📄 attributegenerator.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.AttributeWeightedExampleSet;
import edu.udo.cs.yale.example.Tools;
import edu.udo.cs.yale.tools.RandomGenerator;
import edu.udo.cs.yale.generator.*;
import edu.udo.cs.yale.example.Attribute;
import java.util.ArrayList;
import java.util.LinkedList;
import java.util.List;
/** This PopulationOperator generates new attributes in an individual's example table. Given a generation
* probability <tt>pGenerate</p> and the maximal number of new attributes it generates on average
* <tt>pGenerate</tt> * <tt>numberOfNewAttributes</tt> new attributes using generators from the list
* <tt>generatorList</tt> <br/>
*
* This operator can never handle value series but only single attributes.
*
* @author ingo
* @version 29.05.2001 <br>
*/
public class AttributeGenerator extends IndividualOperator {
/** Probability to generate a new attribute.
*/
private double pGenerate;
/** Maximal number of newly generated attributes.
*/
private int numberOfNewAttributes;
/** A list of applicable generators.
*/
private List generatorList;
/** Creates a new <tt>AttributeGenerator</tt> with given parameters.
*/
public AttributeGenerator(double pGenerate, int numberOfNewAttributes, List generatorList) {
this.pGenerate = pGenerate;
this.numberOfNewAttributes = numberOfNewAttributes;
this.generatorList = generatorList;
}
/** Determines the applicable generators and generatess up to
* <tt>numberOfNewAttributes</tt> new attributes. */
public List operate(AttributeWeightedExampleSet exampleSet) throws Exception {
//Ermittlung der anwendbaren Generatoren bzgl. des gegebenen ExampleSets
//int combinationSum = Tools.setArgumentCombinations(exampleSet, generatorList);
ArrayList selectedGeneratorList = new ArrayList();
for (int h = 0; h < numberOfNewAttributes ; h++){
if (RandomGenerator.getGlobalRandomGenerator().nextDouble() < pGenerate) {
//zufaellige Auswahl eines konkreten Generators aus der Menge der anwendbaren Generatoren
FeatureGenerator selectedGenerator = FeatureGenerator.selectGenerator(exampleSet, generatorList, 0, new String[0]).newInstance();
//Ermittlung der vom selektierten Generator geforderten Eingabe-Attribute
Attribute[] arguments = Tools.getRandomCompatibleAttributes(exampleSet, selectedGenerator, 0, new String[0]);
selectedGenerator.setArguments(arguments);
//selektierten FeatureGenerator in ArrayList einfuegen
selectedGeneratorList.add(selectedGenerator);
}
}
//System.out.println("*** NEW GENERATION ***\n" + selectedGeneratorList);
if (selectedGeneratorList.size() > 0)
//Anwendung der ausgewaehlten Generatoren auf das aktuelle ExampleSet
exampleSet.addAllAttributes(FeatureGenerator.generateAll(exampleSet.getExampleTable(), selectedGeneratorList));
List result = new LinkedList();
result.add(exampleSet);
return result;
}
}
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