source: trunk/lib/statistics/tScore.cc @ 509

Last change on this file since 509 was 509, checked in by Peter, 16 years ago

added test for target
redesign crossSplitter
added two class function in Target

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 1.8 KB
Line 
1// $Id: tScore.cc 509 2006-02-18 13:47:32Z peter $
2
3// System includes
4#include <cassert>
5#include <cmath>
6
7// Thep C++ Tools
8#include <c++_tools/statistics/tScore.h>
9#include <c++_tools/statistics/Averager.h>
10#include <c++_tools/statistics/AveragerWeighted.h>
11#include <c++_tools/classifier/Target.h>
12
13namespace theplu {
14namespace statistics { 
15
16  tScore::tScore(bool b) 
17    : Score(b),  t_(0)
18  {
19  }
20
21  double tScore::score(const classifier::Target& target, 
22                       const gslapi::vector& value)
23  {
24    weighted_=false;
25    statistics::Averager positive;
26    statistics::Averager negative;
27    dof_=target.size()-2;
28    for(size_t i=0; i<target.size(); i++){
29      if (target.one(i))
30        positive.add(value(i));
31      else
32        negative.add(value(i));
33    }
34    double diff = positive.mean() - negative.mean();
35    double s2=(positive.sum_xx_centered()+negative.sum_xx_centered())/
36      (positive.n()+negative.n()-2);
37    t_=diff/sqrt(s2*(1.0/positive.n()+1.0/negative.n()));
38    if (t_<0 && absolute_)
39      t_=-t_;
40     
41    return t_;
42  }
43
44  double tScore::score(const classifier::Target& target, 
45                       const gslapi::vector& value,
46                       const gslapi::vector& weight)
47  {
48    weighted_=true;
49
50    statistics::AveragerWeighted positive;
51    statistics::AveragerWeighted negative;
52    dof_=target.size()-2;
53    for(size_t i=0; i<target.size(); i++){
54      if (target.one(i))
55        positive.add(value(i),weight(i));
56      else
57        negative.add(value(i),weight(i));
58    }
59    double diff = positive.mean() - negative.mean();
60    double s2=(positive.sum_xx_centered()+negative.sum_xx_centered())/
61      (positive.n()+negative.n()-2);
62    t_=diff/sqrt(s2*(1.0/positive.sum_w()+1.0/negative.sum_w()));
63    assert(0);
64    if (t_<0 && absolute_)
65      t_=-t_;
66     
67    return t_;
68  }
69
70  double tScore::p_value(void) const
71  {
72    double p = gsl_cdf_tdist_Q(t_, dof_);
73    return (dof_ > 0 && !weighted_) ? p : 1;
74  }
75
76
77
78}} // of namespace statistics and namespace theplu
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