PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // PLearn (A C++ Machine Learning Library) 00004 // Copyright (C) 1998 Pascal Vincent 00005 // Copyright (C) 1999-2001 Pascal Vincent, Yoshua Bengio, Rejean Ducharme and University of Montreal 00006 // Copyright (C) 2002 Pascal Vincent, Julien Keable, Xavier Saint-Mleux 00007 // Copyright (C) 2003 Olivier Delalleau 00008 // 00009 // Redistribution and use in source and binary forms, with or without 00010 // modification, are permitted provided that the following conditions are met: 00011 // 00012 // 1. Redistributions of source code must retain the above copyright 00013 // notice, this list of conditions and the following disclaimer. 00014 // 00015 // 2. Redistributions in binary form must reproduce the above copyright 00016 // notice, this list of conditions and the following disclaimer in the 00017 // documentation and/or other materials provided with the distribution. 00018 // 00019 // 3. The name of the authors may not be used to endorse or promote 00020 // products derived from this software without specific prior written 00021 // permission. 00022 // 00023 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR 00024 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 00025 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN 00026 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 00027 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED 00028 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00029 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00030 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00031 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00032 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00033 // 00034 // This file is part of the PLearn library. For more information on the PLearn 00035 // library, go to the PLearn Web site at www.plearn.org 00036 00037 00038 /* ****************************************************************** 00039 * $Id: CovariancePreservationImputationVMatrix.h 3658 2005-07-06 20:30:15 Godbout $ 00040 ****************************************************************** */ 00041 00044 #ifndef CovariancePreservationImputationVMatrix_INC 00045 #define CovariancePreservationImputationVMatrix_INC 00046 00047 #include <plearn/vmat/ImputationVMatrix.h> 00048 #include <plearn/vmat/SourceVMatrix.h> 00049 #include <plearn/vmat/FileVMatrix.h> 00050 #include <plearn/io/fileutils.h> 00051 #include <plearn/math/BottomNI.h> 00052 00053 namespace PLearn { 00054 using namespace std; 00055 00056 class CovariancePreservationImputationVMatrix: public ImputationVMatrix 00057 { 00058 typedef ImputationVMatrix inherited; 00059 00060 public: 00061 00064 VMat train_set; 00065 00066 00067 CovariancePreservationImputationVMatrix(); 00068 virtual ~CovariancePreservationImputationVMatrix(); 00069 00070 static void declareOptions(OptionList &ol); 00071 00072 virtual void build(); 00073 virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies); 00074 00075 virtual void getExample(int i, Vec& input, Vec& target, real& weight); 00076 virtual real get(int i, int j) const; 00077 virtual void put(int i, int j, real value); 00078 virtual void getSubRow(int i, int j, Vec v) const; 00079 virtual void putSubRow(int i, int j, Vec v); 00080 virtual void appendRow(Vec v); 00081 virtual void insertRow(int i, Vec v); 00082 virtual void getRow(int i, Vec v) const; 00083 virtual void putRow(int i, Vec v); 00084 virtual void getColumn(int i, Vec v) const; 00085 VMat getCovarianceFile(); 00086 00087 private: 00088 00089 int train_length; 00090 int train_width; 00091 int train_inputsize; 00092 int train_targetsize; 00093 int train_weightsize; 00094 int train_row; 00095 Vec train_input; 00096 TVec<string> train_field_names; 00097 PPath train_metadata; 00098 int source_length; 00099 int source_width; 00100 int source_inputsize; 00101 int source_targetsize; 00102 int source_weightsize; 00103 PPath covariance_file_name; 00104 VMat covariance_file; 00105 int indj; 00106 int indk; 00107 Mat n_obs; 00108 Mat sum_xj; 00109 Mat sum_xj_xk; 00110 Vec mu; 00111 Mat cov; 00112 00113 void build_(); 00114 void createCovarianceFile(); 00115 void loadCovarianceFile(); 00116 void computeCovariances(); 00117 real computeImputation(int row, int col) const; 00118 real computeImputation(int row, int col, Vec input) const; 00119 00120 PLEARN_DECLARE_OBJECT(CovariancePreservationImputationVMatrix); 00121 00122 }; 00123 00124 DECLARE_OBJECT_PTR(CovariancePreservationImputationVMatrix); 00125 00126 } // end of namespcae PLearn 00127 #endif