Index (UniFeat 0.1.1 API)

A B C D E F G H I K L M N O P R S T U V W
All Classes and Interfaces|All Packages|Serialized Form

A

AboutPanel - Class in unifeat.gui.menu: This java class is used to create and show a panel for description of the tool.
AboutPanel() - Constructor for class unifeat.gui.menu.AboutPanel: Creates new form AboutPanel.
actionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.menu.DiagramPanel: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.menu.FriedmanPanel: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.menu.PreprocessPanel: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.menu.selectMode.SelectModePanel: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.ParameterPanel: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.ProjectPath: The listener method for receiving action events.
actionPerformed(ActionEvent) - Method in class unifeat.gui.ResultPanel: The listener method for receiving action events.
addFeature(int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: This method adds a specific feature to the current selected feature subset by the ant.
ALPHA - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
ALPHA - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm
Ant - Class in unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO: This java class is used to represent an ant in optimal ant colony optimization (Optimal ACO) method.
Ant() - Constructor for class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Ant: Initializes the parameters
ArraysFunc - Class in unifeat.util: This java class is used to implement various utility methods for manipulating arrays and matrices.
ArraysFunc() - Constructor for class unifeat.util.ArraysFunc
asList() - Static method in class unifeat.classifier.ClassifierType: Returns the names of classifiers
asList() - Static method in class unifeat.featureSelection.embedded.EmbeddedType: Returns the names of embedded-based feature selection methods
asList() - Static method in class unifeat.featureSelection.filter.NonWeightedFilterType: Returns the names of filter-based feature selection methods that are not feature weighting
asList() - Static method in class unifeat.featureSelection.filter.supervised.SupervisedFilterType: Returns the names of supervised filter-based feature selection methods
asList() - Static method in class unifeat.featureSelection.filter.unsupervised.UnsupervisedFilterType: Returns the names of unsupervised filter-based feature selection methods
asList() - Static method in class unifeat.featureSelection.filter.WeightedFilterType: Returns the names of weighted filter-based feature selection methods
asList() - Static method in class unifeat.featureSelection.hybrid.HybridType: Returns the names of hybrid-based feature selection methods
asList() - Static method in class unifeat.featureSelection.wrapper.WrapperType: Returns the names of wrapper-based feature selection methods
asList() - Static method in class unifeat.gui.classifier.svmClassifier.SVMKernelType: Returns the names of kernel
asList() - Static method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.TreeType: Returns the names of different tree
asList() - Static method in class unifeat.gui.featureSelection.filter.rsm.MultivariateMethodType: Returns the names of multivariate method
asList() - Static method in class unifeat.gui.featureSelection.wrapper.GABased.CrossOverType: Returns the names of different crossover
asList() - Static method in class unifeat.gui.featureSelection.wrapper.GABased.MutationType: Returns the names of different mutation
asList() - Static method in class unifeat.gui.featureSelection.wrapper.GABased.ReplacementType: Returns the names of different replacement
asList() - Static method in class unifeat.gui.featureSelection.wrapper.GABased.SelectionType: Returns the names of different selection
asList() - Static method in class unifeat.gui.menu.selectMode.SelectModeType: Returns the names of select mode
asList() - Static method in class unifeat.result.ResultType: Returns the names of result
AVERAGE - Static variable in class unifeat.gui.menu.selectMode.SelectModeType

B

BasicACO<ColonyType> - Class in unifeat.featureSelection.wrapper.ACOBasedMethods: The abstract class contains the main methods and fields that are used in all ACO-based feature selection methods.
BasicACO(Object...) - Constructor for class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicACO: Initializes the parameters
BasicACOPanel - Class in unifeat.gui.featureSelection.wrapper.ACOBased: This java class is used to create and show a panel for the parameter settings of the basic ant colony optimization (BasicACO) method.
BasicACOPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: Creates new form BasicACOPanel.
BasicAnt - Class in unifeat.featureSelection.wrapper.ACOBasedMethods: The abstract class contains the main methods and fields that are used in all ACO-based feature selection methods.
BasicAnt() - Constructor for class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: Initializes the parameters
BasicColony<AntType> - Class in unifeat.featureSelection.wrapper.ACOBasedMethods: The abstract class contains the main methods and fields that are used in all ACO-based feature selection methods.
BasicColony(Class<AntType>) - Constructor for class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: Initializes the parameters
BasicGA<PopulationType> - Class in unifeat.featureSelection.wrapper.GABasedMethods: The abstract class contains the main methods and fields that are used in all GA-based feature selection methods.
BasicGA(Object...) - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.BasicGA: Initializes the parameters
BasicGAPanel - Class in unifeat.gui.featureSelection.wrapper.GABased: This java class is used to create and show a panel for the parameter settings of the basic genetic algorithm (BasicGA) method.
BasicGAPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: Creates new form BasicGAPanel.
BasicGraphRepresentation - Class in unifeat.featureSelection.wrapper.ACOBasedMethods: The abstract class contains the main methods and fields that are used to represent discrete search space as a graph in ACO algorithm.
BasicGraphRepresentation(int, int) - Constructor for class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicGraphRepresentation: Initializes the parameters
BasicIndividual<GeneType> - Class in unifeat.featureSelection.wrapper.GABasedMethods: The abstract class contains the main methods and fields that are used in all GA-based feature selection methods.
BasicIndividual(Class<GeneType>, Integer) - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.BasicIndividual: Initializes the parameters
BasicParticle<PosType,VelType> - Class in unifeat.featureSelection.wrapper.PSOBasedMethods: The abstract class contains the main methods and fields that are used in all PSO-based feature selection methods.
BasicParticle(Class<PosType>, Class<VelType>, Integer) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle: Initializes the parameters
BasicPopulation<IndividualType> - Class in unifeat.featureSelection.wrapper.GABasedMethods: The abstract class contains the main methods and fields that are used in all GA-based feature selection methods.
BasicPopulation(Class<IndividualType>) - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: Initializes the parameters
BasicPSO<SwarmType> - Class in unifeat.featureSelection.wrapper.PSOBasedMethods: The abstract class contains the main methods and fields that are used in all PSO-based feature selection methods.
BasicPSO(Object...) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicPSO: Initializes the parameters
BasicPSOPanel - Class in unifeat.gui.featureSelection.wrapper.PSOBased: This java class is used to create and show a panel for the parameter settings of the basic particle swarm optimization (BasicPSO) method.
BasicPSOPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: Creates new form BasicPSOPanel.
BasicSwarm<PosType,ParType> - Class in unifeat.featureSelection.wrapper.PSOBasedMethods: The abstract class contains the main methods and fields that are used in all PSO-based feature selection methods.
BasicSwarm(Class<PosType>, Class<ParType>) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: Initializes the parameters
BETA - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
BITWISE_MUTATION - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.MutationType
bitwiseMutation(boolean[], double) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.MutationOperator: Mutates new offsprings by changing the value of some genes in them using bitwise mutation
bitwiseMutation(Boolean[], double) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.MutationOperator: Mutates new offsprings by changing the value of some genes in them using bitwise mutation
BPSO - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO: This java class is used to implement feature selection method based on binary particle swarm optimization (BPSO) in which the type of Swarm is extended from Swarm class.
BPSO - Static variable in class unifeat.featureSelection.wrapper.WrapperType
BPSO(Object...) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.BPSO: Initializes the parameters
BPSOPanel - Class in unifeat.gui.featureSelection.wrapper.PSOBased: This java class is used to create and show a panel for the parameter settings of the binary particle swarm optimization (BPSO) method.
BPSOPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.PSOBased.BPSOPanel: Creates new form BPSOPanel.
btn_classifierType - Variable in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel
btn_classifierType - Variable in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel
btn_classifierType - Variable in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel
btn_more - Variable in class unifeat.gui.ParameterPanel
btn_moreActionPerformed(ActionEvent) - Method in class unifeat.gui.ParameterPanel: This method sets an action for the btn_more button.
btn_ok - Variable in class unifeat.gui.ParameterPanel
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.classifier.DTClassifierPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.classifier.KNNClassifierPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.LaplacianScorePanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.RRFSPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.CPSOPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.PSO42Panel: This method sets an action for the btn_ok button.
btn_okActionPerformed(ActionEvent) - Method in class unifeat.gui.ParameterPanel: This method sets an action for the btn_ok button.
buildClassifier(Instances) - Method in class unifeat.featureSelection.embedded.TreeBasedMethods.DecisionTreeBasedMethod: Generates a classifier using input data
buildClassifier(Instances) - Method in class unifeat.featureSelection.embedded.TreeBasedMethods.RandomForestMethod: Generates a classifier using input data
buildClassifier(Instances) - Method in class unifeat.featureSelection.embedded.TreeBasedMethods.TreeBasedMethods: Generates a classifier using input data
buildSVM_KFoldCrossValidation(int[]) - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.MSVM_RFE: Generates binary classifiers (SVM by applying k-fold cross validation resampling strategy) using input data and based on selected feature subset.
buildSVM_OneAgainstOne(int[]) - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods: Generates binary classifiers (SVM) using input data and based on selected feature subset, and finally returns the weights of features.
buildSVM_OneAgainstRest(int[]) - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods: Generates binary classifiers (SVM) using input data and based on selected feature subset, and finally returns the weights of features.

C

C1 - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
C2 - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
C45 - Static variable in class unifeat.gui.featureSelection.embedded.decisionTreeBased.TreeType
changeDefaultValue(int, int, double, double, double, double, double, double, double, int) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: Replaces the default values of basic PSO parameters with user values
changeDefaultValue(int, int, double, double, double, int) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: Replaces the default values of basic ACO parameters with user values
changeDefaultValue(SelectionType, CrossOverType, MutationType, ReplacementType, int, int, double, double, int) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: Replaces the default values of basic GA parameters with user values
ClassifierType - Class in unifeat.classifier: This java class is used to define the names of classifiers.
classLabel - Variable in class unifeat.featureSelection.embedded.EmbeddedApproach
classLabel - Variable in class unifeat.featureSelection.wrapper.WrapperApproach
classLabelInTrainSet - Variable in class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods
colony - Variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicACO
colony - Variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
Colony - Class in unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO: This java class is used to implement a colony of ants in optimal ant colony optimization (Optimal ACO) method in which the type of ant is extended from Ant class.
Colony(double) - Constructor for class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: Initializes the parameters
COLONY_SIZE - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
commonAsList() - Static method in class unifeat.gui.featureSelection.wrapper.GABased.CrossOverType: Returns the common names of different crossover
commonAsList() - Static method in class unifeat.gui.featureSelection.wrapper.GABased.MutationType: Returns the common names of different mutation
commonAsList() - Static method in class unifeat.gui.featureSelection.wrapper.GABased.ReplacementType: Returns the common names of different replacement
commonAsList() - Static method in class unifeat.gui.featureSelection.wrapper.GABased.SelectionType: Returns the common names of different selection
computeAverageArray(double[][]) - Static method in class unifeat.util.MathFunc: Calculates the average values of all columns
computeAverageValues() - Method in class unifeat.result.performanceMeasure.PerformanceMeasures: Computes the average values of all criteria over number of runs
computeAverageValuesOfPerformanceMeasures() - Method in class unifeat.result.Results: Computes the average values of all criteria over number of runs
computeErrorRate(double[][]) - Static method in class unifeat.util.MathFunc: Calculates the error rate values based on the array of accuracies
computeMean(double[][], int) - Static method in class unifeat.util.MathFunc: Computes the mean value of the data corresponding to a given column (column index)
computePearsonCorCoef(double[][], int, int) - Static method in class unifeat.util.MathFunc: Computes the correlation value between two features using Pearson correlation coefficient
computePerformanceMeasures(int, int) - Method in class unifeat.result.Results: Computes the performance measures based on given classifier
computeSimilarity(double[][], int, int) - Static method in class unifeat.util.MathFunc: Computes the similarity value between two features using cosine similarity
computeStandardDeviation(double[][], double, int, double) - Static method in class unifeat.util.MathFunc: Computes the standard deviation value of the data corresponding to a given column (column index) based on a specific denominator value
computeVariance(double[][], double, int) - Static method in class unifeat.util.MathFunc: Computes the variance value of the data corresponding to a given column (column index)
computeVariance(double[][], double, int, double) - Static method in class unifeat.util.MathFunc: Computes the variance value of the data corresponding to a given column (column index) based on a specific denominator value
constructSolution() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: This method constructs solutions completely of each ant in the colony by applying state transition rule repeatedly.
constructSolution() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: This method constructs solutions completely of each ant in the colony by applying state transition rule repeatedly.
convertArrayListToInt(ArrayList<Integer>) - Static method in class unifeat.util.ArraysFunc: Converts the ArrayList type to an array of integer values
convertCSVtoARFF(String, String, String, int, int, String[], int, String[]) - Static method in class unifeat.util.FileFunc: This method converts CSV file to ARFF file for the Weka Software
convertCSVtoARFF(String, String, String, int, DatasetInfo) - Static method in class unifeat.util.FileFunc: This method converts CSV file to ARFF file for the Weka Software
convertStringToDouble(String[][]) - Static method in class unifeat.util.ArraysFunc: Converts the string input to double values
copyDoubleArray2D(double[][]) - Static method in class unifeat.util.ArraysFunc: Creates a copy of the two dimensional array
copyDoubleArray2D(double[][], int, int) - Static method in class unifeat.util.ArraysFunc: Creates a copy of the two dimensional array by using the indices of rows
CPSO - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO: This java class is used to implement feature selection method based on continuous particle swarm optimization (CPSO) in which the type of Swarm is extended from Swarm class.
CPSO - Static variable in class unifeat.featureSelection.wrapper.WrapperType
CPSO(Object...) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.CPSO: Initializes the parameters
CPSOPanel - Class in unifeat.gui.featureSelection.wrapper.PSOBased: This java class is used to create and show a panel for the parameter settings of the continuous particle swarm optimization (CPSO) method.
CPSOPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.PSOBased.CPSOPanel: Creates new form CPSOPanel.
createAndShow() - Method in class unifeat.gui.MainPanel: This method create and show the main panel of the project
createClassLabel() - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods: Creates an array of class labels available in the train set
createCSVFile(double[][], int[], String, String[], String[]) - Static method in class unifeat.util.FileFunc: This method creates a CSV (Comma delimited) file of the input data
createDirectory(String) - Static method in class unifeat.util.FileFunc: This method creates a new directory denoted by pathname
createFeatNames(int[]) - Method in class unifeat.dataset.DatasetInfo: This method creates a string of the names of features in the selected feature array
createFeatureFiles() - Method in class unifeat.result.Results: This method creates a text file of the subsets of selected features
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicACO: This method creates the selected feature subset based on the best ant in the colony.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.OptimalACO: This method creates the selected feature subset based on the best ant in the colony.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicGA: This method creates the selected feature subset based on the fittest individual in the population.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.HGAFS: This method creates the selected feature subset based on the fittest individual in the population.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.SimpleGA: This method creates the selected feature subset based on the fittest individual in the population.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicPSO: This method creates the selected feature subset based on global best position in the swarm.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.BPSO: This method creates the selected feature subset based on global best position in the swarm.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.CPSO: This method creates the selected feature subset based on global best position in the swarm.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.HPSO_LS: This method creates the selected feature subset based on global best position in the swarm.
createSelectedFeatureSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.PSO42: This method creates the selected feature subset based on global best position in the swarm.
createTempDirectory() - Method in class unifeat.featureSelection.FitnessEvaluator: This method creates a directory based on the specific path
Criteria - Class in unifeat.result.performanceMeasure: This java class is used to set different criteria values used in the feature selection area of research.
Criteria() - Constructor for class unifeat.result.performanceMeasure.Criteria: Initializes the parameters
CriticalValue - Class in unifeat.util: This java class is used to display various critical values of the table.
CriticalValue() - Constructor for class unifeat.util.CriticalValue
CROSS_OVER_RATE - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
CROSSOVER_TYPE - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
CrossoverOperator - Class in unifeat.featureSelection.wrapper.GABasedMethods: This java class is used to implement various crossover operators for recombining the two parents to generate new offsprings
CrossoverOperator() - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator
CrossOverType - Class in unifeat.gui.featureSelection.wrapper.GABased: This java class is used to define the names of different implementation of crossover.
crossValidation(int[]) - Method in class unifeat.featureSelection.FitnessEvaluator: This method performs k-fold cross validation on the reduced training set which is achieved by selected feature subset.
CrossValidation - Class in unifeat.classifier.evaluation.wekaClassifier: This java class is used to apply the classifiers for computing the performance of the feature selection methods.
CrossValidation() - Constructor for class unifeat.classifier.evaluation.wekaClassifier.CrossValidation

D

DATASET_INFORMATION - Static variable in class unifeat.result.ResultType
DatasetInfo - Class in unifeat.dataset: This java class is used to keep the input data, split input data to test/train sets and crate CSV file format.
DatasetInfo() - Constructor for class unifeat.dataset.DatasetInfo
DECISION_TREE_BASED - Static variable in class unifeat.featureSelection.embedded.EmbeddedType
DecisionTreeBasedMethod - Class in unifeat.featureSelection.embedded.TreeBasedMethods: This java class is used to implement the decision tree based methods.
DecisionTreeBasedMethod(Object...) - Constructor for class unifeat.featureSelection.embedded.TreeBasedMethods.DecisionTreeBasedMethod: Initializes the parameters
DecisionTreeBasedMethod(String, double, int) - Constructor for class unifeat.featureSelection.embedded.TreeBasedMethods.DecisionTreeBasedMethod: Initializes the parameters
DecisionTreeBasedMethod(String, int, int, double, double) - Constructor for class unifeat.featureSelection.embedded.TreeBasedMethods.DecisionTreeBasedMethod: Initializes the parameters
DecisionTreeBasedPanel - Class in unifeat.gui.featureSelection.embedded.decisionTreeBased: This java class is used to create and show a panel for the parameter settings of the decision tree based method.
DecisionTreeBasedPanel() - Constructor for class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: Creates new form DecisionTreeBasedPanel.
deleteDirectoryWithAllFiles(String) - Static method in class unifeat.util.FileFunc: This method deletes the current directory with all files in the directory denoted by pathname
deleteFilesInDirectory(String) - Static method in class unifeat.util.FileFunc: This method deletes all files in the directory denoted by pathname
deleteTempDirectory() - Method in class unifeat.featureSelection.FitnessEvaluator: This method deletes the current directory with all files in the directory
DiagramPanel - Class in unifeat.gui.menu: This java class is used to create and show the 2-D diagrams of the input values
DiagramPanel(double[][], int[], String, String, String, String, String) - Constructor for class unifeat.gui.menu.DiagramPanel: Creates new form DiagramPanel.
DiagramPanel.TupleValues - Class in unifeat.gui.menu: This java class is used to create a data structure for pair (key, val) in which key and val are Point data type.
DT - Static variable in class unifeat.classifier.ClassifierType
DTClassifierPanel - Class in unifeat.gui.classifier: This java class is used to create and show a panel for the parameter settings of the decision tree classifier.
DTClassifierPanel() - Constructor for class unifeat.gui.classifier.DTClassifierPanel: Creates new form DTClassifierPanel.
dTree(String, double, int, int) - Static method in class unifeat.classifier.evaluation.wekaClassifier.CrossValidation: This method builds and evaluates the decision tree(DT) classifier.
dTree(String, String, double, int) - Static method in class unifeat.classifier.evaluation.wekaClassifier.TrainTestEvaluation: This method builds and evaluates the decision tree(DT) classifier.

E

EmbeddedApproach - Class in unifeat.featureSelection.embedded: The abstract class contains the main methods and fields that are used in all embedded-based feature selection methods.
EmbeddedApproach(String) - Constructor for class unifeat.featureSelection.embedded.EmbeddedApproach: Initializes the parameters
EmbeddedType - Class in unifeat.featureSelection.embedded: This java class is used to define the names of embedded-based feature selection methods.
emptyFeatureSubset() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: This method clears the current selected feature subset by the ant.
enablePositionValues(boolean) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: Enables the values of text box
END_POS_INTERVAL - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
EnumType - Class in unifeat.featureSelection: The abstract class contains the main methods and fields that are used in all enumerable types.
EnumType(String) - Constructor for class unifeat.featureSelection.EnumType: Initializes the parameters
EnumType(String, int) - Constructor for class unifeat.featureSelection.EnumType: Initializes the parameters
EPSILON - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population
EPSILON - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm
equalsKey(DiagramPanel.TupleValues) - Method in class unifeat.gui.menu.DiagramPanel.TupleValues: Determines whether or not two TupleValues are equal in their keys.
evaluateCurrentSolution(int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: This method evaluates the fitness of each ant in the colony by predefined fitness function.
evaluateCurrentSolution(int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: This method evaluates the fitness of each ant in the colony by predefined fitness function.
evaluateFeatures() - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.MSVM_RFE: Starts the feature selection process by multiple support vector machine method based on recursive feature elimination using k-fold cross validation resampling strategy (MSVM_RFE)
evaluateFeatures() - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.OVA_SVM_RFE: Starts the feature selection process by support vector machine method based on recursive feature elimination using One-Versus-All strategy (OVA_SVM_RFE)
evaluateFeatures() - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.OVO_SVM_RFE: Starts the feature selection process by support vector machine method based on recursive feature elimination using One-Versus-One strategy (OVO_SVM_RFE)
evaluateFeatures() - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.SVM_RFE: Starts the feature selection process by support vector machine method based on recursive feature elimination (SVM_RFE)
evaluateFeatures() - Method in class unifeat.featureSelection.embedded.TreeBasedMethods.DecisionTreeBasedMethod: Starts the feature selection process by Decision Tree based methods
evaluateFeatures() - Method in class unifeat.featureSelection.embedded.TreeBasedMethods.RandomForestMethod: Starts the feature selection process by Random Forest based method
evaluateFeatures() - Method in class unifeat.featureSelection.FeatureSelection: Starts the feature selection process by a given method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.supervised.FisherScore: Starts the feature selection process by Fisher score(FS) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.supervised.GainRatio: Starts the feature selection process by gain ratio(GR) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.supervised.GiniIndex: Starts the feature selection process by Gini index(GI) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.supervised.InformationGain: Starts the feature selection process by information gain(IG) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.supervised.LaplacianScore: Starts the feature selection process by Laplacian score(LS) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.supervised.MRMR: Starts the feature selection process by minimal redundancy maximal relevance (mRMR) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.supervised.RRFS: Starts the feature selection process by relevance-redundancy feature selection(RRFS) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.supervised.SymmetricalUncertainty: Starts the feature selection process by symmetrical uncertainty(SU) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.IRRFSACO_1: Starts the feature selection process by incremental relevance–redundancy feature selection based on ant colony optimization, version1 (IRRFSACO_1) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.IRRFSACO_2: Starts the feature selection process by incremental relevance–redundancy feature selection based on ant colony optimization, version2 (IRRFSACO_2) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.LaplacianScore: Starts the feature selection process by Laplacian score(LS) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.MGSACO: Starts the feature selection process by microarray gene selection based on ant colony optimization (MGSACO) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.MutualCorrelation: Starts the feature selection process by mutual correlation(MC) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.RRFS: Starts the feature selection process by relevance-redundancy feature selection(RRFS) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.RRFSACO_1: Starts the feature selection process by relevance–redundancy feature selection based on ant colony optimization, version1 (RRFSACO_1) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.RRFSACO_2: Starts the feature selection process by relevance–redundancy feature selection based on ant colony optimization, version2 (RRFSACO_2) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.RSM: Starts the feature selection process by random subspace method(RSM)
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.TermVariance: Starts the feature selection process by term variance(TV) method
evaluateFeatures() - Method in class unifeat.featureSelection.filter.unsupervised.UFSACO: Starts the feature selection process by unsupervised feature selection based on ant colony optimization (UFSACO) method
evaluateFeatures() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.OptimalACO: Starts the feature selection process by optimal ant colony optimization (Optimal ACO) method
evaluateFeatures() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.HGAFS: Starts the feature selection process by hybrid genetic algorithm for feature selection using local search (HGAFS)
evaluateFeatures() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.SimpleGA: Starts the feature selection process by simple genetic algorithm (Simple GA) method
evaluateFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.BPSO: Starts the feature selection process by binary particle swarm optimization (BPSO) method
evaluateFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.CPSO: Starts the feature selection process by continuous particle swarm optimization (CPSO) method
evaluateFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.HPSO_LS: Starts the feature selection process by hybrid particle swarm optimization method using local search (HPSO-LS)
evaluateFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.PSO42: Starts the feature selection process by particle swarm optimization version 4-2(PSO(4-2)) method
evaluateFitness() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: This method evaluates the fitness of each individual in the population by predefined fitness function.
evaluateFitness() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method evaluates the fitness of each individual in the population by predefined fitness function.
evaluateFitness() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: This method evaluates the fitness of each individual in the population by predefined fitness function.
evaluateFitness() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method evaluates the fitness of each particle in the swarm by predefined fitness function.
evaluateFitness() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Swarm: This method evaluates the fitness of each particle in the swarm by predefined fitness function.
evaluateFitness() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Swarm: This method evaluates the fitness of each particle in the swarm by predefined fitness function.
evaluateFitness() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: This method evaluates the fitness of each particle in the swarm by predefined fitness function.
evaluateFitness() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Swarm: This method evaluates the fitness of each particle in the swarm by predefined fitness function.

F

FDistributionValue(int, int, double) - Static method in class unifeat.util.CriticalValue: This method return the critical value of the table according to the df1 and df2 degrees of freedom for the significant level sigValues.
FEATURE_VALUES - Static variable in class unifeat.result.ResultType
FeatureSelection - Class in unifeat.featureSelection: The abstract class contains the main methods and fields that are used in all feature selection methods.
FeatureSelection() - Constructor for class unifeat.featureSelection.FeatureSelection: Initializes the parameters
featureSubset - Variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt
featureValues - Variable in class unifeat.featureSelection.FeatureWeighting
FeatureWeighting - Class in unifeat.featureSelection: The abstract class contains the main methods and fields that are used in all feature weighting methods.
FeatureWeighting() - Constructor for class unifeat.featureSelection.FeatureWeighting: Initializes the parameters
FileFunc - Class in unifeat.util: This java class is used to implement various utility methods for manipulating files and directories.
FileFunc() - Constructor for class unifeat.util.FileFunc
fillPheromoneArray(double) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicGraphRepresentation: This method fills all entries of the pheromone array with a specific input value.
FilterApproach - Class in unifeat.featureSelection.filter: The abstract class contains the main methods and fields that are used in all filter-based feature selection methods.
FilterApproach(int) - Constructor for class unifeat.featureSelection.filter.FilterApproach: Initializes the parameters
FilterType - Class in unifeat.featureSelection.filter: This java class is used to define the names of filter-based feature selection methods.
FilterType(String) - Constructor for class unifeat.featureSelection.filter.FilterType: Creates new FilterType.
findMinimumIndex(double[]) - Static method in class unifeat.util.MathFunc: Finds the minimum value of the input array and returns its index
findMinimumValue(double[]) - Static method in class unifeat.util.MathFunc: Finds the minimum value of the input array
FISHER_SCORE - Static variable in class unifeat.featureSelection.filter.FilterType
FisherScore - Class in unifeat.featureSelection.filter.supervised: This java class is used to implement the Fisher score method.
FisherScore(int) - Constructor for class unifeat.featureSelection.filter.supervised.FisherScore: Initializes the parameters
FisherScore(Object...) - Constructor for class unifeat.featureSelection.filter.supervised.FisherScore: Initializes the parameters
FITNESS_PROPORTIONAL_SELECTION - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.SelectionType
fitnessEvaluator - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
fitnessEvaluator - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
fitnessEvaluator - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
FitnessEvaluator - Class in unifeat.featureSelection: 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.
FitnessEvaluator(String, Object, Object, int) - Constructor for class unifeat.featureSelection.FitnessEvaluator: Initializes the parameters
fitnessProportionalSelection(double[], int) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.SelectionOperator: Selects parents from the individuals of a population according to their fitness values using fitness proportional selection method in which roulette wheel algorithm is used for selecting each individual based on their probabilities
FriedmanPanel - Class in unifeat.gui.menu: This java class is used to create and show a panel for analyzing the results based on the Friedman test.
FriedmanPanel() - Constructor for class unifeat.gui.menu.FriedmanPanel: Creates new form FriedmanPanel.

G

GAIN_RATIO - Static variable in class unifeat.featureSelection.filter.FilterType
GainRatio - Class in unifeat.featureSelection.filter.supervised: This java class is used to implement the gain ratio method.
GainRatio(int) - Constructor for class unifeat.featureSelection.filter.supervised.GainRatio: Initializes the parameters
GainRatio(Object...) - Constructor for class unifeat.featureSelection.filter.supervised.GainRatio: Initializes the parameters
gBest - Variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
generateRandNum(double, double) - Static method in class unifeat.util.MathFunc: Generates a random number that is drawn from a uniform distribution in a specific interval.
generateRandNum(double, double, Random) - Static method in class unifeat.util.MathFunc: Generates a random double number that is drawn from a uniform distribution in a specific interval.
generateRandNum(int, int, Random) - Static method in class unifeat.util.MathFunc: Generates a random integer number that is drawn from a uniform distribution in a specific interval.
genes - Variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicIndividual
get(ArrayList<DiagramPanel.TupleValues>) - Method in class unifeat.gui.menu.DiagramPanel.TupleValues: Returns the value to which the specified key is saved in the list, or null if this list contains no element for the key.
getAccuracy() - Method in class unifeat.result.performanceMeasure.Criteria: This method returns the accuracy.
getAccuracyValues() - Method in class unifeat.result.performanceMeasure.PerformanceMeasures: Returns the accuracy values of the feature selection method
getAlpha() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method returns the alpha.
getAlpha() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method returns the alpha.
getAlpha() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method returns the alpha.
getAlpha() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: This method returns the alpha value.
getAverageAccuracyValues() - Method in class unifeat.result.performanceMeasure.PerformanceMeasures: Returns the average values of the accuracy of the feature selection method over number of runs
getAverageErrorRateValues() - Method in class unifeat.result.performanceMeasure.PerformanceMeasures: Returns the average values of the error rate of the feature selection method over number of runs
getAverageTimeValues() - Method in class unifeat.result.performanceMeasure.PerformanceMeasures: Returns the average values of the execution time of the feature selection method over number of runs
getBestAnt() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: This method returns the best ant in the colony
getBestAnt() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: This method returns the best ant in the colony
getBeta() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method returns the beta.
getBeta() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method returns the beta.
getBeta() - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method returns the beta.
getBeta() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method returns the beta.
getBeta() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method returns the beta.
getBeta() - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method returns the beta.
getBeta() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method returns the beta value.
getC1() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the c1 value.
getC2() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the c2 value.
getClassifierType() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method returns the selected classifier type.
getClassifierType() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the selected classifier type.
getClassifierType() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the selected classifier type.
getClassLabel() - Method in class unifeat.dataset.DatasetInfo: This is used to return the names of class labels
getColonySize() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: This method returns the size of the colony.
getColonySize() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method returns the size of colony value.
getConfidence() - Method in class unifeat.gui.classifier.DTClassifierPanel: This method returns the confidence factor value.
getConfidence() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the confidence factor value.
getConstParam() - Method in class unifeat.gui.featureSelection.filter.LaplacianScorePanel: This method returns the const parameter value.
getCountSteps() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Ant: This method returns the current count steps of the ant.
getCrossoverRate() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the crossover rate value.
getCrossOverType() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the selected crossover type.
getElimination() - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method returns the elimination threshold value.
getEndPosInterval() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the position interval end value.
getEpsilon() - Method in class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: This method returns the epsilon value.
getEpsilon() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: This method returns the epsilon value.
getErrorRate() - Method in class unifeat.result.performanceMeasure.Criteria: This method returns the error rate.
getErrorRateValues() - Method in class unifeat.result.performanceMeasure.PerformanceMeasures: Returns the error rate values of the feature selection method
getEvRate() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method returns the evaporation rate.
getEvRate() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method returns the evaporation rate.
getEvRate() - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method returns the evaporation rate.
getEvRate() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method returns the evaporation rate.
getEvRate() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method returns the evaporation rate.
getEvRate() - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method returns the evaporation rate.
getEvRate() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method returns the evaporation rate.
getFeasibleFeatureSet() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: This method returns the feasible features that can be added to the current solution of the ant.
getFeasibleFeatureSet() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Ant: This method returns the feasible features that can be added to the current solution of the ant.
getFeatureSubset() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: This method returns the current selected feature subset by the ant.
getFeatureSubsetSize() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: This method returns the size of current selected feature subset by the ant.
getFeatureValues() - Method in class unifeat.featureSelection.FeatureWeighting: This method returns the weights of features computed by the feature weighting method.
getFitness() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: This method returns the fitness value of the ant.
getFitness() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicIndividual: This method returns the fitness value of the individual.
getFitness() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: This method returns an array of fitness values of individuals in a population
getFitness() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method returns an array of fitness values of individuals in a population
getFitness() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: This method returns an array of fitness values of individuals in a population
getFitness() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle: This method returns the fitness value of the particle.
getFittestIndividual() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: This method returns the fittest individual in the population
getFittestIndividual() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method returns the fittest individual in the population
getFittestIndividual() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: This method returns the fittest individual in the population
getGBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method returns the best position in the swarm (global best)
getGBestFitness() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method returns the fitness value of best position in the swarm (global best)
getInertiaWeight() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the inertia weight (w) value.
getInitPheromone() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method returns the initial pheromone value.
getInitPheromone() - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method returns the initial pheromone value.
getInitPheromone() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method returns the initial pheromone value.
getInitPheromone() - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method returns the initial pheromone value.
getInitPheromone() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: This method returns the initial pheromone value.
getKernel() - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: This method returns the name of kernel.
getKernel() - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method returns the name of kernel.
getKey() - Method in class unifeat.gui.menu.DiagramPanel.TupleValues: Returns the key of this TupleValues in Point data type.
getKFolds() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method returns the k folds value.
getKFolds() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the k folds value.
getKFolds() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the k folds value.
getKNearest() - Method in class unifeat.gui.featureSelection.filter.LaplacianScorePanel: This method returns the k-nearest neighbor value.
getKNNValue() - Method in class unifeat.gui.classifier.KNNClassifierPanel: This method returns the number of neighbours to use.
getMaxDepth() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the maximum depth of the tree.
getMaxVelocity() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the velocity interval end value.
getMinNum() - Method in class unifeat.gui.classifier.DTClassifierPanel: This method returns the minimum number of samples per leaf.
getMinNum() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the minimum number of samples per leaf.
getMinVelocity() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the velocity interval start value.
getMoreOptionDescription() - Method in class unifeat.gui.ParameterPanel: This method returns the description of the parameters in details that is shown in more option panel.
getMu() - Method in class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: This method returns the mu value.
getMultMethodName() - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method returns the name of multivariate method.
getMutationRate() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the mutation rate value.
getMutationType() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the selected mutation type.
getNameFeatures() - Method in class unifeat.dataset.DatasetInfo: This is used to return the names of features
getNameMode() - Method in class unifeat.gui.menu.selectMode.SelectModePanel: This method returns the type of mode.
getNumAnts() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method returns the number of ants value.
getNumAnts() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method returns the number of ants value.
getNumAnts() - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method returns the number of ants value.
getNumAnts() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method returns the number of ants value.
getNumAnts() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method returns the number of ants value.
getNumAnts() - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method returns the number of ants value.
getNumClass() - Method in class unifeat.dataset.DatasetInfo: This is used to return number of classes in the dataset
getNumData() - Method in class unifeat.dataset.DatasetInfo: This is used to return number of samples in the dataset(train set + test set)
getNumFeatOfAnt() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method returns the number of features for ants.
getNumFeatOfAnt() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method returns the number of features for ants.
getNumFeatOfAnt() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method returns the number of features for ants.
getNumFeatOfAnt() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method returns the number of features for ants.
getNumFeatOfAnt() - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method returns the number of features for ants.
getNumFeature() - Method in class unifeat.dataset.DatasetInfo: This is used to return number of features in each sample
getNumFold() - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method returns the number of subsamples value.
getNumIteration() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method returns the number of iterations value.
getNumIteration() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method returns the number of iterations value.
getNumIteration() - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method returns the number of iterations value.
getNumIteration() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method returns the number of iterations value.
getNumIteration() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method returns the number of iterations value.
getNumIteration() - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method returns the number of iterations value.
getNumIteration() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method returns the number of iterations value.
getNumIteration() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the number of iterations value.
getNumIteration() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the number of iterations value.
getNumRun() - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method returns the number of runs value.
getNumSelection() - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method returns the number of selections value.
getNumTestSet() - Method in class unifeat.dataset.DatasetInfo: This is used to return number of samples in the test set
getNumTrainSet() - Method in class unifeat.dataset.DatasetInfo: This is used to return number of samples in the train set
getParameterC() - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: This method returns the complexity parameter C.
getParameterC() - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method returns the complexity parameter C.
getPBestFitness() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle: This method returns the fitness value of best position of the particle (personal best)
getPerformanceMeasures() - Method in class unifeat.result.Results: Returns the performance measures of the obtained result
getPheromone(int, int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicGraphRepresentation: This method returns a pheromone value in a specific entry of the pheromone array that is determined by indeces of the row and column
getPheromone(int, int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.GraphRepresentation: This method returns a pheromone value in a specific entry of the pheromone array that is determined by indeces of the row and column
getPhi() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: This method returns the phi value.
getPopulationSize() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the size of population value.
getPopulationSize() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the size of population value.
getQ0() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method returns the q0.
getQ0() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method returns the q0.
getQ0() - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method returns the q0.
getQ0() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method returns the q0.
getQ0() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method returns the q0.
getQ0() - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method returns the q0.
getRandomForestNumFeatures() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the number of randomly selected features.
getRandomForestNumIterations() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the number of iterations to be performed.
getRandomTreeKValue() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the number of randomly chosen attributes.
getRandomTreeMaxDepth() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the maximum depth of the tree.
getRandomTreeMinNum() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the minimum total weight of the instances in a leaf.
getRandomTreeMinVarianceProp() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the minimum proportion of the total variance (over all the data) required for split.
getReplacementType() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the selected replacement type.
getSelectedClassifierPan() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method returns the selected classifier panel value.
getSelectedClassifierPan() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the selected classifier panel value.
getSelectedClassifierPan() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the selected classifier panel value.
getSelectedFeatureSubset() - Method in class unifeat.featureSelection.FeatureSelection: This method returns the subset of selected features by a given feature selection method.
getSelectionType() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method returns the selected selection type.
getSimilarity() - Method in class unifeat.gui.featureSelection.filter.RRFSPanel: This method returns the similarity threshold value.
getSizeSubspace() - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method returns the size of subspace value.
getStartPosInterval() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method returns the position interval start value.
getTestSet() - Method in class unifeat.dataset.DatasetInfo: This is used to return the test set values
getTheta() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.CPSOPanel: This method returns the theta value.
getTheta() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.PSO42Panel: This method returns the theta value.
getTime() - Method in class unifeat.result.performanceMeasure.Criteria: This method returns the time.
getTimeValues() - Method in class unifeat.result.performanceMeasure.PerformanceMeasures: Returns the execution time values of the feature selection method
getTrainSet() - Method in class unifeat.dataset.DatasetInfo: This is used to return the train set values
getTreeType() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method returns the type of the tree.
getVal() - Method in class unifeat.gui.menu.DiagramPanel.TupleValues: Returns the val of this TupleValues in Point data type.
getValue() - Method in class unifeat.featureSelection.EnumType: Returns value of the object
GINI_INDEX - Static variable in class unifeat.featureSelection.filter.FilterType
GiniIndex - Class in unifeat.featureSelection.filter.supervised: This java class is used to implement the Gini index method.
GiniIndex(int) - Constructor for class unifeat.featureSelection.filter.supervised.GiniIndex: Initializes the parameters
GiniIndex(Object...) - Constructor for class unifeat.featureSelection.filter.supervised.GiniIndex: Initializes the parameters
graphRepresentation - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
GraphRepresentation - Class in unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO: This java class is used to represent a graph in optimal ant colony optimization (optimal ACO) method.
GraphRepresentation(int, int) - Constructor for class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.GraphRepresentation: Initializes the parameters

H

HGAFS - Class in unifeat.featureSelection.wrapper.GABasedMethods.HGAFS: This java class is used to implement feature selection method based on hybrid genetic algorithm for feature selection using local search (HGAFS) in which the type of Population is extended from Population class.
HGAFS - Static variable in class unifeat.featureSelection.wrapper.WrapperType
HGAFS(Object...) - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.HGAFS: Initializes the parameters
HGAFSPanel - Class in unifeat.gui.featureSelection.wrapper.GABased: This java class is used to create and show a panel for the parameter settings of the hybrid genetic algorithm using local search (HGAFS).
HGAFSPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: Creates new form HGAFSPanel.
HPSO_LS - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS: This java class is used to implement feature selection based on hybrid particle swarm optimization method using local search (HPSO-LS) in which the type of Swarm is extended from Swarm class.
HPSO_LS - Static variable in class unifeat.featureSelection.wrapper.WrapperType
HPSO_LS(Object...) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.HPSO_LS: Initializes the parameters
HPSO_LSPanel - Class in unifeat.gui.featureSelection.wrapper.PSOBased: This java class is used to create and show a panel for the parameter settings of the hybrid particle swarm optimization method using local search (HPSO-LS).
HPSO_LSPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: Creates new form HPSO_LSPanel.
HybridApproach - Class in unifeat.featureSelection.hybrid: The abstract class contains the main methods and fields that are used in all hybrid-based feature selection methods.
HybridApproach() - Constructor for class unifeat.featureSelection.hybrid.HybridApproach: Initializes the parameters
HybridType - Class in unifeat.featureSelection.hybrid: This java class is used to define the names of hybrid-based feature selection methods.

I

increaseCountSteps() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Ant: This method increases one step of the count steps of the ant.
Individual - Class in unifeat.featureSelection.wrapper.GABasedMethods.HGAFS: This java class is used to represent an individual in simple genetic algorithm (Simple GA) method in which the type of gene vector is boolean.
Individual - Class in unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA: This java class is used to represent an individual in simple genetic algorithm (Simple GA) method in which the type of gene vector is boolean.
Individual(int) - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Individual: Initializes the parameters
Individual(int) - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Individual: Initializes the parameters
INERTIA_WEIGHT - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
INFORMATION_GAIN - Static variable in class unifeat.featureSelection.filter.FilterType
InformationGain - Class in unifeat.featureSelection.filter.supervised: This java class is used to implement the information gain method.
InformationGain(int) - Constructor for class unifeat.featureSelection.filter.supervised.InformationGain: Initializes the parameters
InformationGain(Object...) - Constructor for class unifeat.featureSelection.filter.supervised.InformationGain: Initializes the parameters
INIT_PHEROMONE_VALUE - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
initialization() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: This method initializes the problem parameters.
initialization() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: This method initializes the problem parameters.
initialization() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: This method initializes each individual in the population.
initialization() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method initializes each individual in the population.
initialization() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: This method initializes each individual in the population.
initialization() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method initializes the position and velocity vectors of each particle in the swarm.
initialization() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Swarm: This method initializes the position and velocity vectors of each particle in the swarm.
initialization() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Swarm: This method initializes the position and velocity vectors of each particle in the swarm.
initialization() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: This method initializes the position and velocity vectors of each particle in the swarm.
initialization() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Swarm: This method initializes the position and velocity vectors of each particle in the swarm.
IRRFSACO_1 - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the incremental relevance-redundancy feature selection based on ant colony optimization, version1 (IRRFSACO_1) method.
IRRFSACO_1 - Static variable in class unifeat.featureSelection.filter.FilterType
IRRFSACO_1(int, int, int, int, double, double, double) - Constructor for class unifeat.featureSelection.filter.unsupervised.IRRFSACO_1: Initializes the parameters
IRRFSACO_1(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.IRRFSACO_1: Initializes the parameters
IRRFSACO_1Panel - Class in unifeat.gui.featureSelection.filter: This java class is used to create and show a panel for the parameter settings of the incremental relevance-redundancy feature selection based on ant colony optimization, version1 (IRRFSACO_1) method.
IRRFSACO_1Panel() - Constructor for class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: Creates new form IRRFSACO_1Panel.
IRRFSACO_2 - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the incremental relevance–redundancy feature selection based on ant colony optimization, version2 (IRRFSACO_2) method.
IRRFSACO_2 - Static variable in class unifeat.featureSelection.filter.FilterType
IRRFSACO_2(int, double, int, int, int, double, double, double, double) - Constructor for class unifeat.featureSelection.filter.unsupervised.IRRFSACO_2: Initializes the parameters
IRRFSACO_2(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.IRRFSACO_2: Initializes the parameters
IRRFSACO_2Panel - Class in unifeat.gui.featureSelection.filter: This java class is used to create and show a panel for the parameter settings of the incremental relevance–redundancy feature selection based on ant colony optimization, version2 (IRRFSACO_2) method.
IRRFSACO_2Panel() - Constructor for class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: Creates new form IRRFSACO_2Panel.
isCompatibleTrainTestSet() - Method in class unifeat.dataset.DatasetInfo: This is used to return the status of train/test sets
isCorrectClassLabel() - Method in class unifeat.dataset.DatasetInfo: This is used to return the status of the class label file
isCorrectDataset() - Method in class unifeat.dataset.DatasetInfo: This is used to return the status of the dataset
isCorrectSamplesClass() - Method in class unifeat.dataset.DatasetInfo: This is used to return the status of the samples' class
isDouble(String) - Static method in class unifeat.util.MathFunc: Checks whether the input string is an double value or not
isEmbeddedMethod(String) - Static method in class unifeat.featureSelection.embedded.EmbeddedType: Checks whether the method is embedded-based feature selection method or not
isHybridMethod(String) - Static method in class unifeat.featureSelection.hybrid.HybridType: Checks whether the method is hybrid-based feature selection method or not
isInteger(String) - Static method in class unifeat.util.MathFunc: Checks whether the input string is an integer value or not
isNonWeightedFilterMethod(String) - Static method in class unifeat.featureSelection.filter.NonWeightedFilterType: Checks whether the method is filter-based feature weighting method or not
isWeightedFilterMethod(String) - Static method in class unifeat.featureSelection.filter.WeightedFilterType: Checks whether the method is filter-based feature weighting method or not
isWrapperMethod(String) - Static method in class unifeat.featureSelection.wrapper.WrapperType: Checks whether the method is wrapper-based feature selection method or not
itemStateChanged(ItemEvent) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: The listener method for receiving item events.
itemStateChanged(ItemEvent) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: The listener method for receiving item events.
itemStateChanged(ItemEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: The listener method for receiving item events.

K

K_FOLDS - Variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicACO
K_FOLDS - Variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicGA
K_FOLDS - Variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicPSO
kernelType - Variable in class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods
keyPressed(KeyEvent) - Method in class unifeat.gui.ParameterPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.classifier.DTClassifierPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.classifier.KNNClassifierPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.LaplacianScorePanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.RRFSPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.CPSOPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.PSO42Panel: The listener method for receiving keyboard events (keystrokes).
keyReleased(KeyEvent) - Method in class unifeat.gui.ParameterPanel: The listener method for receiving keyboard events (keystrokes).
keyTyped(KeyEvent) - Method in class unifeat.gui.ParameterPanel: The listener method for receiving keyboard events (keystrokes).
kNN(String, int, int) - Static method in class unifeat.classifier.evaluation.wekaClassifier.CrossValidation: This method builds and evaluates the k-nearest neighbours(knn) classifier.
kNN(String, String, int) - Static method in class unifeat.classifier.evaluation.wekaClassifier.TrainTestEvaluation: This method builds and evaluates the k-nearest neighbours(knn) classifier.
KNN - Static variable in class unifeat.classifier.ClassifierType
KNNClassifierPanel - Class in unifeat.gui.classifier: This java class is used to create and show a panel for the parameter settings of the k-nearest neighbours classifier.
KNNClassifierPanel() - Constructor for class unifeat.gui.classifier.KNNClassifierPanel: Creates new form KNNClassifierPanel.

L

LAPLACIAN_SCORE - Static variable in class unifeat.featureSelection.filter.FilterType
LaplacianScore - Class in unifeat.featureSelection.filter.supervised: This java class is used to implement the Laplacian score method.
LaplacianScore - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the Laplacian score method.
LaplacianScore(int, double) - Constructor for class unifeat.featureSelection.filter.supervised.LaplacianScore: Initializes the parameters
LaplacianScore(int, double, int) - Constructor for class unifeat.featureSelection.filter.unsupervised.LaplacianScore: Initializes the parameters
LaplacianScore(Object...) - Constructor for class unifeat.featureSelection.filter.supervised.LaplacianScore: Initializes the parameters
LaplacianScore(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.LaplacianScore: Initializes the parameters
LaplacianScorePanel - Class in unifeat.gui.featureSelection.filter: This java class is used to create and show a panel for the parameter settings of the Laplacian score method.
LaplacianScorePanel() - Constructor for class unifeat.gui.featureSelection.filter.LaplacianScorePanel: Creates new form LaplacianScorePanel.
lbl_about - Variable in class unifeat.gui.ParameterPanel
lbl_title - Variable in class unifeat.gui.ParameterPanel
loadDataSet(double[][], int, int) - Method in class unifeat.featureSelection.embedded.EmbeddedApproach: Loads the dataset
loadDataSet(double[][], int, int) - Method in class unifeat.featureSelection.FeatureSelection: Loads the dataset
loadDataSet(double[][], int, int) - Method in class unifeat.featureSelection.wrapper.WrapperApproach: Loads the dataset
loadDataSet(DatasetInfo) - Method in class unifeat.featureSelection.embedded.EmbeddedApproach: Loads the dataset
loadDataSet(DatasetInfo) - Method in class unifeat.featureSelection.FeatureSelection: Loads the dataset
loadDataSet(DatasetInfo) - Method in class unifeat.featureSelection.wrapper.WrapperApproach: Loads the dataset
log2(double) - Static method in class unifeat.util.MathFunc: Returns the base 2 logarithm of a double value

M

main(String[]) - Static method in class unifeat.gui.ProjectPath: This method is the main method to start the tool.
MainPanel - Class in unifeat.gui: This java class is used to create and show the main panel of the project.
MainPanel(String) - Constructor for class unifeat.gui.MainPanel: Creates new form MainPanel.
MathFunc - Class in unifeat.util: This java class is used to implement various utility methods for performing basic statistical operation such as the mean and variance.
MathFunc() - Constructor for class unifeat.util.MathFunc
MAX_VELOCITY - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
MGSACO - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the microarray gene selection based on ant colony optimization (MGSACO) method.
MGSACO - Static variable in class unifeat.featureSelection.filter.FilterType
MGSACO(int, double, int, int, double, double, double) - Constructor for class unifeat.featureSelection.filter.unsupervised.MGSACO: Initializes the parameters
MGSACO(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.MGSACO: Initializes the parameters
MGSACOPanel - Class in unifeat.gui.featureSelection.filter: This java class is used to create and show a panel for the parameter settings of the microarray gene selection based on ant colony optimization (MGSACO) method.
MGSACOPanel() - Constructor for class unifeat.gui.featureSelection.filter.MGSACOPanel: Creates new form MGSACOPanel.
MIN_VELOCITY - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
MoreOpPanel - Class in unifeat.gui: This java class is used to create and show a panel for the "more option" button of the feature selection methods.
MoreOpPanel(String) - Constructor for class unifeat.gui.MoreOpPanel: Creates new form MoreOpPanel.
moreOptionDescription - Variable in class unifeat.gui.ParameterPanel
mouseClicked(MouseEvent) - Method in class unifeat.gui.menu.AboutPanel: The listener method for receiving interesting mouse events on a component.
mouseDragged(MouseEvent) - Method in class unifeat.gui.menu.DiagramPanel: The listener method for receiving mouse motion events on a component.
mouseEntered(MouseEvent) - Method in class unifeat.gui.menu.AboutPanel: The listener method for receiving interesting mouse events on a component.
mouseExited(MouseEvent) - Method in class unifeat.gui.menu.AboutPanel: The listener method for receiving interesting mouse events on a component.
mouseMoved(MouseEvent) - Method in class unifeat.gui.menu.DiagramPanel: The listener method for receiving mouse motion events on a component.
mousePressed(MouseEvent) - Method in class unifeat.gui.menu.AboutPanel: The listener method for receiving interesting mouse events on a component.
mouseReleased(MouseEvent) - Method in class unifeat.gui.menu.AboutPanel: The listener method for receiving interesting mouse events on a component.
MRMR - Class in unifeat.featureSelection.filter.supervised: This java class is used to implement the minimal redundancy maximal relevance (mRMR) method.
MRMR - Static variable in class unifeat.featureSelection.filter.FilterType
MRMR(int) - Constructor for class unifeat.featureSelection.filter.supervised.MRMR: Initializes the parameters
MRMR(Object...) - Constructor for class unifeat.featureSelection.filter.supervised.MRMR: Initializes the parameters
MSVM_RFE - Class in unifeat.featureSelection.embedded.SVMBasedMethods: This java class is used to implement MSVM_RFE method for binary classification based on SVM_RFE method (support vector machine method based on recursive feature elimination) in which multiple linear SVMs trained on subsamples of the original training data.
MSVM_RFE - Static variable in class unifeat.featureSelection.embedded.EmbeddedType
MSVM_RFE(Object...) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.MSVM_RFE: Initializes the parameters
MSVM_RFE(String, SVMKernelType, double, int, int) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.MSVM_RFE: Initializes the parameters
MSVM_RFEPanel - Class in unifeat.gui.featureSelection.embedded: This java class is used to create and show a panel for the parameter settings of the multiple support vector machine method based on recursive feature elimination (MSVM_RFE).
MSVM_RFEPanel() - Constructor for class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: Creates new form MSVM_RFEPanel.
MU - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population
MultivariateMethodType - Class in unifeat.gui.featureSelection.filter.rsm: This java class is used to define the names of multivariate method used in RSM feature selection method.
multMatrix(double[][], double[][]) - Static method in class unifeat.util.MathFunc: Computes the multiple of two matrices
MUTATION_RATE - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
MUTATION_TYPE - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
MutationOperator - Class in unifeat.featureSelection.wrapper.GABasedMethods: This java class is used to implement various mutation operators for mutating new offsprings by changing the value of some genes in them.
MutationOperator() - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.MutationOperator
MutationType - Class in unifeat.gui.featureSelection.wrapper.GABased: This java class is used to define the names of different implementation of mutation.
MUTUAL_CORRELATION - Static variable in class unifeat.featureSelection.filter.FilterType
MUTUAL_CORRELATION - Static variable in class unifeat.gui.featureSelection.filter.rsm.MultivariateMethodType
MutualCorrelation - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the mutual correlation method.
MutualCorrelation(int) - Constructor for class unifeat.featureSelection.filter.unsupervised.MutualCorrelation: Initializes the parameters
MutualCorrelation(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.MutualCorrelation: Initializes the parameters

N

naiveBayes(String, int) - Static method in class unifeat.classifier.evaluation.wekaClassifier.CrossValidation: This method builds and evaluates the naiveBayes(NB) classifier.
naiveBayes(String, String) - Static method in class unifeat.classifier.evaluation.wekaClassifier.TrainTestEvaluation: This method builds and evaluates the naiveBayes(NB) classifier.
name - Variable in class unifeat.featureSelection.EnumType
nameFeatures - Variable in class unifeat.featureSelection.embedded.EmbeddedApproach
nameFeatures - Variable in class unifeat.featureSelection.wrapper.WrapperApproach
NB - Static variable in class unifeat.classifier.ClassifierType
newMethod(EmbeddedType, Object...) - Static method in class unifeat.featureSelection.embedded.EmbeddedApproach: This method creates new object from one of the classes that has been inherited from the EmbeddedApproach class according to type of the feature selection method.
newMethod(FilterType, boolean, Object...) - Static method in class unifeat.featureSelection.filter.FilterApproach: This method creates new object from one of the classes that has been inherited from the FilterApproach class according to type of the feature selection method.
newMethod(FilterType, boolean, Object...) - Static method in class unifeat.featureSelection.filter.WeightedFilterApproach: This method creates new object from one of the classes that has been inherited from the WeightedFilterApproach class according to type of the feature selection method.
newMethod(HybridType, Object...) - Static method in class unifeat.featureSelection.hybrid.HybridApproach: This method creates new object from one of the classes that has been inherited from the HybridApproach class according to type of the feature selection method.
newMethod(WrapperType, Object...) - Static method in class unifeat.featureSelection.wrapper.WrapperApproach: This method creates new object from one of the classes that has been inherited from the WrapperApproach class according to type of the feature selection method.
NONE - Static variable in class unifeat.classifier.ClassifierType
NONE - Static variable in class unifeat.featureSelection.embedded.EmbeddedType
NONE - Static variable in class unifeat.featureSelection.filter.FilterType
NONE - Static variable in class unifeat.featureSelection.hybrid.HybridType
NONE - Static variable in class unifeat.featureSelection.wrapper.WrapperType
NONE - Static variable in class unifeat.gui.classifier.svmClassifier.SVMKernelType
NONE - Static variable in class unifeat.gui.featureSelection.embedded.decisionTreeBased.TreeType
NONE - Static variable in class unifeat.gui.featureSelection.filter.rsm.MultivariateMethodType
NONE - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.CrossOverType
NONE - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.MutationType
NONE - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.ReplacementType
NONE - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.SelectionType
NONE - Static variable in class unifeat.gui.menu.selectMode.SelectModeType
NONE - Static variable in class unifeat.result.ResultType
NonWeightedFilterType - Class in unifeat.featureSelection.filter: This java class is used to define the names of non weighted filter-based feature selection methods.
normalizeVector(double[]) - Static method in class unifeat.util.MathFunc: Normalizes values of the vector
NUM_ITERATION - Variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicACO
NUM_ITERATION - Variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicGA
NUM_ITERATION - Variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicPSO
NUM_ORIGINAL_FEATURE - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
numClass - Variable in class unifeat.featureSelection.FeatureSelection
numFeatures - Variable in class unifeat.featureSelection.FeatureSelection
numSelectedFeature - Variable in class unifeat.featureSelection.FeatureSelection
numSelectedFeatures() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicIndividual: This method returns the number of selected features by the individual based on its gene vector.
numSelectedFeatures() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Individual: This method returns the number of selected features by the individual based on its gene vector.
numSelectedFeatures() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Individual: This method returns the number of selected features by the individual based on its gene vector.
numSelectedFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle: This method returns the number of selected features by the particle based on position vector.
numSelectedFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Particle: This method returns the number of selected features by the particle based on position vector.
numSelectedFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Particle: This method returns the number of selected features by the particle based on position vector.
numSelectedFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Particle: This method returns the number of selected features by the particle based on position vector.
numSelectedFeatures() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Particle: This method returns the number of selected features by the particle based on position vector.
numSelectedFeatures(Double[]) - Static method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Particle: This method returns the number of selected features by the particle based on personal best position vector.

O

ONE_POINT_CROSS_OVER - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.CrossOverType
onePointCrossover(boolean[], boolean[]) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using one-point crossover
onePointCrossover(double[], double[]) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using one-point crossover
onePointCrossover(GeneType[], GeneType[]) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using one-point crossover
operateCrossOver() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: This method recombines (cross over) the parents to generate new offsprings.
operateCrossOver() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method recombines (cross over) the parents to generate new offsprings.
operateCrossOver() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: This method recombines (cross over) the parents to generate new offsprings.
operateGenerationReplacement() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: This method handles populations from one generation to the next generation.
operateGenerationReplacement() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method handles populations from one generation to the next generation.
operateGenerationReplacement() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: This method handles populations from one generation to the next generation.
operateLocalSearch() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method performs a local search strategy on each individual which is based on correlation of features.
operateLocalSearch() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: This method performs a local search strategy on each particle which is based on correlation of features.
operateMutation() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: This method mutates new offsprings by changing the value of some genes in them.
operateMutation() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method mutates new offsprings by changing the value of some genes in them.
operateMutation() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: This method mutates new offsprings by changing the value of some genes in them.
operatePheromoneUpdateRule() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: This method updates the current pheromone values by decreasing pheromone concentrations and then deposit the quantity of pheromone by ants.
operatePheromoneUpdateRule() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: This method updates the current pheromone values by decreasing pheromone concentrations and then deposit the quantity of pheromone by ants.
operateSelection() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation: This method selects parents from the individuals of a population according to their fitness that will recombine for next generation.
operateSelection() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method selects parents from the individuals of a population according to their fitness that will recombine for next generation.
operateSelection() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: This method selects parents from the individuals of a population according to their fitness that will recombine for next generation.
operateStateTransitionRule(int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: This method selects the next state and adds it to the current selected feature subset by using state transition rule that is combination of heuristic desirability and pheromone levels.
operateStateTransitionRule(int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: This method selects the next state and adds it to the current selected feature subset by using state transition rule that is combination of heuristic desirability and pheromone levels.
OPTIMAL_ACO - Static variable in class unifeat.featureSelection.wrapper.WrapperType
OptimalACO - Class in unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO: This java class is used to implement feature selection method based on optimal ant colony optimization (Optimal ACO) in which the type of Colony is extended from Colony class.
OptimalACO(Object...) - Constructor for class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.OptimalACO: Initializes the parameters
OptimalACOPanel - Class in unifeat.gui.featureSelection.wrapper.ACOBased: This java class is used to create and show a panel for the parameter settings of the optimal ant colony optimization (OptimalACO) method.
OptimalACOPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: Creates new form OptimalACOPanel.
originalFeatureSet() - Method in class unifeat.featureSelection.embedded.EmbeddedApproach: This method creates an array of indices of features and returns it.
originalFeatureSet() - Method in class unifeat.featureSelection.wrapper.WrapperApproach: This method creates an array of indices of features and returns it.
OVA_SVM_RFE - Class in unifeat.featureSelection.embedded.SVMBasedMethods: This java class is used to implement OVA_SVM_RFE method for multiclass classification based on SVM_RFE method (support vector machine method based on recursive feature elimination) in which One-Versus-All (OVA) strategy is applied to construct binary classifiers.
OVA_SVM_RFE - Static variable in class unifeat.featureSelection.embedded.EmbeddedType
OVA_SVM_RFE(Object...) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.OVA_SVM_RFE: Initializes the parameters
OVA_SVM_RFE(String, SVMKernelType, double) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.OVA_SVM_RFE: Initializes the parameters
OVO_SVM_RFE - Class in unifeat.featureSelection.embedded.SVMBasedMethods: This java class is used to implement OVO_SVM_RFE method for multiclass classification based on SVM_RFE method (support vector machine method based on recursive feature elimination) in which One-Versus-One (OVO) strategy is applied to construct binary classifiers.
OVO_SVM_RFE - Static variable in class unifeat.featureSelection.embedded.EmbeddedType
OVO_SVM_RFE(Object...) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.OVO_SVM_RFE: Initializes the parameters
OVO_SVM_RFE(String, SVMKernelType, double) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.OVO_SVM_RFE: Initializes the parameters

P

paint(Graphics) - Method in class unifeat.gui.MainPanel: Recreates MainPanel based on the updated progress bar value.
paintComponent(Graphics) - Method in class unifeat.gui.menu.DiagramPanel: This method is used to show the diagram.
panel_about - Variable in class unifeat.gui.ParameterPanel
parameterC - Variable in class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods
ParameterPanel - Class in unifeat.gui: The abstract class contains the main methods and fields that are used to create and show a panel for the parameter settings.
ParameterPanel() - Constructor for class unifeat.gui.ParameterPanel: Creates new form ParameterPanel.
ParameterPanel(String, String, String, String, Rectangle, Rectangle, Rectangle, Rectangle, Dimension) - Constructor for class unifeat.gui.ParameterPanel: Creates new form ParameterPanel.
parse(String) - Static method in class unifeat.classifier.ClassifierType: Converts the classifier name to ClassifierType
parse(String) - Static method in class unifeat.featureSelection.embedded.EmbeddedType: Converts the embedded method name to EmbeddedType
parse(String) - Static method in class unifeat.featureSelection.filter.FilterType: Converts the filter method name to FilterType
parse(String) - Static method in class unifeat.featureSelection.hybrid.HybridType: Converts the hybrid method name to HybridType
parse(String) - Static method in class unifeat.featureSelection.wrapper.WrapperType: Converts the wrapper method name to WrapperType
parse(String) - Static method in class unifeat.gui.classifier.svmClassifier.SVMKernelType: Converts the kernel name to SVMKernelType
parse(String) - Static method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.TreeType: Converts the tree name to TreeType
parse(String) - Static method in class unifeat.gui.featureSelection.filter.rsm.MultivariateMethodType: Converts the multivariate method name to MultivariateMethodType
parse(String) - Static method in class unifeat.gui.featureSelection.wrapper.GABased.CrossOverType: Converts the crossover name to CrossOverType
parse(String) - Static method in class unifeat.gui.featureSelection.wrapper.GABased.MutationType: Converts the mutation name to MutationType
parse(String) - Static method in class unifeat.gui.featureSelection.wrapper.GABased.ReplacementType: Converts the replacement name to ReplacementType
parse(String) - Static method in class unifeat.gui.featureSelection.wrapper.GABased.SelectionType: Converts the selection name to SelectionType
parse(String) - Static method in class unifeat.gui.menu.selectMode.SelectModeType: Converts the select mode name to SelectModeType
parse(String) - Static method in class unifeat.result.ResultType: Converts the result name to ResultType
parse(SVMKernelType) - Static method in class unifeat.classifier.WekaSVMKernel: This method return the weka SVM kernel type according to the unifeat SVM kernel type.
Particle - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO: This java class is used to represent a particle in binary particle swarm optimization (BPSO) method in which the type of position vector is boolean and the type of velocity vector is double.
Particle - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO: This java class is used to represent a particle in continuous particle swarm optimization (CPSO) method in which the type of position and velocity vectors are double.
Particle - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS: This java class is used to represent a particle in hybrid particle swarm optimization method using local search (HPSO-LS) in which the type of position vector is boolean and the type of velocity vector is double.
Particle - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42: This java class is used to represent a particle in particle swarm optimization version 4-2(PSO(4-2)) method in which the type of position and velocity vectors are double.
Particle(int) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Particle: Initializes the parameters
Particle(int) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Particle: Initializes the parameters
Particle(int) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Particle: Initializes the parameters
Particle(int) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Particle: Initializes the parameters
pBest - Variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle
PEARSON_VII - Static variable in class unifeat.gui.classifier.svmClassifier.SVMKernelType
PERFORMANCE_MEASURES - Static variable in class unifeat.result.ResultType
PerformanceMeasures - Class in unifeat.result.performanceMeasure: This java class is used to save all performance measure values obtained from different runs of given feature selection method.
PerformanceMeasures(int, int) - Constructor for class unifeat.result.performanceMeasure.PerformanceMeasures: Initializes the parameters
pheromone - Variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicGraphRepresentation
PHI - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony
POLYNOMIAL - Static variable in class unifeat.gui.classifier.svmClassifier.SVMKernelType
population - Variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicGA
population - Variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
population - Variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
Population - Class in unifeat.featureSelection.wrapper.GABasedMethods.HGAFS: This java class is used to implement a population of individuals in hybrid genetic algorithm for feature selection using local search (HGAFS) in which the type of individual is extended from Individual class.
Population - Class in unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA: This java class is used to implement a population of individuals in simple genetic algorithm (Simple GA) method in which the type of individual is extended from Individual class.
Population() - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Population: Initializes the parameters
Population(double, double) - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: Initializes the parameters
POPULATION_SIZE - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
POPULATION_SIZE - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
position - Variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle
preProcessing(String, String) - Method in class unifeat.dataset.DatasetInfo: This is used to read dataset and class label files, split datasets and set their values
preProcessing(String, String, String) - Method in class unifeat.dataset.DatasetInfo: This is used to read datasets and class labels, split datasets and set their values
PreprocessPanel - Class in unifeat.gui.menu: This java class is used to create and show a panel for preprocessing of the datasets.
PreprocessPanel() - Constructor for class unifeat.gui.menu.PreprocessPanel: Creates new form PreprocessPanel.
PROBLEM_DIMENSION - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
PROBLEM_DIMENSION - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
PROJECT_PATH - Variable in class unifeat.featureSelection.embedded.EmbeddedApproach
PROJECT_PATH - Variable in class unifeat.featureSelection.wrapper.WrapperApproach
ProjectPath - Class in unifeat.gui: This java class is used to create and show a panel for the selecting path for the project.
ProjectPath() - Constructor for class unifeat.gui.ProjectPath: Creates new form ProjectPath.
PSO42 - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42: This java class is used to implement feature selection method based on particle swarm optimization version 4-2(PSO(4-2)) with new initialization strategy and updating rule in which the type of Swarm is extended from Swarm class.
PSO42 - Static variable in class unifeat.featureSelection.wrapper.WrapperType
PSO42(Object...) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.PSO42: Initializes the parameters
PSO42Panel - Class in unifeat.gui.featureSelection.wrapper.PSOBased: This java class is used to create and show a panel for the parameter settings of the particle swarm optimization version 4-2 (PSO(4-2)) method.
PSO42Panel() - Constructor for class unifeat.gui.featureSelection.wrapper.PSOBased.PSO42Panel: Creates new form PSO42Panel.

R

RANDOM_FOREST - Static variable in class unifeat.gui.featureSelection.embedded.decisionTreeBased.TreeType
RANDOM_FOREST_METHOD - Static variable in class unifeat.featureSelection.embedded.EmbeddedType
RANDOM_TREE - Static variable in class unifeat.gui.featureSelection.embedded.decisionTreeBased.TreeType
RandomForestMethod - Class in unifeat.featureSelection.embedded.TreeBasedMethods: This java class is used to implement the random forest based method for feature selection.
RandomForestMethod(Object...) - Constructor for class unifeat.featureSelection.embedded.TreeBasedMethods.RandomForestMethod: Initializes the parameters
RandomForestMethod(String, int, int, int) - Constructor for class unifeat.featureSelection.embedded.TreeBasedMethods.RandomForestMethod: Initializes the parameters
randomize(double[][]) - Static method in class unifeat.util.MathFunc: Shuffles a given array using Fisher–Yates shuffle Algorithm
randomize(T[]) - Static method in class unifeat.util.MathFunc: Shuffles a given array using Fisher–Yates shuffle Algorithm
RANK_BASED_SELECTION - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.SelectionType
rankBasedSelection(double[], int) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.SelectionOperator: Selects parents from the individuals of a population according to their fitness values using rank-based selection method in which roulette wheel algorithm is used for selecting each individual based on their ranks
RBF - Static variable in class unifeat.gui.classifier.svmClassifier.SVMKernelType
removeFeature(int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: This method removes a specific feature of the current selected feature subset by the ant.
removeTreeType(Object...) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: Removes a list of tree types from a combobox
REPLACEMENT_TYPE - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
ReplacementType - Class in unifeat.gui.featureSelection.wrapper.GABased: This java class is used to define the names of different implementation of generation replacement.
ResultPanel - Class in unifeat.gui: This java class is used to create and show a panel for showing the results.
ResultPanel(String) - Constructor for class unifeat.gui.ResultPanel: Creates new form ResultPanel.
Results - Class in unifeat.result: This java class is used to implement various methods for showing the results in the result panel.
Results(DatasetInfo, int, int, String, Object, Object, Object) - Constructor for class unifeat.result.Results: Initializes the parameters
ResultType - Class in unifeat.result: This java class is used to define the types of result.
RHO - Static variable in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony
rouletteWheel(double[]) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.SelectionOperator: Selects an individual in a population according to their probabilities using roulette wheel algorithm
roundDouble(double, int) - Static method in class unifeat.util.MathFunc: Rounds the argument value to a double value with given number of floating-point
RRFS - Class in unifeat.featureSelection.filter.supervised: This java class is used to implement the relevance-redundancy feature selection(RRFS) method.
RRFS - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the relevance-redundancy feature selection(RRFS) method.
RRFS - Static variable in class unifeat.featureSelection.filter.FilterType
RRFS(int, double) - Constructor for class unifeat.featureSelection.filter.supervised.RRFS: Initializes the parameters
RRFS(int, double) - Constructor for class unifeat.featureSelection.filter.unsupervised.RRFS: Initializes the parameters
RRFS(Object...) - Constructor for class unifeat.featureSelection.filter.supervised.RRFS: Initializes the parameters
RRFS(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.RRFS: Initializes the parameters
RRFSACO_1 - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the relevance–redundancy feature selection based on ant colony optimization, version1 (RRFSACO_1) method.
RRFSACO_1 - Static variable in class unifeat.featureSelection.filter.FilterType
RRFSACO_1(int, int, int, int, double, double, double) - Constructor for class unifeat.featureSelection.filter.unsupervised.RRFSACO_1: Initializes the parameters
RRFSACO_1(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.RRFSACO_1: Initializes the parameters
RRFSACO_1Panel - Class in unifeat.gui.featureSelection.filter: This java class is used to create and show a panel for the parameter settings of the relevance–redundancy feature selection based on ant colony optimization, version1 (RRFSACO_1) method.
RRFSACO_1Panel() - Constructor for class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: Creates new form RRFSACO_1Panel.
RRFSACO_2 - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the relevance–redundancy feature selection based on ant colony optimization, version2 (RRFSACO_2) method.
RRFSACO_2 - Static variable in class unifeat.featureSelection.filter.FilterType
RRFSACO_2(int, double, int, int, int, double, double, double, double) - Constructor for class unifeat.featureSelection.filter.unsupervised.RRFSACO_2: Initializes the parameters
RRFSACO_2(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.RRFSACO_2: Initializes the parameters
RRFSACO_2Panel - Class in unifeat.gui.featureSelection.filter: This java class is used to create and show a panel for the parameter settings of the relevance–redundancy feature selection based on ant colony optimization, version2 (RRFSACO_2) method.
RRFSACO_2Panel() - Constructor for class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: Creates new form RRFSACO_2Panel.
RRFSPanel - Class in unifeat.gui.featureSelection.filter: This java class is used to create and show a panel for the parameter settings of the relevance-redundancy feature selection(RRFS) method.
RRFSPanel() - Constructor for class unifeat.gui.featureSelection.filter.RRFSPanel: Creates new form RRFSPanel.
RSM - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the random subspace method(RSM) method.
RSM - Static variable in class unifeat.featureSelection.filter.FilterType
RSM(int, int, int, int, MultivariateMethodType) - Constructor for class unifeat.featureSelection.filter.unsupervised.RSM: Initializes the parameters
RSM(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.RSM: Initializes the parameters
RSMPanel - Class in unifeat.gui.featureSelection.filter.rsm: This java class is used to create and show a panel for the parameter settings of the random subspace method (RSM) method.
RSMPanel() - Constructor for class unifeat.gui.featureSelection.filter.rsm.RSMPanel: Creates new form RSMPanel.

S

SELECTED_FEATURE_SUBSET - Static variable in class unifeat.result.ResultType
selectedFeaturesSubset() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicIndividual: This method returns the indices of selected features by the individual based on its gene vector.
selectedFeaturesSubset() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Individual: This method returns the indices of selected features by the individual based on its gene vector.
selectedFeaturesSubset() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.Individual: This method returns the indices of selected features by the individual based on its gene vector.
selectedFeaturesSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle: This method returns the indices of selected features by the particle based on position vector.
selectedFeaturesSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Particle: This method returns the indices of selected features by the particle based on position vector.
selectedFeaturesSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Particle: This method returns the indices of selected features by the particle based on position vector.
selectedFeaturesSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Particle: This method returns the indices of selected features by the particle based on position vector.
selectedFeaturesSubset() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Particle: This method returns the indices of selected features by the particle based on position vector.
selectedFeatureSubset - Variable in class unifeat.featureSelection.FeatureSelection
selectedFeatureSubset(String) - Method in class unifeat.featureSelection.embedded.TreeBasedMethods.DecisionTreeBasedMethod: Finds the feature subset from the nodes of the created tree (Used for C4.5 and Random Tree)
selectedFeatureSubset(String) - Method in class unifeat.featureSelection.embedded.TreeBasedMethods.RandomForestMethod: Finds the feature subset from the nodes of the created tree (Used for Random Forest)
selectedFeatureSubset(String) - Method in class unifeat.featureSelection.embedded.TreeBasedMethods.TreeBasedMethods: Finds the feature subset from the nodes of the created tree
SELECTION_TYPE - Static variable in class unifeat.featureSelection.wrapper.GABasedMethods.BasicPopulation
SelectionOperator - Class in unifeat.featureSelection.wrapper.GABasedMethods: This java class is used to implement various selection operators for selecting parents from the individuals of a population according to their fitness that will recombine for next generation.
SelectionOperator() - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.SelectionOperator
SelectionType - Class in unifeat.gui.featureSelection.wrapper.GABased: This java class is used to define the names of different implementation of selection.
SelectModePanel - Class in unifeat.gui.menu.selectMode: This java class is used to create and show a panel for the selecting mode of showing the results.
SelectModePanel() - Constructor for class unifeat.gui.menu.selectMode.SelectModePanel: Creates new form SelectModePanel.
SelectModeType - Class in unifeat.gui.menu.selectMode: This java class is used to define the names of select mode used in the result
setAccuracy(double) - Method in class unifeat.result.performanceMeasure.Criteria: This method sets the accuracy value.
setAlpha(double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets the alpha value.
setAlpha(double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets the alpha value.
setAlpha(double) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets the alpha value.
setAlpha(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: This method sets the alpha value.
setBeta(double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method sets the beta value.
setBeta(double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets the beta value.
setBeta(double) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method sets the beta value.
setBeta(double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method sets the beta value.
setBeta(double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets the beta value.
setBeta(double) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method sets the beta value.
setBeta(double) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets the beta value.
setC1(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the c1 value.
setC2(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the c2 value.
setClassifierType(ClassifierType) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets the selected classifier type.
setClassifierType(ClassifierType) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the selected classifier type.
setClassifierType(ClassifierType) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the selected classifier type.
setColonySize(int) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets the size of colony value.
setConfidence(double) - Method in class unifeat.gui.classifier.DTClassifierPanel: This method sets the confidence factor value.
setConfidence(double) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the confidence factor value.
setConstParam(double) - Method in class unifeat.gui.featureSelection.filter.LaplacianScorePanel: This method sets the const parameter value.
setCountSteps(int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Ant: This method sets the count steps of the ant.
setCriteria(int, int, Criteria) - Method in class unifeat.result.performanceMeasure.PerformanceMeasures: Sets the obtained criteria values from feature selection method
setCrossoverRate(double) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the crossover rate value.
setCrossOverType(CrossOverType) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the selected crossover type.
setCurrentFeatureValues(double[]) - Method in class unifeat.result.Results: Sets the values of each feature in the current run over given subset of selected features
setCurrentSelectedSubset(int, int, int[]) - Method in class unifeat.result.Results: Sets the subset of selected features in the current run
setDataInfo(double[][]) - Method in class unifeat.featureSelection.wrapper.GABasedMethods.HGAFS.Population: This method sets the information of the dataset.
setDataInfo(double[][]) - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: This method sets the information of the dataset.
setDataInfo(double[][], String[], String[]) - Method in class unifeat.featureSelection.FitnessEvaluator: This method sets the information of the dataset.
setDefaultValue() - Method in class unifeat.gui.classifier.DTClassifierPanel: Sets the default values of the decision tree parameters
setDefaultValue() - Method in class unifeat.gui.classifier.KNNClassifierPanel: Sets the default values of the k-nearest neighbours parameters
setDefaultValue() - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: Sets the default values of the support vector machine parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: Sets the default values of the tree parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: Sets the default values of the MSVM_RFE parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: Sets the default values of the IRRFSACO_1 parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: Sets the default values of the IRRFSACO_2 parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.LaplacianScorePanel: Sets the default values of the Laplacian score parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: Sets the default values of the MGSACO parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: Sets the default values of the RRFSACO_1 parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: Sets the default values of the RRFSACO_2 parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.RRFSPanel: Sets the default values of the RRFS parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: Sets the default values of the RSM parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: Sets the default values of the UFSACO parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: Sets the default values of the basic ACO parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: Sets the default values of the Optimal ACO parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: Sets the default values of the basic GA parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: Sets the default values of the HGAFS parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: Sets the default values of the basic PSO parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.CPSOPanel: Sets the default values of the CPSO parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: Sets the default values of the HPSO_LS parameters
setDefaultValue() - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.PSO42Panel: Sets the default values of the PSO(4-2) parameters
setDefaultValue(TreeType) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: Sets the default values of the tree parameters
setElimination(int) - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method sets the elimination threshold value.
setEnabledButton() - Method in class unifeat.gui.ResultPanel: Enables the status of all buttons
setEnableKernelType(boolean) - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: Sets the status of the kernel's combo box
setEnableKernelType(boolean) - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: Sets the status of the kernel's combo box
setEndPosInterval(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the position interval end value.
setEpsilon(double) - Method in class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: This method sets the epsilon value.
setEpsilon(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: This method sets the epsilon value.
setErrorRate(double) - Method in class unifeat.result.performanceMeasure.Criteria: This method sets the error rate value.
setEvRate(double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method sets the evaporation rate value.
setEvRate(double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets the evaporation rate value.
setEvRate(double) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method sets the evaporation rate value.
setEvRate(double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method sets the evaporation rate value.
setEvRate(double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets the evaporation rate value.
setEvRate(double) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method sets the evaporation rate value.
setEvRate(double) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets the evaporation rate value.
setFitness(double) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: This method sets the fitness value of the ant.
setFitness(double) - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicIndividual: This method sets the fitness value of the individual.
setFitness(double) - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle: This method sets the fitness value of the particle.
setGBest(PosType[]) - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method sets the best position in the swarm (global best)
setGBestFitness(double) - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method sets the fitness value of best position in the swarm (global best)
setInertiaWeight(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the inertia weight (w) value.
setInitialState() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: This method places any ant randomly to one feature as their initial states.
setInitialState() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.Colony: This method places any ant randomly to one feature as their initial states.
setInitPheromone(double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets the initial pheromone value.
setInitPheromone(double) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method sets the initial pheromone value.
setInitPheromone(double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets the initial pheromone value.
setInitPheromone(double) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method sets the initial pheromone value.
setInitPheromone(double) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: This method sets the initial pheromone value.
setKernel(SVMKernelType) - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: This method sets the name of kernel.
setKernel(SVMKernelType) - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method sets the name of kernel.
setKFolds(int) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets the k folds value.
setKFolds(int) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the k folds value.
setKFolds(int) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the k folds value.
setKNearest(int) - Method in class unifeat.gui.featureSelection.filter.LaplacianScorePanel: This method sets the k-nearest neighbor value.
setKNNValue(int) - Method in class unifeat.gui.classifier.KNNClassifierPanel: This method sets the number of neighbours to use.
setMaxDepth(int) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the maximum depth of the tree.
setMaxVelocity(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the velocity interval end value.
setMessage(String) - Method in class unifeat.gui.ResultPanel: Appends the given text to the end of the documents
setMethodDescription(String) - Method in class unifeat.gui.ParameterPanel: This method sets the description of the method.
setMethodDescriptionPosition(Rectangle) - Method in class unifeat.gui.ParameterPanel: This method sets the position of the methodDescription in the created panel.
setMethodTitle(String) - Method in class unifeat.gui.ParameterPanel: This method sets the title of the method settings.
setMethodTitlePosition(Rectangle) - Method in class unifeat.gui.ParameterPanel: This method sets the position of the methodTitle in the created panel.
setMinNum(int) - Method in class unifeat.gui.classifier.DTClassifierPanel: This method sets the minimum number of samples per leaf value.
setMinNum(int) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the minimum number of samples per leaf value.
setMinVelocity(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the velocity interval start value.
setMoreButtonPosition(Rectangle) - Method in class unifeat.gui.ParameterPanel: This method sets the position of the More button in the created panel.
setMoreOptionDescription(String) - Method in class unifeat.gui.ParameterPanel: This method sets the description of the parameters in details that is shown in more option panel.
setMu(double) - Method in class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: This method sets the mu value.
setMultMethodName(MultivariateMethodType) - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method sets the name of multivariate method.
setMutationRate(double) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the mutation rate value.
setMutationType(MutationType) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the selected mutation type.
setNameMode(SelectModeType) - Method in class unifeat.gui.menu.selectMode.SelectModePanel: This method sets the type of mode.
setNumAnts(int) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method sets the number of ants value.
setNumAnts(int) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets the number of ants value.
setNumAnts(int) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method sets the number of ants value.
setNumAnts(int) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method sets the number of ants value.
setNumAnts(int) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets the number of ants value.
setNumAnts(int) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method sets the number of ants value.
setNumFeatOfAnt(int) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method sets the the number of features for ants value.
setNumFeatOfAnt(int) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets the the number of features for ants value.
setNumFeatOfAnt(int) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method sets the the number of features for ants value.
setNumFeatOfAnt(int) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets the the number of features for ants value.
setNumFeatOfAnt(int) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method sets the the number of features for ants value.
setNumFold(int) - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method sets the number of subsamples value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method sets the number of iterations value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets the number of iterations value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method sets the number of iterations value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method sets the number of iterations value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets the number of iterations value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method sets the number of iterations value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets the number of iterations value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the number of iterations value.
setNumIteration(int) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the number of iterations value.
setNumRun(int) - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method sets the number of runs value.
setNumSelectedFeature(int) - Method in class unifeat.featureSelection.FeatureSelection: This method sets the number of features that should be selected by a given feature selection method.
setNumSelection(int) - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method sets the number of selections value.
setOkButtonPosition(Rectangle) - Method in class unifeat.gui.ParameterPanel: This method sets the position of the Ok button in the created panel.
setPanelSize(Dimension) - Method in class unifeat.gui.ParameterPanel: This method sets the size of the created panel.
setPanelTitle(String) - Method in class unifeat.gui.ParameterPanel: This method sets the title of the panel.
setParameterC(double) - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: This method sets the complexity parameter C.
setParameterC(double) - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: This method sets the complexity parameter C.
setPBestFitness(double) - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle: This method sets the fitness value of best position of the particle (personal best)
setPheromone(double, int, int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicGraphRepresentation: This method sets a pheromone value in a specific entry of the array.
setPheromone(double, int, int) - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.GraphRepresentation: This method sets a pheromone value in a specific entry of the array.
setPhi(double) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: This method sets the phi value.
setPopulationSize(int) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the size of population value.
setPopulationSize(int) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the size of population value.
setQ0(double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: This method sets the q0 value.
setQ0(double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: This method sets the q0 value.
setQ0(double) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: This method sets the q0 value.
setQ0(double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: This method sets the q0 value.
setQ0(double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: This method sets the q0 value.
setQ0(double) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: This method sets the q0 value.
setRandomForestNumFeatures(int) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the number of randomly selected features.
setRandomForestNumIterations(int) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the number of iterations to be performed.
setRandomTreeKValue(int) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the number of randomly chosen attributes.
setRandomTreeMaxDepth(int) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the maximum depth of the tree.
setRandomTreeMinNum(double) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the minimum total weight of the instances in a leaf.
setRandomTreeMinVarianceProp(double) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: This method sets the minimum proportion of the total variance (over all the data) required for split.
setReplacementType(ReplacementType) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the selected replacement type.
setSelectedClassifierPan(Object) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: This method sets the selected classifier panel value.
setSelectedClassifierPan(Object) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the selected classifier panel value.
setSelectedClassifierPan(Object) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the selected classifier panel value.
setSelectionType(SelectionType) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: This method sets the selected selection type.
setSimilarity(double) - Method in class unifeat.gui.featureSelection.filter.RRFSPanel: This method sets the similarity threshold value.
setSizeSubspace(int) - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: This method sets the size of subspace value.
setStartPosInterval(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: This method sets the position interval start value.
setTheta(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.CPSOPanel: This method sets the theta value.
setTheta(double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.PSO42Panel: This method sets the theta value.
setTime(double) - Method in class unifeat.result.performanceMeasure.Criteria: This method sets the time value.
setTime(double) - Method in class unifeat.result.Results: Sets the execution time of the feature selection method in the current run.
setUserValue(double) - Method in class unifeat.gui.featureSelection.filter.RRFSPanel: Sets the last values of the RRFS parameters entered by user
setUserValue(double, int) - Method in class unifeat.gui.classifier.DTClassifierPanel: Sets the last values of the decision tree parameters entered by user
setUserValue(double, int) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: Sets the last values of the C4.5 parameters entered by user
setUserValue(double, int, int, double, double, double) - Method in class unifeat.gui.featureSelection.filter.MGSACOPanel: Sets the last values of the MGSACO parameters entered by user
setUserValue(double, int, int, int, double, double, double) - Method in class unifeat.gui.featureSelection.filter.UFSACOPanel: Sets the last values of the UFSACO parameters entered by user
setUserValue(double, int, int, int, double, double, double, double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_2Panel: Sets the last values of the IRRFSACO_2 parameters entered by user
setUserValue(double, int, int, int, double, double, double, double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_2Panel: Sets the last values of the RRFSACO_2 parameters entered by user
setUserValue(int) - Method in class unifeat.gui.classifier.KNNClassifierPanel: Sets the last values of the k-nearest neighbours parameters entered by user
setUserValue(int, double) - Method in class unifeat.gui.featureSelection.filter.LaplacianScorePanel: Sets the last values of the Laplacian score parameters entered by user
setUserValue(int, int, double, double) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: Sets the last values of the random tree parameters entered by user.
setUserValue(int, int, int) - Method in class unifeat.gui.featureSelection.embedded.decisionTreeBased.DecisionTreeBasedPanel: Sets the last values of the random forest parameters entered by user.
setUserValue(int, int, int, double, double, double) - Method in class unifeat.gui.featureSelection.filter.IRRFSACO_1Panel: Sets the last values of the IRRFSACO_1 parameters entered by user
setUserValue(int, int, int, double, double, double) - Method in class unifeat.gui.featureSelection.filter.RRFSACO_1Panel: Sets the last values of the RRFSACO_1 parameters entered by user
setUserValue(int, int, int, MultivariateMethodType) - Method in class unifeat.gui.featureSelection.filter.rsm.RSMPanel: Sets the last values of the RSM parameters entered by user
setUserValue(ClassifierType, Object, int, int, double, double, double, double, double, double, double, int) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.BasicPSOPanel: Sets the last values of the basic PSO parameters entered by user
setUserValue(ClassifierType, Object, int, int, double, double, double, double, double, double, double, int, double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.CPSOPanel: Sets the last values of the continuous PSO (CPSO) parameters entered by user
setUserValue(ClassifierType, Object, int, int, double, double, double, double, double, double, double, int, double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.PSO42Panel: Sets the last values of the PSO(4-2) parameters entered by user
setUserValue(ClassifierType, Object, int, int, double, double, double, double, double, double, double, int, double, double) - Method in class unifeat.gui.featureSelection.wrapper.PSOBased.HPSO_LSPanel: Sets the last values of the HPSO_LS parameters entered by user
setUserValue(ClassifierType, Object, int, int, double, double, double, int) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.BasicACOPanel: Sets the last values of the basic ACO parameters entered by user
setUserValue(ClassifierType, Object, int, int, double, double, double, int, double, double) - Method in class unifeat.gui.featureSelection.wrapper.ACOBased.OptimalACOPanel: Sets the last values of the Optimal ACO parameters entered by user
setUserValue(ClassifierType, Object, SelectionType, CrossOverType, MutationType, ReplacementType, int, int, double, double, int) - Method in class unifeat.gui.featureSelection.wrapper.GABased.BasicGAPanel: Sets the last values of the basic GA parameters entered by user
setUserValue(ClassifierType, Object, SelectionType, CrossOverType, MutationType, ReplacementType, int, int, double, double, int, double, double) - Method in class unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel: Sets the last values of the basic GA parameters entered by user
setUserValue(SVMKernelType, double) - Method in class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: Sets the last values of the support vector machine parameters entered by user
setUserValue(SVMKernelType, double, int, int) - Method in class unifeat.gui.featureSelection.embedded.MSVM_RFEPanel: Sets the last values of the MSVM_RFE parameters entered by user
SIMPLE_GA - Static variable in class unifeat.featureSelection.wrapper.WrapperType
SimpleGA - Class in unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA: This java class is used to implement feature selection method based on simple genetic algorithm (Simple GA) in which the type of Population is extended from Population class.
SimpleGA(Object...) - Constructor for class unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA.SimpleGA: Initializes the parameters
SimpleGAPanel - Class in unifeat.gui.featureSelection.wrapper.GABased: This java class is used to create and show a panel for the parameter settings of the simple genetic algorithm (Simple GA).
SimpleGAPanel() - Constructor for class unifeat.gui.featureSelection.wrapper.GABased.SimpleGAPanel: Creates new form SimpleGAPanel.
sortArray1D(double[], boolean) - Static method in class unifeat.util.ArraysFunc: Sorts the one dimensional array (double values) as descending or ascending order
sortArray1D(int[], boolean) - Static method in class unifeat.util.ArraysFunc: Sorts the one dimensional array (integer values) as descending or ascending order
sortArray1D(int[], boolean, int, int) - Static method in class unifeat.util.ArraysFunc: Sorts the one dimensional array (integer values) as descending or ascending order
sortArray2D(double[][], int) - Static method in class unifeat.util.ArraysFunc: Sorts the two dimensional array by using the index of column as ascending order
sortArray2D(double[][], int, int, int) - Static method in class unifeat.util.ArraysFunc: Sorts the two dimensional array by using the index of column as ascending order
sortWithIndex(double[], boolean) - Static method in class unifeat.util.ArraysFunc: Sorts the one dimensional array (double values) by values and returns a list of indices
sortWithIndex(int[], boolean) - Static method in class unifeat.util.ArraysFunc: Sorts the one dimensional array (integer values) by values and returns a list of indices
START_POS_INTERVAL - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm
subMatrix(double[][], double[][]) - Static method in class unifeat.util.MathFunc: Computes the subtract of two matrices
sum(double[]) - Static method in class unifeat.util.MathFunc: Computes the sum of the elements of input array
sum(double[], int, int) - Static method in class unifeat.util.MathFunc: Computes the sum of the elements of input array in the range of [start, end)
sum(int[]) - Static method in class unifeat.util.MathFunc: Computes the sum of the elements of input array
sum(int[], int, int) - Static method in class unifeat.util.MathFunc: Computes the sum of the elements of input array in the range of [start, end)
SupervisedFilterType - Class in unifeat.featureSelection.filter.supervised: This java class is used to define the names of supervised filter-based feature selection methods.
SVM - Static variable in class unifeat.classifier.ClassifierType
SVM(String, String, SVMKernelType, double) - Static method in class unifeat.classifier.evaluation.wekaClassifier.TrainTestEvaluation: This method builds and evaluates the support vector machine(SVM) classifier.
SVM(String, SVMKernelType, double, int) - Static method in class unifeat.classifier.evaluation.wekaClassifier.CrossValidation: This method builds and evaluates the support vector machine(SVM) classifier.
SVM_RFE - Class in unifeat.featureSelection.embedded.SVMBasedMethods: This java class is used to implement support vector machine method based on recursive feature elimination (SVM_RFE).
SVM_RFE - Static variable in class unifeat.featureSelection.embedded.EmbeddedType
SVM_RFE(Object...) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.SVM_RFE: Initializes the parameters
SVM_RFE(String, SVMKernelType, double) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.SVM_RFE: Initializes the parameters
SVMBasedMethods - Class in unifeat.featureSelection.embedded.SVMBasedMethods: The abstract class contains the main methods and fields that are used in all SVM-based feature selection methods.
SVMBasedMethods(Object...) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods: Initializes the parameters
SVMBasedMethods(String, SVMKernelType, double) - Constructor for class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods: Initializes the parameters
SVMClassifierPanel - Class in unifeat.gui.classifier.svmClassifier: This java class is used to create and show a panel for the parameter settings of the support vector machine classifier.
SVMClassifierPanel() - Constructor for class unifeat.gui.classifier.svmClassifier.SVMClassifierPanel: Creates new form SVMClassifierPanel.
SVMKernelType - Class in unifeat.gui.classifier.svmClassifier: This java class is used to define the names of kernel used in SVM.
swap(boolean[], int, boolean[], int) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Changes the values of the two elements in the two arrays identified by index1 and index2
swap(double[][], int, int) - Static method in class unifeat.util.MathFunc: Changes the values of the two rows in the input array identified by firstIndex and secondIndex
swap(double[], int, double[], int) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Changes the values of the two elements in the two arrays identified by index1 and index2
swap(int[], int, int) - Static method in class unifeat.util.MathFunc: Changes the values of the two elements in the input array identified by firstIndex and secondIndex
swap(GeneType[], int, GeneType[], int) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Changes the values of the two elements in the two arrays identified by index1 and index2
swap(T[], int, int) - Static method in class unifeat.util.MathFunc: Changes the values of the two elements in the input array identified by firstIndex and secondIndex
swarm - Variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicPSO
Swarm - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO: This java class is used to implement a swarm of particles in binary particle swarm optimization (BPSO) method in which the type of position vector is boolean and the type of particle is extended from Particle class.
Swarm - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO: This java class is used to implement a swarm of particles in continuous particle swarm optimization (CPSO) method in which the type of position vector is double and the type of particle is extended from Particle class.
Swarm - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS: This java class is used to implement a swarm of particles in hybrid particle swarm optimization method using local search (HPSO-LS) in which the type of position vector is boolean and the type of particle is extended from Particle class.
Swarm - Class in unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42: This java class is used to implement a swarm of particles in particle swarm optimization version 4-2(PSO(4-2)) method in which the type of position vector is double and the type of particle is extended from Particle class.
Swarm() - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Swarm: Initializes the parameters
Swarm(double) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Swarm: Initializes the parameters
Swarm(double) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Swarm: Initializes the parameters
Swarm(double, double) - Constructor for class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: Initializes the parameters
SYMMETRICAL_UNCERTAINTY - Static variable in class unifeat.featureSelection.filter.FilterType
SymmetricalUncertainty - Class in unifeat.featureSelection.filter.supervised: This java class is used to implement the symmetrical uncertainty method.
SymmetricalUncertainty(int) - Constructor for class unifeat.featureSelection.filter.supervised.SymmetricalUncertainty: Initializes the parameters
SymmetricalUncertainty(Object...) - Constructor for class unifeat.featureSelection.filter.supervised.SymmetricalUncertainty: Initializes the parameters

T

TEMP_PATH - Variable in class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods
TEMP_PATH - Variable in class unifeat.featureSelection.embedded.TreeBasedMethods.TreeBasedMethods
TEMP_PATH - Variable in class unifeat.featureSelection.wrapper.WrapperApproach
TERM_VARIANCE - Static variable in class unifeat.featureSelection.filter.FilterType
TermVariance - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the term variance method.
TermVariance(int) - Constructor for class unifeat.featureSelection.filter.unsupervised.TermVariance: Initializes the parameters
TermVariance(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.TermVariance: Initializes the parameters
THETA - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Particle
THETA - Static variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Particle
toString() - Method in class unifeat.featureSelection.EnumType: Converts the object name to string
toString() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicAnt: Returns a string representation of the ant.
toString() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicColony: Returns a string representation of the colony.
toString() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.BasicGraphRepresentation: Returns a string representation of the graph.
toString() - Method in class unifeat.result.Results: This method returns an empty string
toString(ResultType) - Method in class unifeat.result.Results: This method converts the obtained results over all runs to the string based on result type for showing in the result panel.
TOTAL - Static variable in class unifeat.gui.menu.selectMode.SelectModeType
TOTAL_REPLACEMENT - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.ReplacementType
trainSet - Variable in class unifeat.featureSelection.FeatureSelection
TrainTestEvaluation - Class in unifeat.classifier.evaluation.wekaClassifier: This java class is used to apply the classifiers for computing the performance of the feature selection methods.
TrainTestEvaluation() - Constructor for class unifeat.classifier.evaluation.wekaClassifier.TrainTestEvaluation
transMatrix(double[][]) - Static method in class unifeat.util.MathFunc: Computes the transpose of the input matrix
TREE_TYPE - Variable in class unifeat.featureSelection.embedded.TreeBasedMethods.TreeBasedMethods
TreeBasedMethods - Class in unifeat.featureSelection.embedded.TreeBasedMethods: The abstract class contains the main methods and fields that are used in all Tree-based feature selection methods.
TreeBasedMethods(Object...) - Constructor for class unifeat.featureSelection.embedded.TreeBasedMethods.TreeBasedMethods: Initializes the parameters
TreeType - Class in unifeat.gui.featureSelection.embedded.decisionTreeBased: This java class is used to define the names of different implementation of Tree.
TupleValues(Point, Point) - Constructor for class unifeat.gui.menu.DiagramPanel.TupleValues: Constructs and initializes a TupleValues with the specified (key, val).
TWO_POINT_CROSS_OVER - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.CrossOverType
twoPointCrossover(boolean[], boolean[]) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using two-point crossover
twoPointCrossover(double[], double[]) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using two-point crossover
twoPointCrossover(GeneType[], GeneType[]) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using two-point crossover

U

UFSACO - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to implement the unsupervised feature selection based on ant colony optimization (UFSACO) method.
UFSACO - Static variable in class unifeat.featureSelection.filter.FilterType
UFSACO(int, double, int, int, int, double, double, double) - Constructor for class unifeat.featureSelection.filter.unsupervised.UFSACO: Initializes the parameters
UFSACO(Object...) - Constructor for class unifeat.featureSelection.filter.unsupervised.UFSACO: Initializes the parameters
UFSACOPanel - Class in unifeat.gui.featureSelection.filter: This java class is used to create and show a panel for the parameter settings of the unsupervised feature selection based on ant colony optimization (UFSACO) method.
UFSACOPanel() - Constructor for class unifeat.gui.featureSelection.filter.UFSACOPanel: Creates new form UFSACOPanel.
unifeat.classifier - package unifeat.classifier
unifeat.classifier.evaluation.wekaClassifier - package unifeat.classifier.evaluation.wekaClassifier
unifeat.dataset - package unifeat.dataset
unifeat.featureSelection - package unifeat.featureSelection
unifeat.featureSelection.embedded - package unifeat.featureSelection.embedded
unifeat.featureSelection.embedded.SVMBasedMethods - package unifeat.featureSelection.embedded.SVMBasedMethods
unifeat.featureSelection.embedded.TreeBasedMethods - package unifeat.featureSelection.embedded.TreeBasedMethods
unifeat.featureSelection.filter - package unifeat.featureSelection.filter
unifeat.featureSelection.filter.supervised - package unifeat.featureSelection.filter.supervised
unifeat.featureSelection.filter.unsupervised - package unifeat.featureSelection.filter.unsupervised
unifeat.featureSelection.hybrid - package unifeat.featureSelection.hybrid
unifeat.featureSelection.wrapper - package unifeat.featureSelection.wrapper
unifeat.featureSelection.wrapper.ACOBasedMethods - package unifeat.featureSelection.wrapper.ACOBasedMethods
unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO - package unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO
unifeat.featureSelection.wrapper.GABasedMethods - package unifeat.featureSelection.wrapper.GABasedMethods
unifeat.featureSelection.wrapper.GABasedMethods.HGAFS - package unifeat.featureSelection.wrapper.GABasedMethods.HGAFS
unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA - package unifeat.featureSelection.wrapper.GABasedMethods.SimpleGA
unifeat.featureSelection.wrapper.PSOBasedMethods - package unifeat.featureSelection.wrapper.PSOBasedMethods
unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO - package unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO
unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO - package unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO
unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS - package unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS
unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42 - package unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42
unifeat.gui - package unifeat.gui
unifeat.gui.classifier - package unifeat.gui.classifier
unifeat.gui.classifier.svmClassifier - package unifeat.gui.classifier.svmClassifier
unifeat.gui.featureSelection.embedded - package unifeat.gui.featureSelection.embedded
unifeat.gui.featureSelection.embedded.decisionTreeBased - package unifeat.gui.featureSelection.embedded.decisionTreeBased
unifeat.gui.featureSelection.filter - package unifeat.gui.featureSelection.filter
unifeat.gui.featureSelection.filter.rsm - package unifeat.gui.featureSelection.filter.rsm
unifeat.gui.featureSelection.wrapper.ACOBased - package unifeat.gui.featureSelection.wrapper.ACOBased
unifeat.gui.featureSelection.wrapper.GABased - package unifeat.gui.featureSelection.wrapper.GABased
unifeat.gui.featureSelection.wrapper.PSOBased - package unifeat.gui.featureSelection.wrapper.PSOBased
unifeat.gui.menu - package unifeat.gui.menu
unifeat.gui.menu.selectMode - package unifeat.gui.menu.selectMode
unifeat.result - package unifeat.result
unifeat.result.performanceMeasure - package unifeat.result.performanceMeasure
unifeat.util - package unifeat.util
UNIFORM_CROSS_OVER - Static variable in class unifeat.gui.featureSelection.wrapper.GABased.CrossOverType
uniformCrossover(boolean[], boolean[], double) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using uniform crossover
uniformCrossover(double[], double[], double) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using uniform crossover
uniformCrossover(GeneType[], GeneType[], double) - Static method in class unifeat.featureSelection.wrapper.GABasedMethods.CrossoverOperator: Recombines (cross over) the two parents to generate new offsprings using uniform crossover
UnsupervisedFilterType - Class in unifeat.featureSelection.filter.unsupervised: This java class is used to define the names of unsupervised filter-based feature selection methods.
updateGlobalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method updates the global best position (global best) of the swarm.
updateGlobalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Swarm: This method updates the global best position (global best) of the swarm.
updateGlobalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Swarm: This method updates the global best position (global best) of the swarm.
updateGlobalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: This method updates the global best position (global best) of the swarm.
updateGlobalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Swarm: This method updates the global best position (global best) of the swarm.
updateParticlePosition() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method updates the position vector of each particle in the swarm.
updateParticlePosition() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Swarm: This method updates the position vector of each particle in the swarm.
updateParticlePosition() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Swarm: This method updates the position vector of each particle in the swarm.
updateParticlePosition() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: This method updates the position vector of each particle in the swarm.
updateParticlePosition() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Swarm: This method updates the position vector of each particle in the swarm.
updateParticleVelocity() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method updates the velocity vector of each particle in the swarm.
updateParticleVelocity() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Swarm: This method updates the velocity vector of each particle in the swarm.
updateParticleVelocity() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Swarm: This method updates the velocity vector of each particle in the swarm.
updateParticleVelocity() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: This method updates the velocity vector of each particle in the swarm.
updateParticleVelocity() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Swarm: This method updates the velocity vector of each particle in the swarm.
updatePersonalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicSwarm: This method updates the best position (personal best) of each particle in the swarm.
updatePersonalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BPSO.Swarm: This method updates the best position (personal best) of each particle in the swarm.
updatePersonalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.CPSO.Swarm: This method updates the best position (personal best) of each particle in the swarm.
updatePersonalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.HPSO_LS.Swarm: This method updates the best position (personal best) of each particle in the swarm.
updatePersonalBest() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.PSO42.Swarm: This method updates the best position (personal best) of each particle in the swarm.

V

validate() - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.MSVM_RFE: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.embedded.SVMBasedMethods.SVM_RFE: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.FeatureSelection: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.filter.unsupervised.IRRFSACO_1: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.filter.unsupervised.IRRFSACO_2: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.filter.unsupervised.LaplacianScore: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.filter.unsupervised.MGSACO: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.filter.unsupervised.RRFSACO_1: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.filter.unsupervised.RRFSACO_2: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.filter.unsupervised.RSM: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.filter.unsupervised.UFSACO: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.wrapper.ACOBasedMethods.OptimalACO.OptimalACO: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.wrapper.GABasedMethods.BasicGA: This method returns the potential errors in the input parameters.
validate() - Method in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicPSO: This method returns the potential errors in the input parameters.
value - Variable in class unifeat.featureSelection.EnumType
velocity - Variable in class unifeat.featureSelection.wrapper.PSOBasedMethods.BasicParticle

W

WeightedFilterApproach - Class in unifeat.featureSelection.filter: The abstract class contains the main methods and fields that are used in all weighted filter feature selection methods.
WeightedFilterApproach(int) - Constructor for class unifeat.featureSelection.filter.WeightedFilterApproach: Initializes the parameters
WeightedFilterType - Class in unifeat.featureSelection.filter: This java class is used to define the names of weighted filter-based feature selection methods.
WekaSVMKernel - Class in unifeat.classifier: This java class is used to convert SVM kernel implemented in unifeat tool to SVM kernel implemented in weka software.
WekaSVMKernel() - Constructor for class unifeat.classifier.WekaSVMKernel
WrapperApproach - Class in unifeat.featureSelection.wrapper: The abstract class contains the main methods and fields that are used in all wrapper-based feature selection methods.
WrapperApproach(String) - Constructor for class unifeat.featureSelection.wrapper.WrapperApproach: Initializes the parameters
WrapperType - Class in unifeat.featureSelection.wrapper: This java class is used to define the names of wrapper-based feature selection methods.

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