PLearn 0.1
GaussianKernel.h
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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: GaussianKernel.h 3994 2005-08-25 13:35:03Z chapados $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #ifndef GaussianKernel_INC
00044 #define GaussianKernel_INC
00045 
00046 #include "Kernel.h"
00047 
00048 namespace PLearn {
00049 using namespace std;
00050 
00051 
00052 
00054 class GaussianKernel: public Kernel
00055 {
00056 
00057 private:
00058 
00059     typedef Kernel inherited;
00060                 
00061 public:
00062 
00064     bool scale_by_sigma;
00065     real sigma;
00066 
00067 protected:
00068 
00069     real minus_one_over_sigmasquare;  
00070     real sigmasquare_over_two;        
00071 
00072     Vec squarednorms; 
00073          
00074 public:
00075 
00077     GaussianKernel();
00078   
00080     GaussianKernel(real the_sigma);
00081 
00082     PLEARN_DECLARE_OBJECT(GaussianKernel);
00083 
00084     virtual void build();
00085 
00086     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00087 
00089     virtual void setDataForKernelMatrix(VMat the_data);
00090   
00092     virtual void addDataForKernelMatrix(const Vec& newRow);
00093 
00094     virtual real evaluate(const Vec& x1, const Vec& x2) const; 
00095     virtual real evaluate_i_j(int i, int j) const; 
00096     virtual real evaluate_i_x(int i, const Vec& x, real squared_norm_of_x=-1) const; 
00097     virtual real evaluate_x_i(const Vec& x, int i, real squared_norm_of_x=-1) const; 
00098 
00099     virtual void setParameters(Vec paramvec);
00100 
00101 protected:
00102     static void declareOptions(OptionList& ol);  
00103 
00110     inline bool isUnsafe(real sqn_1, real sqn_2) const;
00111 
00112 private:
00113 
00114     inline real evaluateFromSquaredNormOfDifference(real sqnorm_of_diff) const;
00115 
00116     inline real evaluateFromDotAndSquaredNorm(real sqnorm_x1, real dot_x1_x2, real sqnorm_x2) const;
00117 
00118     void build_();
00119 };
00120 
00121 DECLARE_OBJECT_PTR(GaussianKernel);
00122 
00123 } // end of namespace PLearn
00124 
00125 #endif
00126 
00127 
00128 /*
00129   Local Variables:
00130   mode:c++
00131   c-basic-offset:4
00132   c-file-style:"stroustrup"
00133   c-file-offsets:((innamespace . 0)(inline-open . 0))
00134   indent-tabs-mode:nil
00135   fill-column:79
00136   End:
00137 */
00138 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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