1 | #ifndef _theplu_yat_classifier_gaussian_kernel_function_ |
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2 | #define _theplu_yat_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) 2004, 2005, 2006, 2007, 2008 Jari Häkkinen, Peter Johansson |
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8 | Copyright (C) 2022 Peter Johansson |
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9 | |
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10 | This file is part of the yat library, http://dev.thep.lu.se/yat |
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11 | |
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12 | The yat library is free software; you can redistribute it and/or |
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13 | modify it under the terms of the GNU General Public License as |
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14 | published by the Free Software Foundation; either version 3 of the |
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15 | License, or (at your option) any later version. |
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16 | |
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17 | The yat library is distributed in the hope that it will be useful, |
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18 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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19 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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20 | General Public License for more details. |
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21 | |
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22 | You should have received a copy of the GNU General Public License |
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23 | along with yat. If not, see <http://www.gnu.org/licenses/>. |
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24 | */ |
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25 | |
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26 | #include "KernelFunction.h" |
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27 | |
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28 | #include <cmath> |
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29 | |
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30 | namespace theplu { |
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31 | namespace yat { |
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32 | namespace classifier { |
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33 | |
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34 | class DataLookup1D; |
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35 | |
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36 | /// |
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37 | /// @brief Class for Gaussian kernel calculations. |
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38 | /// |
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39 | |
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40 | class GaussianKernelFunction : public KernelFunction |
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41 | { |
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42 | |
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43 | public: |
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44 | /// |
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45 | /// Constructor taking the sigma_ , i.e. the width of the Gaussian,as |
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46 | /// input. Default is sigma_ = 1. |
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47 | /// |
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48 | GaussianKernelFunction(double = 1); |
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49 | |
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50 | /// |
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51 | ///Destructor |
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52 | /// |
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53 | virtual ~GaussianKernelFunction(void) {}; |
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54 | |
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55 | /// |
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56 | /// returning the scalar product of two vectors in feature space using the |
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57 | /// Gaussian kernel. @return \f$ exp(-(x - y)^{2}/\sigma^2) \f$ \n |
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58 | /// |
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59 | double operator()(const DataLookup1D& x, |
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60 | const DataLookup1D& y) const; |
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61 | |
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62 | /** |
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63 | \f$ \exp(-d^2/\sigma^2) \f$ where \f$ d^2 = \sum w_y(x_i-y_i)^2 |
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64 | / \sum w_y * N \f$ |
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65 | **/ |
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66 | double operator()(const DataLookup1D& x, |
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67 | const DataLookupWeighted1D& y) const; |
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68 | |
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69 | /** |
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70 | \f$ \exp(-d^2/\sigma^2) \f$ where \f$ d^2 = \sum w_xw_y(x_i-y_i)^2 |
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71 | / \sum w_xw_y * N \f$ |
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72 | **/ |
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73 | double operator()(const DataLookupWeighted1D& x, |
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74 | const DataLookupWeighted1D& y) const; |
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75 | |
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76 | private: |
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77 | double sigma2_; |
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78 | |
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79 | }; // class GaussianKernelFunction |
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80 | |
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81 | }}} // of namespace classifier, yat, and theplu |
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82 | |
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83 | #endif |
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