selectionmutation.java

一个很好的LIBSVM的JAVA源码。对于要研究和改进SVM算法的学者。可以参考。来自数据挖掘工具YALE工具包。

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2001-2004
 *      Simon Fischer, Ralf Klinkenberg, Ingo Mierswa, 
 *          Katharina Morik, Oliver Ritthoff
 *      Artificial Intelligence Unit
 *      Computer Science Department
 *      University of Dortmund
 *      44221 Dortmund,  Germany
 *  email: [e-mail]
 *  web:   http://yale.cs.uni-dortmund.de/
 *
 *  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 2 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, write to the Free Software
 *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
 *  USA.
 */
package edu.udo.cs.yale.operator.features.ga;

import edu.udo.cs.yale.example.AttributeWeightedExampleSet;
import edu.udo.cs.yale.tools.RandomGenerator;
import edu.udo.cs.yale.operator.features.*;

import java.util.LinkedList;
import java.util.List;

/** Inverts the used bit for every feature of every example set with a given fixed probability.
 *
 *  @author simon, ingo
 *  @version $Id: SelectionMutation.java,v 2.13 2004/08/27 11:57:36 ingomierswa Exp $
 */
public class SelectionMutation extends IndividualOperator {

    private double probability;

    public SelectionMutation(double probability) { 
	this.probability = probability; 
    }

    public List operate(AttributeWeightedExampleSet es) {
	LinkedList l = new LinkedList();
	AttributeWeightedExampleSet exampleSet = (AttributeWeightedExampleSet)es;
	AttributeWeightedExampleSet clone = (AttributeWeightedExampleSet)es.clone();
	double prob = probability < 0 ? 1.0d / (double)clone.getNumberOfAttributes() : probability;
	for (int i = 0; i < clone.getNumberOfAttributes(); i++) {
	    if (RandomGenerator.getGlobalRandomGenerator().nextDouble() < prob) {
		i = clone.flipAttributeUsed(i);
	    }
	}
	if (clone.getNumberOfUsedAttributes() > 0) {
	    l.add(clone);
	} else {
	    l.add(exampleSet);
	}
	return l;
    }
}