source: trunk/yat/regression/Naive.h @ 702

Last change on this file since 702 was 702, checked in by Peter, 15 years ago

Refs #81 moved mse_ to inherited classes and made mse() pure virtual because mse is calculated different for different classes and therefore this design is more logic. Fixed docs and other things...

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 2.1 KB
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1#ifndef _theplu_yat_regression_naive_
2#define _theplu_yat_regression_naive_
3
4// $Id: Naive.h 702 2006-10-26 14:04:35Z peter $
5
6/*
7  Copyright (C) The authors contributing to this file.
8
9  This file is part of the yat library, http://lev.thep.lu.se/trac/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 2 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 this program; if not, write to the Free Software
23  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
24  02111-1307, USA.
25*/
26
27#include "OneDimensional.h"
28
29#include <iostream>
30#include <utility>
31
32namespace theplu {
33namespace yat {
34  namespace utility {
35    class vector;
36  }
37namespace regression {
38
39  ///
40  /// @bief naive fitting.
41  ///
42  /// @todo document
43  ///
44  class Naive : public OneDimensional
45  {
46 
47  public:
48    ///
49    /// Default Constructor.
50    ///
51    inline Naive(void) : OneDimensional(), mse_(0.0) {}
52
53    ///
54    /// Copy Constructor. (not implemented)
55    ///
56    Naive(const Naive&);
57
58    ///
59    /// Destructor
60    ///
61    virtual ~Naive(void) {};
62         
63    ///
64    /// This function computes the best-fit for the naive model \f$ y
65    /// = m \f$ from vectors \a x and \a y, by minimizing \f$
66    /// \sum{(y_i-m)^2} \f$. This function is the same as using the
67    /// weighted version with unity weights.
68    ///
69    void fit(const utility::vector& x, const utility::vector& y);
70
71    ///
72    /// @brief Mean Squared Error
73    ///
74    inline double mse(void) const { return mse_; }
75
76    ///
77    /// Function predicting value using the naive model.
78    ///
79    double predict(const double x) const;
80 
81    ///
82    /// @return standard error
83    ///
84    double standard_error(const double x) const;
85
86  private:
87    double mse_;
88  };
89
90}}} // of namespaces regression, yat, and theplu
91
92#endif
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