1 | ## Process this file with automake to produce Makefile.in |
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2 | ## |
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3 | ## $Id$ |
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4 | |
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5 | # Copyright (C) 2005, 2006, 2007, 2008 Jari Häkkinen, Peter Johansson, Markus Ringnér |
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6 | # |
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7 | # This file is part of the yat library, http://dev.thep.lu.se/yat |
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8 | # |
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9 | # The yat library is free software; you can redistribute it and/or |
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10 | # modify it under the terms of the GNU General Public License as |
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11 | # published by the Free Software Foundation; either version 2 of the |
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12 | # License, or (at your option) any later version. |
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13 | # |
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14 | # The yat library is distributed in the hope that it will be useful, |
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15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of |
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16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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17 | # General Public License for more details. |
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18 | # |
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19 | # You should have received a copy of the GNU General Public License |
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20 | # along with this program; if not, write to the Free Software |
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21 | # Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA |
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22 | # 02111-1307, USA. |
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23 | |
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24 | include $(top_srcdir)/build_support/yat.am |
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25 | |
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26 | noinst_LTLIBRARIES = libclassifier.la |
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27 | libclassifier_la_SOURCES = \ |
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28 | BootstrapSampler.cc \ |
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29 | ConsensusInputRanker.cc \ |
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30 | CrossValidationSampler.cc \ |
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31 | DataLookup1D.cc \ |
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32 | DataLookupWeighted1D.cc \ |
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33 | FeatureSelector.cc \ |
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34 | FeatureSelectorIR.cc \ |
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35 | FeatureSelectorRandom.cc \ |
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36 | GaussianKernelFunction.cc \ |
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37 | InputRanker.cc \ |
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38 | Kernel.cc \ |
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39 | Kernel_MEV.cc \ |
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40 | Kernel_SEV.cc \ |
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41 | KernelLookup.cc \ |
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42 | KNN_Uniform.cc \ |
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43 | KNN_ReciprocalDistance.cc \ |
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44 | KNN_ReciprocalRank.cc \ |
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45 | MatrixLookup.cc \ |
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46 | MatrixLookupWeighted.cc \ |
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47 | NBC.cc \ |
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48 | PolynomialKernelFunction.cc \ |
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49 | Sampler.cc \ |
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50 | SupervisedClassifier.cc \ |
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51 | SVindex.cc \ |
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52 | SVM.cc \ |
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53 | Target.cc \ |
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54 | utility.cc |
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55 | |
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56 | include_classifierdir = $(includedir)/yat/classifier |
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57 | |
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58 | include_classifier_HEADERS = \ |
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59 | BootstrapSampler.h \ |
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60 | ConsensusInputRanker.h \ |
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61 | CrossValidationSampler.h \ |
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62 | DataLookup1D.h \ |
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63 | DataLookupWeighted1D.h \ |
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64 | EnsembleBuilder.h \ |
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65 | FeatureSelector.h \ |
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66 | FeatureSelectorIR.h \ |
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67 | FeatureSelectorRandom.h \ |
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68 | GaussianKernelFunction.h \ |
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69 | IGP.h \ |
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70 | IRRank.h \ |
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71 | IRRetrieve.h \ |
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72 | InputRanker.h \ |
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73 | Kernel.h \ |
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74 | KernelFunction.h \ |
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75 | KernelLookup.h \ |
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76 | Kernel_MEV.h \ |
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77 | Kernel_SEV.h \ |
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78 | KNN.h \ |
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79 | KNN_ReciprocalDistance.h \ |
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80 | KNN_ReciprocalRank.h \ |
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81 | KNN_Uniform.h \ |
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82 | MatrixLookup.h \ |
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83 | MatrixLookupWeighted.h \ |
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84 | NBC.h \ |
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85 | NCC.h \ |
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86 | PolynomialKernelFunction.h \ |
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87 | SVM.h \ |
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88 | SVindex.h \ |
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89 | Sampler.h \ |
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90 | SubsetGenerator.h \ |
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91 | SupervisedClassifier.h \ |
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92 | Target.h \ |
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93 | utility.h |
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