source: trunk/yat/classifier/GaussianKernelFunction.h

Last change on this file was 4207, checked in by Peter, 5 weeks ago

update copyright statements

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1#ifndef _theplu_yat_classifier_gaussian_kernel_function_
2#define _theplu_yat_classifier_gaussian_kernel_function_
3
4// $Id$
5
6/*
7  Copyright (C) 2004, 2005, 2006, 2007, 2008 Jari Häkkinen, Peter Johansson
8  Copyright (C) 2022 Peter Johansson
9
10  This file is part of the yat library, http://dev.thep.lu.se/yat
11
12  The yat library is free software; you can redistribute it and/or
13  modify it under the terms of the GNU General Public License as
14  published by the Free Software Foundation; either version 3 of the
15  License, or (at your option) any later version.
16
17  The yat library is distributed in the hope that it will be useful,
18  but WITHOUT ANY WARRANTY; without even the implied warranty of
19  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
20  General Public License for more details.
21
22  You should have received a copy of the GNU General Public License
23  along with yat. If not, see <http://www.gnu.org/licenses/>.
24*/
25
26#include "KernelFunction.h"
27
28#include <cmath>
29
30namespace theplu {
31namespace yat {
32namespace classifier {
33
34  class DataLookup1D;
35
36  ///
37  /// @brief Class for Gaussian kernel calculations.
38  ///
39
40  class GaussianKernelFunction : public KernelFunction
41  {
42
43  public:
44    ///
45    /// Constructor taking the sigma_ , i.e. the width of the Gaussian,as
46    /// input. Default is sigma_ = 1.
47    ///
48    GaussianKernelFunction(double = 1);
49
50    ///
51    ///Destructor
52    ///
53       virtual ~GaussianKernelFunction(void) {};
54
55    ///
56    /// returning the scalar product of two vectors in feature space using the
57    /// Gaussian kernel. @return \f$ exp(-(x - y)^{2}/\sigma^2) \f$ \n
58    ///
59    double operator()(const DataLookup1D& x,
60                      const DataLookup1D& y) const;
61
62    /**
63       \f$ \exp(-d^2/\sigma^2) \f$ where \f$ d^2 = \sum w_y(x_i-y_i)^2
64       / \sum w_y * N \f$
65     **/
66    double operator()(const DataLookup1D& x,
67                      const DataLookupWeighted1D& y) const;
68
69    /**
70       \f$ \exp(-d^2/\sigma^2) \f$ where \f$ d^2 = \sum w_xw_y(x_i-y_i)^2
71       / \sum w_xw_y * N \f$
72     **/
73    double operator()(const DataLookupWeighted1D& x,
74                      const DataLookupWeighted1D& y) const;
75
76  private:
77    double sigma2_;
78
79  }; // class GaussianKernelFunction
80
81}}} // of namespace classifier, yat, and theplu
82
83#endif
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