/*
* 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.
*/
/*
* NominalLossFunction.java
* Copyright (C) 2004 Stijn Lievens
*
*/
package weka.classifiers.misc.monotone;
/**
* Interface for incorporating different loss functions.
* <p>
* This interface contains only one method, namely <code> loss
* </code> that measures the error between an actual class
* value <code> actual </code> and a predicted value <code>
* predicted. </code> It is understood that the return value
* of this method is always be positive and that it is zero
* if and only if the actual and the predicted value coincide.
* </p>
* <p>
* This implementation is done as part of the master's thesis: "Studie
* en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd
* rangschikken", Stijn Lievens, Ghent University, 2004.
* </p>
*
* @author Stijn Lievens (stijn.lievens@ugent.be)
* @version $Revision$
*/
public interface NominalLossFunction {
/**
* Calculate the loss between an actual and a predicted class value.
*
* @param actual the actual class value
* @param predicted the predicted class value
* @return a measure for the error of making the prediction
* <code> predicted </code> instead of <code> actual </code>
*/
public double loss(double actual, double predicted);
}