/* * 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: 5922 $ */ 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); }