📄 bruteforceoperator.java
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/*
* 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: yale-team@lists.sourceforge.net
* 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.AttributeWeightedExampleSet;
import edu.udo.cs.yale.example.Attribute;
import edu.udo.cs.yale.tools.Ontology;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.operator.parameter.*;
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 2.13 2004/09/14 08:39:05 ingomierswa Exp $ <br>
*/
public class BruteForceOperator extends FeatureOperator {
/** An empty operator list. */
private List emptyList = new LinkedList();
/** The post evaluation population operators list contains a result to output stream writer
* if a parameter is set. */
private List postOps = new LinkedList();
public Population createInitialPopulation(ExampleSet es) {
AttributeWeightedExampleSet exampleSet = new AttributeWeightedExampleSet(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, AttributeWeightedExampleSet es, int startIndex) {
if (startIndex >= es.getNumberOfAttributes()) return;
Attribute attribute = es.getAttribute(startIndex);
int endIndex =
Ontology.ATTRIBUTE_BLOCK_TYPE.isA(attribute.getBlockType(), Ontology.VALUE_SERIES) ?
es.getBlockEndIndex(startIndex) :
startIndex;
AttributeWeightedExampleSet ce2 = (AttributeWeightedExampleSet)es.clone();
for (int i = startIndex; i <= endIndex; i++)
ce2.setAttributeUsed(i, false);
addAll(pop, ce2, endIndex+1);
AttributeWeightedExampleSet ce1 = (AttributeWeightedExampleSet)es.clone();
for (int i = startIndex; i <= endIndex; i++)
ce1.setAttributeUsed(i, true);
if (ce1.getNumberOfUsedAttributes() > 0) pop.add(ce1);
addAll(pop, ce1, endIndex+1);
}
/** Does nothing. */
public List getPreEvaluationPopulationOperators() { return emptyList; }
/** Returns an empty list if the parameter debug_output is set to false. */
public List getPostEvaluationPopulationOperators() { return postOps; }
/** Stops immediately. */
public boolean solutionGoodEnough(Population pop) { return true; }
}
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