PLearn 0.1
CovariancePreservationImputationVMatrix.h
Go to the documentation of this file.
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
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines