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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 2 of the License, or
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* (at your option) any later version.
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
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* NominalLossFunction.java
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* Copyright (C) 2004 Stijn Lievens
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package weka.classifiers.misc.monotone;
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* Interface for incorporating different loss functions.
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* This interface contains only one method, namely <code> loss
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* </code> that measures the error between an actual class
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* value <code> actual </code> and a predicted value <code>
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* predicted. </code> It is understood that the return value
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* of this method is always be positive and that it is zero
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* if and only if the actual and the predicted value coincide.
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* This implementation is done as part of the master's thesis: "Studie
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* en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd
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* rangschikken", Stijn Lievens, Ghent University, 2004.
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* @author Stijn Lievens (stijn.lievens@ugent.be)
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* @version $Revision: 1.1 $
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public interface NominalLossFunction {
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* Calculate the loss between an actual and a predicted class value.
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* @param actual the actual class value
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* @param predicted the predicted class value
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* @return a measure for the error of making the prediction
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* <code> predicted </code> instead of <code> actual </code>
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public double loss(double actual, double predicted);