keel.Algorithms.ImbalancedClassification.Ensembles

Class multi_C45

java.lang.Object

keel.Algorithms.ImbalancedClassification.Ensembles.multi_C45

public class multi_C45
extends java.lang.Object

Title: multi_C45

Description: Main class to compute the algorithm procedure

Company: KEEL

Since:

JDK1.6

Version:

1.2

Author:

Mikel Galar Idoate (UPNA), Modified by Alberto Fernandez (University of Jaen) 15/10/2012, Modified by Sarah Vluymans (University of Ghent) 29/01/2014, Modified by Alberto Fernandez (University of Jaen) 08/05/2014

Field Summary

Fields

Modifier and Type	Field and Description
static java.lang.String	outputTr Training output filename.

Constructor Summary

Constructors

Constructor and Description
multi_C45() Default constructor
multi_C45(parseParameters parameters) It reads the data from the input files (training, validation and test) and parse all the parameters from the parameters array.

Method Summary

Modifier and Type	Method and Description
double	classify(myDataset dataset) It carries out the classification of a given dataset throughout the learning stage of the ensemble
void	execute() It launches the algorithm
protected int	obtainClass(int i, double[] example) It returns the class index of the prediction of an example in the i^{th} classifier
protected double	obtainConfidence(int i, double[] example) It obtains the confidence on the prediction of the example in the i^{th} classifier
void	writeOutput(AccAUC pairTra, AccAUC pairTst, java.lang.String ruleBaseFile) It writes on a file the full ensemble (C4.5 rule sets)

Methods inherited from class java.lang.Object

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

Field Detail

outputTr

public static java.lang.String outputTr

Training output filename.

Constructor Detail

multi_C45

public multi_C45()

Default constructor

multi_C45

public multi_C45(parseParameters parameters)

It reads the data from the input files (training, validation and test) and parse all the parameters from the parameters array.

Parameters:

parameters - parseParameters It contains the input files, output files and parameters

Method Detail

execute

public void execute()

It launches the algorithm

classify

public double classify(myDataset dataset)

It carries out the classification of a given dataset throughout the learning stage of the ensemble

Parameters:

dataset - the instance set

Returns:

accuracy for the current ensemble

obtainClass

protected int obtainClass(int i,
                          double[] example)

It returns the class index of the prediction of an example in the i^{th} classifier

Parameters:

i - the classifier to be used

example - the example to be classified

Returns:

the predicted class index

obtainConfidence

protected double obtainConfidence(int i,
                                  double[] example)

It obtains the confidence on the prediction of the example in the i^{th} classifier

Parameters:

i - the classifier to be used

example - the example to be classified

Returns:

the confidence on the prediction

writeOutput

public void writeOutput(AccAUC pairTra,
                        AccAUC pairTst,
                        java.lang.String ruleBaseFile)

It writes on a file the full ensemble (C4.5 rule sets)

Parameters:

pairTra - Training accuracy (AUC)

pairTst - Test accuracy (AUC)

ruleBaseFile - RuleBase filename.