PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // PLS.h 00004 // 00005 // Copyright (C) 2004 Olivier Delalleau 00006 // 00007 // Redistribution and use in source and binary forms, with or without 00008 // modification, are permitted provided that the following conditions are met: 00009 // 00010 // 1. Redistributions of source code must retain the above copyright 00011 // notice, this list of conditions and the following disclaimer. 00012 // 00013 // 2. Redistributions in binary form must reproduce the above copyright 00014 // notice, this list of conditions and the following disclaimer in the 00015 // documentation and/or other materials provided with the distribution. 00016 // 00017 // 3. The name of the authors may not be used to endorse or promote 00018 // products derived from this software without specific prior written 00019 // permission. 00020 // 00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR 00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN 00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED 00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00031 // 00032 // This file is part of the PLearn library. For more information on the PLearn 00033 // library, go to the PLearn Web site at www.plearn.org 00034 00035 /* ******************************************************* 00036 * $Id: PLS.h 6465 2006-11-29 03:40:00Z chapados $ 00037 ******************************************************* */ 00038 00039 // Authors: Olivier Delalleau 00040 00043 #ifndef PLS_INC 00044 #define PLS_INC 00045 00046 #include <plearn_learners/generic/PLearner.h> 00047 00048 namespace PLearn { 00049 using namespace std; 00050 00051 class PLS: public PLearner 00052 { 00053 00054 public: 00055 00056 typedef PLearner inherited; 00057 00058 protected: 00059 00060 // ********************* 00061 // * protected options * 00062 // ********************* 00063 00064 Mat B; 00065 int m; 00066 Vec mean_input; 00067 Vec mean_target; 00068 int p; 00069 Vec stddev_input; 00070 Vec stddev_target; 00071 Mat W; 00072 00076 Vec resid_variance; 00077 00078 public: 00079 00080 // ************************ 00081 // * public build options * 00082 // ************************ 00083 00084 int k; 00085 string method; 00086 real precision; 00087 bool output_the_score; 00088 bool output_the_target; 00089 bool compute_confidence; 00090 00091 // **************** 00092 // * Constructors * 00093 // **************** 00094 00095 // Default constructor, make sure the implementation in the .cc 00096 // initializes all fields to reasonable default values. 00097 PLS(); 00098 00099 00100 // ******************** 00101 // * PLearner methods * 00102 // ******************** 00103 00104 private: 00105 00107 void build_(); 00108 00109 protected: 00110 00112 static void declareOptions(OptionList& ol); 00113 00115 void computeResidVariance(VMat dataset, Vec& resid_variance); 00116 00117 public: 00118 00119 // ************************ 00120 // **** Object methods **** 00121 // ************************ 00122 00124 virtual void build(); 00125 00127 virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies); 00128 00129 // Declares other standard object methods. 00130 // If your class is not instantiatable (it has pure virtual methods) 00131 // you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT_METHODS. 00132 PLEARN_DECLARE_OBJECT(PLS); 00133 00134 00135 // ************************** 00136 // **** PLearner methods **** 00137 // ************************** 00138 00141 virtual int outputsize() const; 00142 00145 virtual void forget(); 00146 00149 virtual void train(); 00150 00152 virtual void computeOutput(const Vec& input, Vec& output) const; 00153 00155 virtual void computeCostsFromOutputs(const Vec& input, const Vec& output, 00156 const Vec& target, Vec& costs) const; 00157 00159 virtual bool computeConfidenceFromOutput(const Vec&, const Vec& output, real probability, 00160 TVec< pair<real,real> >& intervals) const; 00161 00163 virtual TVec<string> getTestCostNames() const; 00164 00167 virtual TVec<string> getTrainCostNames() const; 00168 00169 // *** SUBCLASS WRITING: *** 00170 // While in general not necessary, in case of particular needs 00171 // (efficiency concerns for ex) you may also want to overload 00172 // some of the following methods: 00173 // virtual void computeOutputAndCosts(const Vec& input, const Vec& target, Vec& output, Vec& costs) const; 00174 // virtual void computeCostsOnly(const Vec& input, const Vec& target, Vec& costs) const; 00175 // virtual void test(VMat testset, PP<VecStatsCollector> test_stats, VMat testoutputs=0, VMat testcosts=0) const; 00176 // virtual int nTestCosts() const; 00177 // virtual int nTrainCosts() const; 00178 00179 00180 //***** STATIC METHODS ***** 00181 00187 static void NIPALSEigenvector(const Mat& m, Vec& v, real precision); 00188 00189 }; 00190 00191 // Declares a few other classes and functions related to this class. 00192 DECLARE_OBJECT_PTR(PLS); 00193 00194 } // end of namespace PLearn 00195 00196 #endif 00197 00198 00199 /* 00200 Local Variables: 00201 mode:c++ 00202 c-basic-offset:4 00203 c-file-style:"stroustrup" 00204 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00205 indent-tabs-mode:nil 00206 fill-column:79 00207 End: 00208 */ 00209 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :