/*
* 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 java.util.LinkedList;
import java.util.List;
import com.rapidminer.operator.IOObject;
import com.rapidminer.operator.MissingIOObjectException;
import com.rapidminer.operator.Operator;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.operator.performance.PerformanceVector;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeDouble;
import com.rapidminer.tools.math.SignificanceTestResult;
/**
* Determines if the null hypothesis (all actual mean values are the same) holds
* for the input performance vectors.
*
* @author Ingo Mierswa
* @version $Id: SignificanceTestOperator.java,v 1.5 2006/04/05 08:57:28
* ingomierswa Exp $
*/
public abstract class SignificanceTestOperator extends Operator {
public static final String PARAMETER_ALPHA = "alpha";
public SignificanceTestOperator(OperatorDescription description) {
super(description);
}
/**
* Returns the result of the significance test for the given performance
* vector collection.
*/
public abstract SignificanceTestResult performSignificanceTest(PerformanceVector[] allVectors, double alpha) throws OperatorException;
/**
* Returns the minimum number of performance vectors which can be compared
* by this significance test.
*/
public abstract int getMinSize();
/**
* Returns the maximum number of performance vectors which can be compared
* by this significance test.
*/
public abstract int getMaxSize();
/** Writes the attribute set to a file. */
public IOObject[] apply() throws OperatorException {
List<PerformanceVector> allVectors = new LinkedList<PerformanceVector>();
boolean ok = true;
while (ok) {
try {
PerformanceVector pv = getInput(PerformanceVector.class);
allVectors.add(pv);
} catch (MissingIOObjectException e) {
ok = false;
}
}
if (allVectors.size() < getMinSize()) {
throw new UserError(this, 123, PerformanceVector.class, getMinSize() + "");
}
if (allVectors.size() > getMaxSize()) {
throw new UserError(this, 124, PerformanceVector.class, getMaxSize() + "");
}
PerformanceVector[] allVectorsArray = new PerformanceVector[allVectors.size()];
allVectors.toArray(allVectorsArray);
SignificanceTestResult result = performSignificanceTest(allVectorsArray, getParameterAsDouble(PARAMETER_ALPHA));
// create result array
IOObject[] resultArray = new IOObject[allVectors.size() + 1];
System.arraycopy(allVectorsArray, 0, resultArray, 0, allVectorsArray.length);
resultArray[resultArray.length - 1] = result;
return resultArray;
}
public Class<?>[] getInputClasses() {
return new Class[] { PerformanceVector.class };
}
public Class<?>[] getOutputClasses() {
return new Class[] { PerformanceVector.class, SignificanceTestResult.class };
}
public List<ParameterType> getParameterTypes() {
List<ParameterType> types = super.getParameterTypes();
types.add(new ParameterTypeDouble(PARAMETER_ALPHA, "The probability threshold which determines if differences are considered as significant.", 0.0d, 1.0d, 0.05d));
return types;
}
}