Package unifeat.featureSelection

Class FitnessEvaluator

java.lang.Object

unifeat.featureSelection.FitnessEvaluator

public class FitnessEvaluator
extends Object

This java class is used to implement fitness evaluator of a solution in which k-fold cross validation on training set is used for evaluating the classification performance of a selected feature subset.

Author:

Sina Tabakhi

See Also:

• CrossValidation

Constructor Summary

Constructors

Constructor	Description
FitnessEvaluator(String path, Object classifierName, Object selectedEvaluationClassifierPanel, int kFolds)	Initializes the parameters

Method Summary

Modifier and Type	Method	Description
void	createTempDirectory()	This method creates a directory based on the specific path
Criteria	crossValidation(int[] selectedFeature)	This method performs k-fold cross validation on the reduced training set which is achieved by selected feature subset.
void	deleteTempDirectory()	This method deletes the current directory with all files in the directory
void	setDataInfo(double[][] data, String[] nameFeatures, String[] classLabel)	This method sets the information of the dataset.

Methods inherited from class java.lang.Object

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

Constructor Details

FitnessEvaluator

public FitnessEvaluator(String path,
 Object classifierName,
 Object selectedEvaluationClassifierPanel,
 int kFolds)

Initializes the parameters

Parameters:

path - the temp path in the project

classifierName - the name of given classifier

selectedEvaluationClassifierPanel - panel of the selected classifier contained the parameter values

kFolds - the number of equal sized subsamples that is used in k-fold cross validation

Method Details

setDataInfo

public void setDataInfo(double[][] data,
 String[] nameFeatures,
 String[] classLabel)

This method sets the information of the dataset.

Parameters:

data - the input dataset values

nameFeatures - the string array of features names

classLabel - the string array of class labels names

crossValidation

public Criteria crossValidation(int[] selectedFeature)

This method performs k-fold cross validation on the reduced training set which is achieved by selected feature subset.

Parameters:

selectedFeature - an array of indices of the selected feature subset

Returns:

the different criteria values

createTempDirectory

public void createTempDirectory()

This method creates a directory based on the specific path

deleteTempDirectory

public void deleteTempDirectory()

This method deletes the current directory with all files in the directory