/*
* RapidMiner
*
* Copyright (C) 2001-2008 by Rapid-I and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapid-i.com
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero 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 Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.operator.features.aggregation;
import java.util.LinkedList;
import java.util.List;
import java.util.Random;
/**
* Performs a tournament selection on the given population list.
*
* @author Ingo Mierswa
* @version $Id: AggregationTournamentSelection.java,v 1.3 2006/03/27 13:21:58
* ingomierswa Exp $
*/
public class AggregationTournamentSelection implements AggregationSelection {
private int popSize = 10;
private double tournamentFraction = 0.25;
private Random random;
public AggregationTournamentSelection(int popSize, double tournamentFraction, Random random) {
this.popSize = popSize;
this.tournamentFraction = tournamentFraction;
this.random = random;
}
public void performSelection(List<AggregationIndividual> population) {
List<AggregationIndividual> newGeneration = new LinkedList<AggregationIndividual>();
int tournamentSize = Math.max((int) Math.round(population.size() * tournamentFraction), 1);
while (newGeneration.size() < popSize) {
AggregationIndividual winner = null;
for (int k = 0; k < tournamentSize; k++) {
AggregationIndividual current = population.get(random.nextInt(population.size()));
if ((winner == null) || (current.getPerformance().getMainCriterion().getFitness() > (winner.getPerformance().getMainCriterion().getFitness())))
winner = current;
}
newGeneration.add(winner);
}
population.clear();
population.addAll(newGeneration);
}
}