bruteforceoperator.java

著名的开源仿真软件yale

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2002, 2003
 *      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;

import edu.udo.cs.yale.example.ExampleSet;
import edu.udo.cs.yale.example.AttributeSelectionExampleSet;
import edu.udo.cs.yale.operator.OperatorException;

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

/** This feature selection operator selects the best attribute set by trying all possible
 *  combinations of attribute selections. It returns the example set containing
 *  the subset of attributes which produced the best performance. As this operator
 *  works on the powerset of the attributes set it has exponential runtime.
 *
 *  @yale.xmlclass BruteForce
 *  @author simon
 *  @version $Id: BruteForceOperator.java,v 2.5 2003/08/23 18:55:49 mierswa Exp $ <br>
 */
public class BruteForceOperator extends FeatureOperator {

    /** An empty operator list. */
    private List emptyList;

    public void initApply() throws OperatorException {
	super.initApply();
	emptyList = new LinkedList();
	
    }

    public Population createInitialPopulation(ExampleSet es) {
	AttributeSelectionExampleSet exampleSet = new AttributeSelectionExampleSet(es);
	for (int i = 0; i < es.getNumberOfAttributes(); i++)
	    exampleSet.setAttributeUsed(i, false);
	Population pop = new Population();
	addAll(pop, exampleSet, 0);
	return pop;
    }

    /** Recursive method to add all attribute combinations to the population. */	
    private void addAll(Population pop, AttributeSelectionExampleSet es, int startIndex) {
	if (startIndex >= es.getNumberOfAttributes()) return;

	AttributeSelectionExampleSet ce2 = (AttributeSelectionExampleSet)es.clone();
	ce2.setAttributeUsed(startIndex, false);
	addAll(pop, ce2, startIndex+1);
    
	AttributeSelectionExampleSet ce1 = (AttributeSelectionExampleSet)es.clone();
	ce1.setAttributeUsed(startIndex, true);
	if (ce1.getNumberOfAttributes() > 0) pop.add(ce1);
	addAll(pop, ce1, startIndex+1);
    }
	

    /** Does nothing. */
    public List getPreEvaluationPopulationOperators() { return emptyList; }

    /** Does nothing. */
    public List getPostEvaluationPopulationOperators() { return emptyList; }

    /** Stops immediately. */
    public boolean solutionGoodEnough(Population pop) { return true; }
}