/***********************************************************************
This file is part of KEEL-software, the Data Mining tool for regression,
classification, clustering, pattern mining and so on.
Copyright (C) 2004-2010
F. Herrera (herrera@decsai.ugr.es)
L. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (alberto.fernandez@ujaen.es)
J. Luengo (julianlm@decsai.ugr.es)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see http://www.gnu.org/licenses/
**********************************************************************/
/**
* <p>
* @author Written by Albert Orriols (La Salle, Ram�n Llull University - Barcelona) 28/03/2004
* @author Modified by Xavi Sol� (La Salle, Ram�n Llull University - Barcelona) 03/12/2008
* @version 1.1
* @since JDK1.2
* </p>
*/
package keel.Algorithms.Genetic_Rule_Learning.XCS;
import keel.Algorithms.Genetic_Rule_Learning.XCS.KeelParser.Config;
import java.lang.*;
import java.io.*;
import java.util.*;
public class TournamentSelection implements Selection {
/**
* <p>
* This class implements the tournament selection method.
* </p>
*/
///////////////////////////////////////
// attributes
/**
* <p>
* It is the first set of the population chosen by tournament.
* </p>
*
*/
private Classifier [] set1;
/**
* <p>
* It is the second set of the population chosen by tournament.
* </p>
*
*/
private Classifier [] set2;
/**
* <p>
* It is the set from which the selection has to be made.
* </p>
*
*/
private int activeSet = 1;
/**
* <p>
* It is the size of the tournament.
*
*/
private int tournamentSize;
///////////////////////////////////////
// operations
/**
* <p>
* Creates a TournamentSelection object
* </p>
*
*/
public TournamentSelection() {
activeSet = 1;
tournamentSize = 0;
set1 = null;
set2 = null;
} // end TournamentSelection
/**
* <p>
* Initializes the tournament selection. It initializes two sets of
* classifiers to make the tournament selection with them. Their size
* is a fraction of the action set size.
* </p>
* <p>
*
* @param pop is the population.
* </p>
*/
public void init(Population pop) {
int aleat = 0;
int aSetSize = pop.getMacroClSum();
tournamentSize = (int)Config.tournamentSize * aSetSize;
set1 = new Classifier [tournamentSize];
for (int i = 0; i<tournamentSize; i++){
aleat = (int) (Config.rand() * (double)aSetSize);
if (aleat == aSetSize) aleat --;
set1[i] = pop.getClassifier(aleat);
}
set2 = new Classifier[tournamentSize];
for (int i = 0; i<tournamentSize; i++){
aleat = (int) (Config.rand() * (double)aSetSize);
if (aleat == aSetSize) aleat --;
set2[i] = pop.getClassifier(aleat);
}
activeSet = 1;
} // end init
/**
* <p>
* Applies the tournament selection.
* </p>
* <p>
* @param pop is the population.
* </p>
* <p>
* @return a Classifier with the selected classifier
* </p>
*/
public Classifier makeSelection(Population pop) {
double maxFitness = -1000;
int pos = -1;
for (int i=0; i<tournamentSize; i++){
if (activeSet == 1){
if (set1[i].getFitness() > maxFitness){
pos = i;
maxFitness = set1[i].getFitness();
}
}
else{
if (set2[i].getFitness() > maxFitness){
pos = i;
maxFitness = set2[i].getFitness();
}
}
}
if (pos >= 0){
if (activeSet == 1){
activeSet = 2;
return set1[pos];
}
else{
activeSet = 1;
return set2[pos];
}
}
else{
activeSet = activeSet%2 +1;
return null;
}
} // end makeSelection
} // end TournamentSelection