PLearn 0.1
VariableSelectionWithDirectedGradientDescent.h
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00001 // -*- C++ -*-
00002 
00003 // VariableSelectionWithDirectedGradientDescent.h
00004 // Copyright (c) 1998-2002 Pascal Vincent
00005 // Copyright (C) 1999-2002 Yoshua Bengio and University of Montreal
00006 // Copyright (c) 2002 Jean-Sebastien Senecal, Xavier Saint-Mleux, Rejean Ducharme
00007 //
00008 // Redistribution and use in source and binary forms, with or without
00009 // modification, are permitted provided that the following conditions are met:
00010 // 
00011 //  1. Redistributions of source code must retain the above copyright
00012 //     notice, this list of conditions and the following disclaimer.
00013 // 
00014 //  2. Redistributions in binary form must reproduce the above copyright
00015 //     notice, this list of conditions and the following disclaimer in the
00016 //     documentation and/or other materials provided with the distribution.
00017 // 
00018 //  3. The name of the authors may not be used to endorse or promote
00019 //     products derived from this software without specific prior written
00020 //     permission.
00021 // 
00022 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00023 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00024 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00025 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00026 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00027 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00028 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00029 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00030 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00031 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00032 // 
00033 // This file is part of the PLearn library. For more information on the PLearn
00034 // library, go to the PLearn Web site at www.plearn.org
00035 
00036 
00037 /* **************************************************************************************************************    
00038  * $Id: VariableSelectionWithDirectedGradientDescent.h, v 1.0 2004/07/19 10:00:00 Bengio/Kegl/Godbout         *
00039  * This file is part of the PLearn library.                                                                   *
00040  ************************************************************************************************************** */
00041 
00042 
00043 #ifndef VariableSelectionWithDirectedGradientDescent_INC
00044 #define VariableSelectionWithDirectedGradientDescent_INC
00045 
00046 #include <plearn_learners/generic/PLearner.h>
00047 
00048 namespace PLearn {
00049 using namespace std;
00050 
00051 class VariableSelectionWithDirectedGradientDescent: public PLearner
00052 {
00053     typedef PLearner inherited;
00054 private:        
00055     int inputsize;                              // input size of train set
00056     int targetsize;                             // output size of train set
00057     int weightsize;                             // weightsize size of train set
00058     int length;                                 // number of samples in train set
00059     int width;                                  // number of columns in train set
00060   
00061     real learning_rate;  
00062     Mat input_weights;
00063     TVec<bool> weights_selected;
00064     TVec<int> selected_variables;
00065   
00066     PP<ProgressBar> pb;
00067     int row;
00068     int col;
00069     Vec sample_input;
00070     Vec sample_target;
00071     real sample_weight;
00072     Vec sample_output;
00073     Vec sample_cost;  
00074     Vec train_criterion;
00075     real n7_value;
00076     real n8_value;
00077     real n9_value;
00078     real n10_value;
00079     real n10_gradient;
00080     real n9_gradient;
00081     real n8_gradient;
00082     real n7_gradient;
00083     Mat weights_gradient;
00084     int weights_gradient_max_col;
00085     real weights_gradient_max;
00087     Vec sum_of_abs_gradient;
00088   
00089   
00090 public:
00091 
00093     VariableSelectionWithDirectedGradientDescent();
00094     
00095     PLEARN_DECLARE_OBJECT(VariableSelectionWithDirectedGradientDescent);
00096 
00097     virtual void         makeDeepCopyFromShallowCopy(CopiesMap &copies);
00098     virtual void         build();
00099     virtual void         train();
00100     virtual void         forget();
00101     virtual int          outputsize() const;
00102     virtual TVec<string> getTrainCostNames() const;
00103     virtual TVec<string> getTestCostNames() const;
00104     virtual void         computeOutput(const Vec& input, Vec& output) const;
00105     virtual void         computeCostsFromOutputs(const Vec& input, const Vec& output, const Vec& target, Vec& costs) const;
00107     virtual void         setTrainingSet(VMat training_set, bool call_forget=true);
00108 
00109 
00110 protected:
00111 
00112     static  void         declareOptions(OptionList& ol);
00113 
00114 private:
00115     void         build_();
00116     void         verbose(string the_msg, int the_level);
00117 };
00118 
00119 DECLARE_OBJECT_PTR(VariableSelectionWithDirectedGradientDescent);
00120 
00121 } // end of namespace PLearn
00122 
00123 #endif
00124 
00125 
00126 /*
00127   Local Variables:
00128   mode:c++
00129   c-basic-offset:4
00130   c-file-style:"stroustrup"
00131   c-file-offsets:((innamespace . 0)(inline-open . 0))
00132   indent-tabs-mode:nil
00133   fill-column:79
00134   End:
00135 */
00136 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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