source: trunk/lib/statistics/tScore.cc @ 529

Last change on this file since 529 was 529, checked in by Markus Ringnér, 16 years ago

Added score for signal-to-noise ratio (Golub score). Fixed documentation. Improved weighted version of tScore

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  • Property svn:keywords set to Author Date Id Revision
File size: 1.9 KB
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1// $Id: tScore.cc 529 2006-03-01 14:03:27Z markus $
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.binary(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    for(size_t i=0; i<target.size(); i++){
53      if (target.binary(i))
54        positive.add(value(i),weight(i));
55      else
56        negative.add(value(i),weight(i));
57    }
58    double diff = positive.mean() - negative.mean();
59    double s2=(positive.sum_xx_centered()+negative.sum_xx_centered())/
60      (positive.n()+negative.n()-2);
61    t_=diff/sqrt(s2*(1.0/positive.sum_w()+1.0/negative.sum_w()));   
62    if (t_<0 && absolute_)
63      t_=-t_;
64
65    if(positive.n()==0 || negative.n()==0 ||
66       positive.sum_w()==0 || positive.sum_w()==0)
67      t_=0;
68    dof_=target.size()-2;
69     
70    return t_;
71  }
72
73  double tScore::p_value(void) const
74  {
75    double p = gsl_cdf_tdist_Q(t_, dof_);
76    return (dof_ > 0 && !weighted_) ? p : 1;
77  }
78
79
80
81}} // of namespace statistics and namespace theplu
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