PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // AutoLinearRegressor.h 00004 // 00005 // Copyright (C) 2006 Pascal Vincent 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 // Authors: Pascal Vincent 00036 00040 #ifndef AutoLinearRegressor_INC 00041 #define AutoLinearRegressor_INC 00042 00043 #include <plearn_learners/generic/PLearner.h> 00044 00045 namespace PLearn { 00046 00057 class AutoLinearRegressor : public PLearner 00058 { 00059 typedef PLearner inherited; 00060 00061 public: 00062 //##### Public Options ############################################ 00063 00067 bool include_bias; 00068 00069 real min_weight_decay; 00070 00071 real weight_decay; 00072 00073 Mat weights; 00074 00075 Vec mean_target; 00076 00077 public: 00078 //##### Public Member Functions ######################################### 00079 00081 // ### Make sure the implementation in the .cc 00082 // ### initializes all fields to reasonable default values. 00083 AutoLinearRegressor(); 00084 00085 //##### PLearner Member Functions ####################################### 00086 00089 // (PLEASE IMPLEMENT IN .cc) 00090 virtual int outputsize() const; 00091 00095 // (PLEASE IMPLEMENT IN .cc) 00096 virtual void forget(); 00097 00101 // (PLEASE IMPLEMENT IN .cc) 00102 virtual void train(); 00103 00105 // (PLEASE IMPLEMENT IN .cc) 00106 virtual void computeOutput(const Vec& input, Vec& output) const; 00107 00109 // (PLEASE IMPLEMENT IN .cc) 00110 virtual void computeCostsFromOutputs(const Vec& input, const Vec& output, 00111 const Vec& target, Vec& costs) const; 00112 00115 // (PLEASE IMPLEMENT IN .cc) 00116 virtual TVec<std::string> getTestCostNames() const; 00117 00120 // (PLEASE IMPLEMENT IN .cc) 00121 virtual TVec<std::string> getTrainCostNames() const; 00122 00123 00124 // *** SUBCLASS WRITING: *** 00125 // While in general not necessary, in case of particular needs 00126 // (efficiency concerns for ex) you may also want to overload 00127 // some of the following methods: 00128 // virtual void computeOutputAndCosts(const Vec& input, const Vec& target, 00129 // Vec& output, Vec& costs) const; 00130 // virtual void computeCostsOnly(const Vec& input, const Vec& target, 00131 // Vec& costs) const; 00132 // virtual void test(VMat testset, PP<VecStatsCollector> test_stats, 00133 // VMat testoutputs=0, VMat testcosts=0) const; 00134 // virtual int nTestCosts() const; 00135 // virtual int nTrainCosts() const; 00136 // virtual void resetInternalState(); 00137 // virtual bool isStatefulLearner() const; 00138 00139 00140 //##### PLearn::Object Protocol ######################################### 00141 00142 // Declares other standard object methods. 00143 // ### If your class is not instantiatable (it has pure virtual methods) 00144 // ### you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT_METHODS 00145 PLEARN_DECLARE_OBJECT(AutoLinearRegressor); 00146 00147 // Simply calls inherited::build() then build_() 00148 virtual void build(); 00149 00151 // (PLEASE IMPLEMENT IN .cc) 00152 virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies); 00153 00154 protected: 00155 //##### Protected Options ############################################### 00156 00157 // ### Declare protected option fields (such as learned parameters) here 00158 // ... 00159 00160 protected: 00161 //##### Protected Member Functions ###################################### 00162 00164 // (PLEASE IMPLEMENT IN .cc) 00165 static void declareOptions(OptionList& ol); 00166 00167 private: 00168 //##### Private Member Functions ######################################## 00169 00171 void build_(); 00172 00173 00174 private: 00175 //##### Private Data Members ############################################ 00176 00177 // The rest of the private stuff goes here 00178 00180 real weights_norm; 00181 mutable Vec extendedinput; 00182 }; 00183 00184 // Declares a few other classes and functions related to this class 00185 DECLARE_OBJECT_PTR(AutoLinearRegressor); 00186 00187 } // end of namespace PLearn 00188 00189 #endif 00190 00191 00192 /* 00193 Local Variables: 00194 mode:c++ 00195 c-basic-offset:4 00196 c-file-style:"stroustrup" 00197 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00198 indent-tabs-mode:nil 00199 fill-column:79 00200 End: 00201 */ 00202 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :