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) 1999-2002 Pascal Vincent, Yoshua Bengio, Rejean Ducharme and University of Montreal 00006 // Copyright (C) 2001-2002 Nicolas Chapados, Ichiro Takeuchi, Jean-Sebastien Senecal 00007 // Copyright (C) 2002 Xiangdong Wang, Christian Dorion 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: DiagonalizedFactorsProductVariable.h 2052 2004-07-19 22:31:11Z Dan Popovici $ 00040 * This file is part of the PLearn library. 00041 ******************************************************* */ 00042 00043 #ifndef WeightedLogGaussian_INC 00044 #define WeightedLogGaussian_INC 00045 00046 #include <plearn/var/NaryVariable.h> 00047 #include "Molecule.h" 00048 #include "Template.h" 00049 00050 namespace PLearn { 00051 using namespace std; 00052 00053 00056 class WeightedLogGaussian: public NaryVariable 00057 { 00058 typedef NaryVariable inherited; 00059 00060 public: 00062 WeightedLogGaussian() {} 00063 WeightedLogGaussian(bool training_mode, int class_label, Var input_index, Var mu, Var sigma, MoleculeTemplate templates); 00064 00065 int class_label ; 00066 bool training_mode ; 00067 VMat test_set ; 00068 00069 PLEARN_DECLARE_OBJECT(WeightedLogGaussian); 00070 00071 virtual void build(); 00072 00073 virtual void recomputeSize(int& l, int& w) const; 00074 virtual void fprop(); 00075 virtual void bprop(); 00076 virtual void symbolicBprop(); 00077 00078 Var& input_index() { return varray[0]; } 00079 Var& mu() { return varray[1]; } 00080 Var& sigma() { return varray[2]; } 00081 00082 MoleculeTemplate current_template ; 00083 PMolecule molecule; 00084 Mat W_lp ; 00085 00086 protected: 00087 void build_(); 00088 }; 00089 00090 DECLARE_OBJECT_PTR(WeightedLogGaussian); 00091 00092 /* 00093 inline Var diagonalized_factors_product(Var left_matrix, Var center_diagonal, Var right_matrix) 00094 { return new DiagonalizedFactorsProductVariable(left_matrix,center_diagonal,right_matrix); } 00095 */ 00096 } // end of namespace PLearn 00097 00098 00099 #endif