source: trunk/yat/classifier/GaussianKernelFunction.cc @ 1275

Last change on this file since 1275 was 1275, checked in by Jari Häkkinen, 13 years ago

Updating copyright statements.

  • 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 Jari Häkkinen, Peter Johansson
7
8  This file is part of the yat library, http://trac.thep.lu.se/yat
9
10  The yat library is free software; you can redistribute it and/or
11  modify it under the terms of the GNU General Public License as
12  published by the Free Software Foundation; either version 2 of the
13  License, or (at your option) any later version.
14
15  The yat library is distributed in the hope that it will be useful,
16  but WITHOUT ANY WARRANTY; without even the implied warranty of
17  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
18  General Public License for more details.
19
20  You should have received a copy of the GNU General Public License
21  along with this program; if not, write to the Free Software
22  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
23  02111-1307, USA.
24*/
25
26#include "GaussianKernelFunction.h"
27#include "KernelFunction.h"
28#include "DataLookup1D.h"
29#include "DataLookupWeighted1D.h"
30
31#include <cassert>
32#include <math.h>
33
34namespace theplu {
35namespace yat {
36namespace classifier { 
37
38  GaussianKernelFunction::GaussianKernelFunction(double sigma) 
39    : KernelFunction(), sigma2_(sigma*sigma)
40  {
41  }
42
43  double GaussianKernelFunction::operator()(const DataLookup1D& x,
44                                            const DataLookup1D& y) const
45  {
46    assert(x.size()==y.size());
47    double d2 = 0;
48    for (size_t i=0; i<x.size(); i++){
49      double d = x(i)-y(i);
50      d2 += d*d;
51    }
52    return exp(-d2/sigma2_); 
53  }
54
55
56  double GaussianKernelFunction::operator()(const DataLookup1D& x,
57                                            const DataLookupWeighted1D& y) const
58  {
59    assert(x.size()==y.size());
60    double d2 = 0;
61    double normalization_factor = 0;
62    for (size_t i=0; i<x.size(); i++) {
63      // ignoring Nan with accompanied weight zero
64      if (y.weight(i)){
65        d2 += y.weight(i) * (x(i)-y.data(i)) * (x(i)-y.data(i));
66        normalization_factor += y.weight(i);
67      }
68    }
69    // to make it coherent with no weight case
70    normalization_factor /= x.size(); 
71    return exp(d2/normalization_factor/sigma2_);
72  }
73
74
75  double GaussianKernelFunction::operator()(const DataLookupWeighted1D& x,
76                                            const DataLookupWeighted1D& y) const
77  {
78    assert(x.size()==y.size());
79    double d2 = 0;
80    double normalization_factor = 0;
81    for (size_t i=0; i<x.size(); i++) {
82      // ignoring Nan with accompanied weight zero
83      if (x.weight(i) && y.weight(i)){
84        d2 += x.weight(i) * y.weight(i) * (x.data(i)-y.data(i)) * 
85          (x.data(i)-y.data(i));
86        normalization_factor += x.weight(i) * y.weight(i);
87      }
88    }
89    // to make it coherent with no weight case
90    normalization_factor /= x.size(); 
91    return exp(d2/normalization_factor/sigma2_);
92  }
93
94
95}}} // of namespace svn, yat, and theplu
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