Package unifeat.featureSelection
Class FitnessEvaluator
java.lang.Object
unifeat.featureSelection.FitnessEvaluator
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:
 
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Field Summary
FieldsModifier and TypeFieldDescriptionprivate ClassifierTypeprivate String[]private intprivate String[]private Objectprivate final Stringprivate double[][] - 
Constructor Summary
ConstructorsConstructorDescriptionFitnessEvaluator(String path, Object classifierName, Object selectedEvaluationClassifierPanel, int kFolds) Initializes the parameters - 
Method Summary
Modifier and TypeMethodDescriptionvoidThis method creates a directory based on the specific pathcrossValidation(int[] selectedFeature) This method performs k-fold cross validation on the reduced training set which is achieved by selected feature subset.voidThis method deletes the current directory with all files in the directoryvoidsetDataInfo(double[][] data, String[] nameFeatures, String[] classLabel) This method sets the information of the dataset. 
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Field Details
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TEMP_PATH
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trainSet
private double[][] trainSet - 
nameFeatures
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classLabel
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selectedEvaluationClassifierPanel
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classifierType
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kFolds
private int kFolds 
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Constructor Details
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FitnessEvaluator
public FitnessEvaluator(String path, Object classifierName, Object selectedEvaluationClassifierPanel, int kFolds) Initializes the parameters- Parameters:
 path- the temp path in the projectclassifierName- the name of given classifierselectedEvaluationClassifierPanel- panel of the selected classifier contained the parameter valueskFolds- the number of equal sized subsamples that is used in k-fold cross validation
 
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Method Details
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setDataInfo
This method sets the information of the dataset.- Parameters:
 data- the input dataset valuesnameFeatures- the string array of features namesclassLabel- the string array of class labels names
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crossValidation
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
 
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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 
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