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 // Copyright (C) 2004 Olivier Delalleau 00009 00010 // Redistribution and use in source and binary forms, with or without 00011 // modification, are permitted provided that the following conditions are met: 00012 // 00013 // 1. Redistributions of source code must retain the above copyright 00014 // notice, this list of conditions and the following disclaimer. 00015 // 00016 // 2. Redistributions in binary form must reproduce the above copyright 00017 // notice, this list of conditions and the following disclaimer in the 00018 // documentation and/or other materials provided with the distribution. 00019 // 00020 // 3. The name of the authors may not be used to endorse or promote 00021 // products derived from this software without specific prior written 00022 // permission. 00023 // 00024 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR 00025 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 00026 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN 00027 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 00028 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED 00029 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00030 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00031 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00032 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00033 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00034 // 00035 // This file is part of the PLearn library. For more information on the PLearn 00036 // library, go to the PLearn Web site at www.plearn.org 00037 00038 00039 /* ******************************************************* 00040 * $Id: BinaryClassificationLossVariable.cc 3994 2005-08-25 13:35:03Z chapados $ 00041 * This file is part of the PLearn library. 00042 ******************************************************* */ 00043 00044 #include "BinaryClassificationLossVariable.h" 00045 namespace PLearn { 00046 using namespace std; 00047 00050 PLEARN_IMPLEMENT_OBJECT( 00051 BinaryClassificationLossVariable, 00052 "Variable outputting the class for thresholded binary classification", 00053 "For one-dimensional output, \n" 00054 "Class is 'class_1' if output < 'threshold', and 'class_2' if >= 'threshold'. \n" 00055 ); 00056 00057 00058 BinaryClassificationLossVariable::BinaryClassificationLossVariable() 00059 : threshold(0.0) 00060 { } 00061 00063 // declareOptions // 00065 void BinaryClassificationLossVariable::declareOptions(OptionList& ol) { 00066 declareOption(ol, "threshold", &BinaryClassificationLossVariable::threshold, OptionBase::buildoption, 00067 "The threshold under which the class is 'class_1', and above which the class is 'class_2'."); 00068 inherited::declareOptions(ol); 00069 } 00070 00071 BinaryClassificationLossVariable::BinaryClassificationLossVariable(Variable* netout, Variable* classnum) 00072 : inherited(netout,classnum,1,1), 00073 class_1(0), 00074 class_2(1), 00075 threshold(0.5) 00076 { 00077 build_(); 00078 } 00079 00080 void 00081 BinaryClassificationLossVariable::build() 00082 { 00083 inherited::build(); 00084 build_(); 00085 } 00086 00087 void 00088 BinaryClassificationLossVariable::build_() 00089 { 00090 // input2 == classnum from constructor 00091 if (input2 && !input2->isScalar()) 00092 PLERROR("In BinaryClassificationLossVariable: classnum must be a scalar variable representing an index of netout (typically a class number)"); 00093 } 00094 00095 void BinaryClassificationLossVariable::recomputeSize(int& l, int& w) const 00096 { l=1, w=1; } 00097 00098 00099 void BinaryClassificationLossVariable::fprop() 00100 { 00101 int classnum = int(input2->valuedata[0]); 00102 int outputclass; 00103 if (input1->valuedata[0] < threshold) { 00104 outputclass = class_1; 00105 } else { 00106 outputclass = class_2; 00107 } 00108 00109 valuedata[0] = (outputclass == classnum ?0 :1); 00110 } 00111 00112 } // end of namespace PLearn 00113 00114 00115 /* 00116 Local Variables: 00117 mode:c++ 00118 c-basic-offset:4 00119 c-file-style:"stroustrup" 00120 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00121 indent-tabs-mode:nil 00122 fill-column:79 00123 End: 00124 */ 00125 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :