PLearn 0.1
GradientAdaboostCostVariable.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) 2003 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: GradientAdaboostCostVariable.cc 6827 2007-04-03 23:08:36Z larocheh $
00041  * This file is part of the PLearn library.
00042  ******************************************************* */
00043 
00044 #include "GradientAdaboostCostVariable.h"
00045 
00046 namespace PLearn {
00047 using namespace std;
00048 
00051 PLEARN_IMPLEMENT_OBJECT(
00052     GradientAdaboostCostVariable,
00053     "Cost for weak learner in MarginBoost version of AdaBoost",
00054     "Cost for a weak learner used in the functional gradient descent view of\n"
00055     "boosting on a margin-based loss function. See \"Functional Gradient \n"
00056     "Techniques for Combining Hypotheses\" by Mason et al.");
00057 
00059 // GradientAdaboostCostVariable //
00061 GradientAdaboostCostVariable::GradientAdaboostCostVariable(Variable* output, Variable* target)
00062     : inherited(output,target,output->size(),1)
00063 {
00064     build_();
00065 }
00066 
00067 void
00068 GradientAdaboostCostVariable::build()
00069 {
00070     inherited::build();
00071     build_();
00072 }
00073 
00074 void
00075 GradientAdaboostCostVariable::build_()
00076 {
00077     if (input2 && input2->size() != input1->size())
00078         PLERROR("In GradientAdaboostCostVariable: target and output should have same size");
00079 }
00080 
00081 void
00082 GradientAdaboostCostVariable::declareOptions(OptionList &ol)
00083 {
00084     inherited::declareOptions(ol);
00085 }
00086 
00088 // recomputeSize //
00090 void GradientAdaboostCostVariable::recomputeSize(int& l, int& w) const
00091 { l=input1->size(), w=1; }
00092 
00094 // fprop //
00096 void GradientAdaboostCostVariable::fprop()
00097 {
00098     for(int i=0; i<length(); i++)
00099         valuedata[i] = -1*(2*input1->valuedata[i]-1)*(2*input2->valuedata[i]-1);
00100 }
00101 
00103 // bprop //
00105 void GradientAdaboostCostVariable::bprop()
00106 {
00107     for(int i=0; i<length(); i++)
00108         input1->gradientdata[i] += (gradientdata[i])*-2*(2*input2->valuedata[i]-1);
00109 }
00110 
00111 } // end of namespace PLearn
00112 
00113 
00114 /*
00115   Local Variables:
00116   mode:c++
00117   c-basic-offset:4
00118   c-file-style:"stroustrup"
00119   c-file-offsets:((innamespace . 0)(inline-open . 0))
00120   indent-tabs-mode:nil
00121   fill-column:79
00122   End:
00123 */
00124 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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