PLearn 0.1
BinaryClassificationLossVariable.cc
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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 :
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