1 | #ifndef _theplu_classifier_gaussian_kernel_function_ |
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2 | #define _theplu_classifier_gaussian_kernel_function_ |
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3 | |
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4 | // $Id$ |
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5 | |
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6 | /* |
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7 | Copyright (C) The authors contributing to this file. |
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8 | |
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9 | This file is part of the yat library, http://lev.thep.lu.se/trac/yat |
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10 | |
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11 | The yat library is free software; you can redistribute it and/or |
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12 | modify it under the terms of the GNU General Public License as |
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13 | published by the Free Software Foundation; either version 2 of the |
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14 | License, or (at your option) any later version. |
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15 | |
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16 | The yat library is distributed in the hope that it will be useful, |
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17 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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18 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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19 | General Public License for more details. |
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20 | |
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21 | You should have received a copy of the GNU General Public License |
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22 | along with this program; if not, write to the Free Software |
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23 | Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA |
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24 | 02111-1307, USA. |
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25 | */ |
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26 | |
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27 | #include "yat/classifier/KernelFunction.h" |
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28 | #include "yat/classifier/DataLookup1D.h" |
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29 | |
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30 | #include <cmath> |
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31 | |
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32 | namespace theplu { |
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33 | namespace classifier { |
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34 | |
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35 | /// |
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36 | /// Class for Gaussian kernel calculations. |
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37 | /// |
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38 | |
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39 | class GaussianKernelFunction : public KernelFunction |
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40 | { |
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41 | |
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42 | public: |
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43 | /// |
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44 | /// Constructor taking the sigma_ , i.e. the width of the Gaussian,as |
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45 | /// input. Default is sigma_ = 1. |
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46 | /// |
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47 | GaussianKernelFunction(double = 1); |
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48 | |
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49 | /// |
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50 | ///Destructor |
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51 | /// |
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52 | virtual ~GaussianKernelFunction(void) {}; |
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53 | |
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54 | /// |
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55 | /// returning the scalar product of two vectors in feature space using the |
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56 | /// Gaussian kernel. @return \f$ exp(-(x - y)^{2}/\sigma^2) \f$ \n |
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57 | /// |
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58 | double operator()(const DataLookup1D& x, |
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59 | const DataLookup1D& y) const; |
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60 | |
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61 | /** |
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62 | \f$ \exp(-d^2/\sigma^2) \f$ where \f$ d^2 = \sum w_y(x_i-y_i)^2 |
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63 | / \sum w_y * N \f$ |
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64 | **/ |
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65 | double operator()(const DataLookup1D& x, |
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66 | const DataLookupWeighted1D& y) const; |
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67 | |
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68 | /** |
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69 | \f$ \exp(-d^2/\sigma^2) \f$ where \f$ d^2 = \sum w_xw_y(x_i-y_i)^2 |
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70 | / \sum w_xw_y * N \f$ |
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71 | **/ |
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72 | double operator()(const DataLookupWeighted1D& x, |
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73 | const DataLookupWeighted1D& y) const; |
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74 | |
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75 | private: |
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76 | double sigma2_; |
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77 | |
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78 | }; // class GaussianKernelFunction |
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79 | |
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80 | }} // of namespace classifier and namespace theplu |
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81 | |
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82 | #endif |
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