source: trunk/yat/regression/PolynomialWeighted.cc @ 729

Last change on this file since 729 was 729, checked in by Peter, 16 years ago

Fixes #159. Also removed some inlines in OneDimensionalWeighted? by adding source file. Refs #81

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.3 KB
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1// $Id: PolynomialWeighted.cc 729 2007-01-05 16:00:15Z peter $
2
3/*
4  Copyright (C) The authors contributing to this file.
5
6  This file is part of the yat library, http://lev.thep.lu.se/trac/yat
7
8  The yat library is free software; you can redistribute it and/or
9  modify it under the terms of the GNU General Public License as
10  published by the Free Software Foundation; either version 2 of the
11  License, or (at your option) any later version.
12
13  The yat library is distributed in the hope that it will be useful,
14  but WITHOUT ANY WARRANTY; without even the implied warranty of
15  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
16  General Public License for more details.
17
18  You should have received a copy of the GNU General Public License
19  along with this program; if not, write to the Free Software
20  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
21  02111-1307, USA.
22*/
23
24#include "PolynomialWeighted.h"
25#include "yat/utility/matrix.h"
26#include "yat/utility/vector.h"
27
28#include <cassert>
29
30namespace theplu {
31namespace yat {
32namespace regression {
33
34  PolynomialWeighted::PolynomialWeighted(size_t power)
35    : OneDimensionalWeighted(), mse_(0), power_(power)
36  {
37  }
38
39  PolynomialWeighted::~PolynomialWeighted(void)
40  {
41  }
42
43  void PolynomialWeighted::fit(const utility::vector& x,
44                               const utility::vector& y,
45                               const utility::vector& w)
46  {
47    assert(x.size()==y.size());
48    assert(y.size()==w.size());
49    utility::matrix X=utility::matrix(x.size(),power_+1,1);
50    for (size_t i=0; i<X.rows(); ++i)
51      for (u_int j=1; j<X.columns(); j++)
52        X(i,j)=X(i,j-1)*x(i);
53    md_.fit(X,y,w);
54  }
55
56  double PolynomialWeighted::s2(const double) const
57  {
58    return mse_;
59  }
60
61  double PolynomialWeighted::predict(const double x) const
62  {
63    utility::vector vec(power_+1,1);
64    for (size_t i=1; i<=power_; ++i)
65      vec(i) = vec(i-1)*x;
66    return md_.predict(vec);
67  }
68
69  double PolynomialWeighted::prediction_error(const double x, 
70                                              const double w) const
71  {
72    utility::vector vec(power_+1,1);
73    for (size_t i=1; i<=power_; ++i)
74      vec(i) = vec(i-1)*x;
75    return md_.prediction_error(vec, w);
76  }
77
78  double PolynomialWeighted::standard_error2(const double x) const
79  {
80    utility::vector vec(power_+1,1);
81    for (size_t i=1; i<=power_; ++i)
82      vec(i) = vec(i-1)*x;
83    return md_.standard_error(vec);
84  }
85
86}}} // of namespaces regression, yat, and theplu
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