/*
* RapidMiner
*
* Copyright (C) 2001-2008 by Rapid-I and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapid-i.com
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as published by
* the Free Software Foundation, either version 3 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 Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.operator.features.weighting;
import com.rapidminer.example.Attribute;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.set.AttributeWeightedExampleSet;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.features.Individual;
import com.rapidminer.operator.features.Population;
import com.rapidminer.operator.features.PopulationOperator;
/**
* Uses the backward selection idea for the weighting of features.
*
* @author Ingo Mierswa
* @version $Id: BackwardWeighting.java,v 1.10 2006/03/21 15:35:46 ingomierswa
* Exp $
*/
public class BackwardWeighting extends FeatureWeighting {
public BackwardWeighting(OperatorDescription description) {
super(description);
}
public PopulationOperator getWeightingOperator(String parameter) {
double[] weights = new double[] { 1.0d, 0.75d, 0.5d, 0.25d };
if ((parameter != null) && (parameter.length() != 0)) {
try {
String[] weightStrings = parameter.split(" ");
weights = new double[weightStrings.length];
for (int i = 0; i < weights.length; i++)
weights[i] = Double.parseDouble(weightStrings[i]);
} catch (Exception e) {
logError("Could not create weights: " + e.getMessage() + "! Use standard weights.");
weights = new double[] { 1.0d, 0.75d, 0.5d, 0.25d };
}
}
return new SimpleWeighting(1.0d, weights);
}
public Population createInitialPopulation(ExampleSet es) {
Population initPop = new Population();
AttributeWeightedExampleSet nes = new AttributeWeightedExampleSet((ExampleSet) es.clone());
for (Attribute attribute : es.getAttributes())
nes.setWeight(attribute, 1.0d);
initPop.add(new Individual(nes));
return initPop;
}
}