/*
* RapidMiner
*
* Copyright (C) 2001-2011 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.performance;
import com.rapidminer.tools.Tools;
/**
* The average relative error in a lenient way of calculation:
* <i>Sum(|label-predicted|/max(|label|, |predicted|))/#examples</i>.
* The relative error of label 0 and prediction 0 is defined as 0.
*
* @author Ingo Mierswa
*/
public class LenientRelativeError extends SimpleCriterion {
private static final long serialVersionUID = -6816726234908353254L;
public LenientRelativeError() {}
public LenientRelativeError(LenientRelativeError sc) {
super(sc);
}
@Override
public double countExample(double label, double predictedLabel) {
double diff = Math.abs(label - predictedLabel);
double absLabel = Math.abs(label);
double absPrediction = Math.abs(predictedLabel);
if (Tools.isZero(diff)) {
return 0.0d;
} else {
return diff / Math.max(absLabel, absPrediction);
}
}
/**
* Indicates whether or not percentage format should be used in the
* {@link #toString} method. The default implementation returns false.
*/
@Override
public boolean formatPercent() {
return true;
}
@Override
public String getName() {
return "relative_error_lenient";
}
@Override
public String getDescription() {
return "Average lenient relative error (average of absolute deviation of the prediction from the actual value divided by maximum of the actual value and the prediction)";
}
}