/*
* 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., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
/*
* RankingLossFunctionBase.java
* Copyright (C) 2009-2010 Aristotle University of Thessaloniki, Thessaloniki, Greece
*/
package mulan.evaluation.loss;
import java.io.Serializable;
import mulan.classifier.MultiLabelOutput;
import mulan.core.ArgumentNullException;
/**
* Base class for ranking loss functions
*
* @author GrigoriosTsoumakas
* @version 2010.11.10
*/
public abstract class RankingLossFunctionBase implements RankingLossFunction, Serializable {
private void checkRanking(int[] ranking) {
if (ranking == null) {
throw new ArgumentNullException("Ranking is null");
}
}
private void checkLength(int[] ranking, boolean[] groundTruth) {
if (ranking.length != groundTruth.length) {
throw new IllegalArgumentException("The dimensions of the " +
"ranking and the ground truth array do not match");
}
}
public final double computeLoss(MultiLabelOutput prediction, boolean[] groundTruth) {
int[] ranking = prediction.getRanking();
checkRanking(ranking);
checkLength(ranking, groundTruth);
return computeLoss(ranking, groundTruth);
}
abstract public double computeLoss(int[] ranking, boolean[] groundTruth);
}