Package unifeat.featureSelection.filter.unsupervised

Class MGSACO

java.lang.Object

unifeat.featureSelection.FeatureSelection

unifeat.featureSelection.filter.FilterApproach

unifeat.featureSelection.filter.unsupervised.MGSACO

public class MGSACO
extends FilterApproach

This java class is used to implement the microarray gene selection based on ant colony optimization (MGSACO) method.

Author:

Sina Tabakhi

See Also:

• FilterApproach
• FeatureSelection

Field Summary

Fields inherited from class unifeat.featureSelection.FeatureSelection

numClass, numFeatures, numSelectedFeature, selectedFeatureSubset, trainSet

Constructor Summary

Constructors

Constructor	Description
MGSACO(int sizeSelectedFeatureSubset, double initPheromone, int numIterations, int numAnt, double evaporationRate, double betaParameter, double q0_Parameter)	Initializes the parameters
MGSACO(Object... arguments)	Initializes the parameters

Method Summary

Modifier and Type	Method	Description
void	evaluateFeatures()	Starts the feature selection process by microarray gene selection based on ant colony optimization (MGSACO) method
String	validate()	This method returns the potential errors in the input parameters.

Methods inherited from class unifeat.featureSelection.filter.FilterApproach

newMethod

Methods inherited from class unifeat.featureSelection.FeatureSelection

getSelectedFeatureSubset, loadDataSet, loadDataSet, setNumSelectedFeature

Methods inherited from class java.lang.Object

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

Constructor Details

MGSACO

public MGSACO(Object... arguments)

Initializes the parameters

Parameters:

arguments - array of parameter contains (sizeSelectedFeatureSubset, initPheromone, numIterations, numAnt, evaporationRate, betaParameter, q0_Parameter) in which sizeSelectedFeatureSubset is the number of selected features, initPheromone is the initial value of the pheromone, numIterations is the maximum number of iteration, numAnt is the number of ants, evaporationRate is the evaporation rate of the pheromone, betaParameter is the beta parameter in the state transition rule, and q0_Parameter is the q0 parameter in the state transition rule

MGSACO

public MGSACO(int sizeSelectedFeatureSubset,
 double initPheromone,
 int numIterations,
 int numAnt,
 double evaporationRate,
 double betaParameter,
 double q0_Parameter)

Initializes the parameters

Parameters:

sizeSelectedFeatureSubset - the number of selected features

initPheromone - the initial value of the pheromone

numIterations - the maximum number of iteration

numAnt - the number of ants

evaporationRate - the evaporation rate of the pheromone

betaParameter - the beta parameter in the state transition rule

q0_Parameter - the q0 parameter in the state transition rule

Method Details

evaluateFeatures

public void evaluateFeatures()

Starts the feature selection process by microarray gene selection based on ant colony optimization (MGSACO) method

Specified by:

evaluateFeatures in class FeatureSelection

validate

public String validate()

This method returns the potential errors in the input parameters.

Overrides:

validate in class FeatureSelection

Returns:

a string contains the information about incorrect parameters