yat  0.13.2pre
Public Member Functions | Protected Attributes | List of all members
theplu::yat::statistics::SNRScore Class Reference

Class for score based on signal-to-noise ratio (SNRScore). More...

#include <yat/statistics/SNRScore.h>

Inheritance diagram for theplu::yat::statistics::SNRScore:
theplu::yat::statistics::Score

Public Member Functions

 SNRScore (bool absolute=true)
 Default Constructor.
 
virtual ~SNRScore (void)
 The destructor.
 
double score (const classifier::Target &target, const utility::VectorBase &value) const
 
double score (const classifier::Target &target, const classifier::DataLookupWeighted1D &value) const
 
double score (const classifier::Target &target, const utility::VectorBase &value, const utility::VectorBase &weight) const
 
void absolute (bool absolute)
 Function changing mode of Score.
 
virtual double score (const classifier::Target &target, const classifier::DataLookup1D &value) const
 
double score (const classifier::Target &target, const classifier::DataLookup1D &value, const classifier::DataLookup1D &weight) const
 

Protected Attributes

bool absolute_
 

Detailed Description

Class for score based on signal-to-noise ratio (SNRScore).

Also sometimes referred to as Golub score. The score is the ratio between difference in mean and the sum of standard deviations for two groups: $ \frac{ m_x-m_y}{ s_x + s_y} $ where $ s $ is standard deviation.

Member Function Documentation

double theplu::yat::statistics::SNRScore::score ( const classifier::Target target,
const utility::VectorBase value 
) const
virtual

SNRScore is defined as $ \frac{m_x-m_y}{s_x+s_y} $ where $ m $ and $ s $ are mean and standard deviation, respectively.

See Also
Averager
Returns
SNRScore score. If absolute=true absolute value of SNRScore is returned

Implements theplu::yat::statistics::Score.

virtual double theplu::yat::statistics::Score::score ( const classifier::Target target,
const classifier::DataLookup1D value 
) const
virtualinherited

Function calculating the score. In absolute mode, also the score using negated class labels is calculated, and the largest of the two scores are calculated.

value is copied to a utility::vector and that operator is called. If speed is important this operator should be implemented in inherited class to avoid copying.

Returns
score
double theplu::yat::statistics::SNRScore::score ( const classifier::Target target,
const classifier::DataLookupWeighted1D value 
) const
virtual

SNRScore is defined as $ \frac{m_x-m_y}{s_x+s_y} $ where $ m $ and $ s $ are weighted versions of mean and standard deviation, respectively.

See Also
AveragerWeighted
Returns
SNRScore score. If absolute=true absolute value of SNRScore is returned

Reimplemented from theplu::yat::statistics::Score.

double theplu::yat::statistics::SNRScore::score ( const classifier::Target target,
const utility::VectorBase value,
const utility::VectorBase weight 
) const
virtual

SNRScore is defined as $ \frac{m_x-m_y}{s_x+s_y} $ where $ m $ and $ s $ are weighted versions of mean and standard deviation, respectively.

See Also
AveragerWeighted
Returns
SNRScore score. If absolute=true absolute value of SNRScore is returned

Implements theplu::yat::statistics::Score.

double theplu::yat::statistics::Score::score ( const classifier::Target target,
const classifier::DataLookup1D value,
const classifier::DataLookup1D weight 
) const
inherited

Function calculating the weighted version of score. In absolute mode, also the score using negated class labels is calculated, and the largest of the two scores are calculated. Absolute mode should be used when two-tailed test is wanted.

value and weight are copied to utility::vector and the corresponding operator is called. If speed is important this operator should be implemented in inherited class to avoid copying.

Member Data Documentation

bool theplu::yat::statistics::Score::absolute_
protectedinherited

true if method is absolute, which means if score is below expected value (by chance) E, score returns E-score+E instead.


The documentation for this class was generated from the following file:

Generated on Wed Jan 4 2017 02:23:08 for yat by  doxygen 1.8.5