| 1 | /* |
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| 2 | * This program is free software; you can redistribute it and/or modify |
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| 3 | * it under the terms of the GNU General Public License as published by |
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| 4 | * the Free Software Foundation; either version 2 of the License, or |
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| 5 | * (at your option) any later version. |
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| 6 | * |
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| 7 | * This program is distributed in the hope that it will be useful, |
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| 8 | * but WITHOUT ANY WARRANTY; without even the implied warranty of |
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| 9 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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| 10 | * GNU General Public License for more details. |
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| 11 | * |
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| 12 | * You should have received a copy of the GNU General Public License |
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| 13 | * along with this program; if not, write to the Free Software |
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| 14 | * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. |
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| 15 | */ |
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| 16 | |
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| 17 | /* |
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| 18 | * ZeroOneLossFunction.java |
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| 19 | * Copyright (C) 2004 Stijn Lievens |
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| 20 | * |
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| 21 | */ |
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| 22 | |
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| 23 | package weka.classifiers.misc.monotone; |
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| 24 | |
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| 25 | import weka.core.RevisionHandler; |
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| 26 | import weka.core.RevisionUtils; |
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| 27 | |
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| 28 | /** |
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| 29 | * Class implementing the zero-one loss function, this is |
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| 30 | * an incorrect prediction always accounts for one unit loss. |
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| 31 | * |
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| 32 | * <p> |
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| 33 | * This implementation is done as part of the master's thesis: "Studie |
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| 34 | * en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd |
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| 35 | * rangschikken", Stijn Lievens, Ghent University, 2004. |
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| 36 | * </p> |
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| 37 | * |
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| 38 | * @author Stijn Lievens (stijn.lievens@ugent.be) |
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| 39 | * @version $Revision: 5922 $ |
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| 40 | */ |
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| 41 | public class ZeroOneLossFunction |
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| 42 | implements NominalLossFunction, RevisionHandler { |
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| 43 | |
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| 44 | /** |
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| 45 | * Returns the zero-one loss function between two class values. |
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| 46 | * |
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| 47 | * @param actual the actual class value |
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| 48 | * @param predicted the predicted class value |
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| 49 | * @return 1 if the actual and predicted value differ, 0 otherwise |
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| 50 | */ |
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| 51 | public final double loss(double actual, double predicted) { |
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| 52 | return actual == predicted ? 0 : 1; |
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| 53 | } |
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| 54 | |
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| 55 | /** |
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| 56 | * Returns a string with the name of the loss function. |
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| 57 | * |
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| 58 | * @return a string with the name of the loss function |
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| 59 | */ |
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| 60 | public String toString() { |
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| 61 | return "ZeroOneLossFunction"; |
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| 62 | } |
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| 63 | |
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| 64 | /** |
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| 65 | * Returns the revision string. |
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| 66 | * |
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| 67 | * @return the revision |
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| 68 | */ |
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| 69 | public String getRevision() { |
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| 70 | return RevisionUtils.extract("$Revision: 5922 $"); |
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| 71 | } |
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| 72 | } |
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