PLearn 0.1
LocalGaussianClassifier.h
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00001 // -*- C++ -*-
00002 
00003 // LocalGaussianClassifier.h
00004 //
00005 // Copyright (C) 2007 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 LocalGaussianClassifier_INC
00041 #define LocalGaussianClassifier_INC
00042 
00043 #include <plearn_learners/generic/PLearner.h>
00044 
00045 // From C++ stdlib
00046 #include <utility>                           
00047 #include <algorithm>                         
00048 
00049 namespace PLearn {
00050 
00061 class LocalGaussianClassifier : public PLearner
00062 {
00063     typedef PLearner inherited;
00064     
00065 
00066 protected:
00067 
00068     // Vec emptyvec;
00069     // mutable Vec NN_outputs;
00070     // mutable Vec NN_costs;
00071 
00072     // *********************
00073     // * protected options *
00074     // *********************
00075 
00076     // PP<GenericNearestNeighbors> NN;
00077 
00078 
00079 public:
00080     //#####  Public Build Options  ############################################
00081 
00082     int nclasses;
00083     real computation_neighbors;
00084     real kernel_sigma;
00085     real regularization_sigma;
00086     real ignore_weights_below;
00087 
00088 private:
00089     real minus_one_half_over_kernel_sigma_square;
00090 
00092     Vec trainsample;
00093     Vec traininput;
00094     real* traintarget_ptr;
00095     real* trainweight_ptr;
00096     mutable TVec< pair<real,int> > pqvec; // priority queue (heap) vector 
00097 
00098     Vec log_counts;  // the log_counts considering all points
00099     Vec log_counts2; // the log_counts considering only the points kept for computing the covariance
00100     Mat means;    
00101     Mat allcovars;
00102     TVec<Mat> covars;
00103 
00104 
00105 public:
00106     //#####  Public Member Functions  #########################################
00107 
00109     // ### Make sure the implementation in the .cc
00110     // ### initializes all fields to reasonable default values.
00111     LocalGaussianClassifier();
00112 
00113 
00114     //#####  PLearner Member Functions  #######################################
00115 
00118     // (PLEASE IMPLEMENT IN .cc)
00119     virtual int outputsize() const;
00120 
00124     // (PLEASE IMPLEMENT IN .cc)
00125     virtual void forget();
00126 
00127     virtual void setTrainingSet(VMat training_set, bool call_forget=true);
00128 
00132     // (PLEASE IMPLEMENT IN .cc)
00133     virtual void train();
00134 
00136     // (PLEASE IMPLEMENT IN .cc)
00137     virtual void computeOutput(const Vec& input, Vec& output) const;
00138 
00140     // (PLEASE IMPLEMENT IN .cc)
00141     virtual void computeCostsFromOutputs(const Vec& input, const Vec& output,
00142                                          const Vec& target, Vec& costs) const;
00143 
00146     // (PLEASE IMPLEMENT IN .cc)
00147     virtual TVec<std::string> getTestCostNames() const;
00148 
00149     real computeLogWeight(const Vec& input, const Vec& traininput) const;
00150 
00153     // (PLEASE IMPLEMENT IN .cc)
00154     virtual TVec<std::string> getTrainCostNames() const;
00155 
00156 
00157     // *** SUBCLASS WRITING: ***
00158     // While in general not necessary, in case of particular needs
00159     // (efficiency concerns for ex) you may also want to overload
00160     // some of the following methods:
00161     // virtual void computeOutputAndCosts(const Vec& input, const Vec& target,
00162     //                                    Vec& output, Vec& costs) const;
00163     // virtual void computeCostsOnly(const Vec& input, const Vec& target,
00164     //                               Vec& costs) const;
00165     // virtual void test(VMat testset, PP<VecStatsCollector> test_stats,
00166     //                   VMat testoutputs=0, VMat testcosts=0) const;
00167     // virtual int nTestCosts() const;
00168     // virtual int nTrainCosts() const;
00169     // virtual void resetInternalState();
00170     // virtual bool isStatefulLearner() const;
00171 
00172 
00173     //#####  PLearn::Object Protocol  #########################################
00174 
00175     // Declares other standard object methods.
00176     // ### If your class is not instantiatable (it has pure virtual methods)
00177     // ### you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT_METHODS
00178     PLEARN_DECLARE_OBJECT(LocalGaussianClassifier);
00179 
00180     // Simply calls inherited::build() then build_()
00181     virtual void build();
00182 
00184     // (PLEASE IMPLEMENT IN .cc)
00185     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00186 
00187 protected:
00188     //#####  Protected Options  ###############################################
00189 
00190     // ### Declare protected option fields (such as learned parameters) here
00191     // ...
00192 
00193 protected:
00194     //#####  Protected Member Functions  ######################################
00195 
00197     // (PLEASE IMPLEMENT IN .cc)
00198     static void declareOptions(OptionList& ol);
00199 
00200 private:
00201     //#####  Private Member Functions  ########################################
00202 
00204     // (PLEASE IMPLEMENT IN .cc)
00205     void build_();
00206 
00207 private:
00208     //#####  Private Data Members  ############################################
00209 
00210     // The rest of the private stuff goes here
00211 };
00212 
00213 // Declares a few other classes and functions related to this class
00214 DECLARE_OBJECT_PTR(LocalGaussianClassifier);
00215 
00216 } // end of namespace PLearn
00217 
00218 #endif
00219 
00220 
00221 /*
00222   Local Variables:
00223   mode:c++
00224   c-basic-offset:4
00225   c-file-style:"stroustrup"
00226   c-file-offsets:((innamespace . 0)(inline-open . 0))
00227   indent-tabs-mode:nil
00228   fill-column:79
00229   End:
00230 */
00231 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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