source: trunk/yat/classifier/GaussianKernelFunction.cc

Last change on this file was 2919, checked in by Peter, 9 years ago

update copyright years

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date ID
File size: 2.7 KB
Line 
1// $Id$
2
3/*
4  Copyright (C) 2004 Jari Häkkinen, Peter Johansson
5  Copyright (C) 2005 Peter Johansson
6  Copyright (C) 2006, 2007, 2008 Jari Häkkinen, Peter Johansson
7  Copyright (C) 2012 Peter Johansson
8
9  This file is part of the yat library, http://dev.thep.lu.se/yat
10
11  The yat library is free software; you can redistribute it and/or
12  modify it under the terms of the GNU General Public License as
13  published by the Free Software Foundation; either version 3 of the
14  License, or (at your option) any later version.
15
16  The yat library is distributed in the hope that it will be useful,
17  but WITHOUT ANY WARRANTY; without even the implied warranty of
18  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
19  General Public License for more details.
20
21  You should have received a copy of the GNU General Public License
22  along with yat. If not, see <http://www.gnu.org/licenses/>.
23*/
24
25#include <config.h>
26
27#include "GaussianKernelFunction.h"
28#include "KernelFunction.h"
29#include "DataLookup1D.h"
30#include "DataLookupWeighted1D.h"
31
32#include <cassert>
33#include <math.h>
34
35namespace theplu {
36namespace yat {
37namespace classifier { 
38
39  GaussianKernelFunction::GaussianKernelFunction(double sigma) 
40    : KernelFunction(), sigma2_(sigma*sigma)
41  {
42  }
43
44  double GaussianKernelFunction::operator()(const DataLookup1D& x,
45                                            const DataLookup1D& y) const
46  {
47    assert(x.size()==y.size());
48    double d2 = 0;
49    for (size_t i=0; i<x.size(); i++){
50      double d = x(i)-y(i);
51      d2 += d*d;
52    }
53    return exp(-d2/sigma2_); 
54  }
55
56
57  double GaussianKernelFunction::operator()(const DataLookup1D& x,
58                                            const DataLookupWeighted1D& y) const
59  {
60    assert(x.size()==y.size());
61    double d2 = 0;
62    double normalization_factor = 0;
63    for (size_t i=0; i<x.size(); i++) {
64      // ignoring Nan with accompanied weight zero
65      if (y.weight(i)){
66        d2 += y.weight(i) * (x(i)-y.data(i)) * (x(i)-y.data(i));
67        normalization_factor += y.weight(i);
68      }
69    }
70    // to make it coherent with no weight case
71    normalization_factor /= x.size(); 
72    return exp(d2/normalization_factor/sigma2_);
73  }
74
75
76  double GaussianKernelFunction::operator()(const DataLookupWeighted1D& x,
77                                            const DataLookupWeighted1D& y) const
78  {
79    assert(x.size()==y.size());
80    double d2 = 0;
81    double normalization_factor = 0;
82    for (size_t i=0; i<x.size(); i++) {
83      // ignoring Nan with accompanied weight zero
84      if (x.weight(i) && y.weight(i)){
85        d2 += x.weight(i) * y.weight(i) * (x.data(i)-y.data(i)) * 
86          (x.data(i)-y.data(i));
87        normalization_factor += x.weight(i) * y.weight(i);
88      }
89    }
90    // to make it coherent with no weight case
91    normalization_factor /= x.size(); 
92    return exp(d2/normalization_factor/sigma2_);
93  }
94
95
96}}} // of namespace svn, yat, and theplu
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