kernelType, double c)	Initializes the parameters

Method Summary

Modifier and Type	Method	Description
void	evaluateFeatures()	Starts the feature selection process by support vector machine method based on recursive feature elimination (SVM_RFE)
private double[]	getFeaturesWeights(int[] selectedFeature)	Generates a classifier (SVM) using input data and based on selected feature subset, and finally returns the weights of features based on ranking criterion (weight magnitude)
String	validate()	This method returns the potential errors in the input parameters.

Methods inherited from class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods

buildSVM_OneAgainstOne, buildSVM_OneAgainstRest, createClassLabel

Methods inherited from class unifeat.featureSelection.embedded.EmbeddedApproach

loadDataSet, loadDataSet, newMethod, originalFeatureSet

Methods inherited from class unifeat.featureSelection.FeatureSelection

getSelectedFeatureSubset, setNumSelectedFeature

Methods inherited from class java.lang.Object

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

Constructor Details

SVM_RFE

public SVM_RFE(Object... arguments)

Initializes the parameters

Parameters:

arguments - array of parameters contains (path, kernelType, Parameter c) in which path is the path of the project, kernelType is the type of kernel to use, and Parameter c is the complexity parameter C

SVM_RFE

public SVM_RFE(String path,
 SVMKernelType kernelType,
 double c)

Initializes the parameters

Parameters:

path - the path of the project

kernelType - the type of kernel to use

c - the complexity parameter C

Method Details

getFeaturesWeights

private double[] getFeaturesWeights(int[] selectedFeature)

Generates a classifier (SVM) using input data and based on selected feature subset, and finally returns the weights of features based on ranking criterion (weight magnitude)

Parameters:

selectedFeature - an array of indices of the selected feature subset

Returns:

an array of the weights of features

evaluateFeatures

public void evaluateFeatures()

Starts the feature selection process by support vector machine method based on recursive feature elimination (SVM_RFE)

Specified by:

evaluateFeatures in class FeatureSelection

validate

public String validate()

This method returns the potential errors in the input parameters.

Overrides:

validate in class FeatureSelection

Returns:

a string contains the information about incorrect parameters