/*
* 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.validation.significance;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.operator.performance.PerformanceCriterion;
import com.rapidminer.operator.performance.PerformanceVector;
import com.rapidminer.tools.math.AnovaCalculator;
import com.rapidminer.tools.math.SignificanceCalculationException;
import com.rapidminer.tools.math.SignificanceTestResult;
/**
* Determines if the null hypothesis (all actual mean values are the same) holds
* for the input performance vectors. This operator uses an ANalysis Of
* VAriances approach to determine probability that the null hypothesis is
* wrong.
*
* @author Ingo Mierswa
* @version $Id: AnovaSignificanceTestOperator.java,v 1.5 2006/03/21 15:35:52
* ingomierswa Exp $
*/
public class AnovaSignificanceTestOperator extends SignificanceTestOperator {
public AnovaSignificanceTestOperator(OperatorDescription description) {
super(description);
}
public SignificanceTestResult performSignificanceTest(PerformanceVector[] allVectors, double alpha) throws OperatorException {
AnovaCalculator calculator = new AnovaCalculator();
calculator.setAlpha(alpha);
for (int i = 0; i < allVectors.length; i++) {
PerformanceCriterion pc = allVectors[i].getMainCriterion();
calculator.addGroup(pc.getAverageCount(), pc.getAverage(), pc.getVariance());
}
try {
return calculator.performSignificanceTest();
} catch (SignificanceCalculationException e) {
throw new UserError(this, 920, e.getMessage());
}
}
public int getMinSize() {
return 2;
}
public int getMaxSize() {
return Integer.MAX_VALUE;
}
}