/***********************************************************************
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 RouletteSelection implements Selection{
/**
* <p>
* This class implements Selection roulette.
* </p>
*/
///////////////////////////////////////
// attributes
/**
* <p>
* It's a roulette object.
* </p>
*
*/
private Roulette roul;
///////////////////////////////////////
// operations
/**
* <p>
* Creates a RouletteSelection object.
* </p>
*
*/
public RouletteSelection() {
roul = null;
} // end RouletteSelection
/**
* <p>
* It creates and initializes the roulette with the fitness of all
* classifiers in the population.
* </p>
* <p>
*
* @param pop is the action set where the selection has to be applied.
* </p>
* <p>
* @see Roulette
* </p>
*/
public void init(Population pop) {
int i = 0;
double lowerFitness=0;
roul = new Roulette (pop.getMacroClSum());
for (i=0; i<pop.getMacroClSum(); i++){
roul.add(pop.getClassifier(i).getFitness() /*- lowerFitness*/);
}
} // end init
/**
* <p>
* Performs the roulette wheel selection
* </p>
* <p>
* @param pop is the population.
* </p>
* <p>
* @return a Classifier with the selected classifier
* </p>
*/
public Classifier makeSelection(Population pop) {
int i = roul.selectRoulette();
return pop.getClassifier(i);
} // end makeSelection
} // end RouletteSelection