generatinggeneticalgorithm.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.operator.parameter.*;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.generator.*;
import edu.udo.cs.yale.operator.features.*;
import edu.udo.cs.yale.tools.LogService;

import java.util.ArrayList;
import java.util.List;

/** In contrast to its superclass {@link GeneticAlgorithm}, the {@link GeneratingGeneticAlgorithm}
 *  generates new attributes and thus can change the length of an individual. Therfore specialized mutation
 *  and crossover operators are being applied. Generators are chosen at random from a list of generators
 *  specified by boolean parameters. <br/>
 *
 *  Since this operator does not contain algorithms to extract features from value series, it is restricted
 *  to example sets with only single attributes. For automatic feature extraction from values series the 
 *  value series plugin for Yale written by Ingo Mierswa should be used. It is available at 
 *  <a href="http://yale.cs.uni-dortmund.de">http://yale.cs.uni-dortmund.de</a>
 *
 *  @yale.reference Ritthoff/etal/2001a
 *  @yale.xmlclass GeneratingGeneticAlgorithm
 *  @author ingo
 *  @version $Id: GeneratingGeneticAlgorithm.java,v 2.14 2004/08/27 11:57:36 ingomierswa Exp $
 */
public class GeneratingGeneticAlgorithm extends AbstractGeneratingGeneticAlgorithm {

    /** Returns an operator that performs the mutation. Can be overridden by subclasses. */
    protected PopulationOperator getMutationPopulationOperator() {
	double pMutation  = getParameterAsDouble("p_mutation");
	return new SelectionMutation(pMutation);
    }

    /** Returns a specialized mutation, i.e. a <code>AttributeGenerator</code> */
    protected PopulationOperator getGeneratingPopulationOperator() {
	List generators = getGenerators();
	if (generators.size()==0) {
	    LogService.logMessage("No FeatureGenerators specified for " + getName() + ".", LogService.WARNING);
	}
	int    noOfNewAttributes = getParameterAsInt("max_number_of_new_attributes"); 
	double pGenerate         = getParameterAsDouble("p_generate");
	return new AttributeGenerator(pGenerate, noOfNewAttributes, generators);
    }    

    public List getParameterTypes() {
	List types = super.getParameterTypes();
	ParameterType type = new ParameterTypeInt("max_number_of_new_attributes", "Max number of attributes to generate for an individual.", 0, Integer.MAX_VALUE, 1);
	type.setExpert(false);
	types.add(type);
	type = new ParameterTypeDouble("p_generate", "Probability for an individual to be selected for generation.", 0, 1, 0.1);
	type.setExpert(false);
	types.add(type);
	type = new ParameterTypeDouble("p_mutation", 
				       "Probability for an attribute to be changed (-1: 1 / numberOfAtts).", 
				       -1.0d, 1.0d, 0.1d);
	type.setExpert(false);
	types.add(type);
	return types;
    }
}