CHistogram Class Reference

Inheritance diagram for CHistogram:

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List of all members.

Detailed Description

class Histogram

Definition at line 18 of file Histogram.h.


Public Member Functions

 CHistogram ()
 CHistogram (CStringFeatures< WORD > *f)
 ~CHistogram ()
virtual bool train ()
virtual INT get_num_model_parameters ()
virtual DREAL get_log_model_parameter (INT num_param)
virtual DREAL get_log_derivative (INT num_param, INT num_example)
virtual DREAL get_log_likelihood_example (INT num_example)
virtual bool set_histogram (DREAL *src, INT num)
virtual void get_histogram (DREAL **dst, INT *num)
virtual INT get_num_relevant_model_parameters ()
virtual DREAL get_log_likelihood_sample ()
virtual void get_log_likelihood (DREAL **dst, INT *num)
virtual DREAL get_model_parameter (INT num_param)
virtual DREAL get_derivative (INT num_param, INT num_example)
virtual DREAL get_likelihood_example (INT num_example)
virtual void set_features (CFeatures *f)
virtual CFeatures * get_features ()
virtual void set_pseudo_count (DREAL pseudo)
virtual DREAL get_pseudo_count ()

Static Public Attributes

static CParallel parallel
static CIO io
static CVersion version

Protected Attributes

DREAL * hist
CFeatures * features
DREAL pseudo_count

Constructor & Destructor Documentation

CHistogram::CHistogram (  ) 

default constructor

Definition at line 19 of file Histogram.cpp.

CHistogram::CHistogram ( CStringFeatures< WORD > *  f  ) 

constructor

Parameters:
f histogram's features

Definition at line 25 of file Histogram.cpp.

CHistogram::~CHistogram (  ) 

Definition at line 32 of file Histogram.cpp.

Member Function Documentation

bool CHistogram::train (  )  [virtual]

train histogram

Returns:
if training was successful

Implements CDistribution.

Definition at line 37 of file Histogram.cpp.

virtual INT CHistogram::get_num_model_parameters (  )  [virtual]

get number of model parameters

Returns:
number of model parameters

Implements CDistribution.

Definition at line 41 of file Histogram.h.

DREAL CHistogram::get_log_model_parameter ( INT  num_param  )  [virtual]

get logarithm of given model parameter

Parameters:
num_param which param
Returns:
logarithm of given model parameter

Implements CDistribution.

Definition at line 117 of file Histogram.cpp.

DREAL CHistogram::get_log_derivative ( INT  num_param,
INT  num_example 
) [virtual]

get logarithm of one example's derivative's likelihood

Parameters:
num_param which example's param
num_example which example
Returns:
logarithm of example's derivative's likelihood

Implements CDistribution.

Definition at line 83 of file Histogram.cpp.

DREAL CHistogram::get_log_likelihood_example ( INT  num_example  )  [virtual]

get logarithm of one example's likelihood

Parameters:
num_example which example
Returns:
logarithm of example's likelihood

Implements CDistribution.

Definition at line 66 of file Histogram.cpp.

bool CHistogram::set_histogram ( DREAL *  src,
INT  num 
) [virtual]

set histogram

Parameters:
src new histogram
num number of values in histogram

Definition at line 122 of file Histogram.cpp.

void CHistogram::get_histogram ( DREAL **  dst,
INT *  num 
) [virtual]

get histogram

Parameters:
dst where the histogram will be stored
num where number of values in histogram will be stored

Definition at line 135 of file Histogram.cpp.

INT CDistribution::get_num_relevant_model_parameters (  )  [virtual, inherited]

get number of parameters in model that are relevant, i.e. > ALMOST_NEG_INFTY

Returns:
number of relevant model parameters

Definition at line 48 of file Distribution.cpp.

DREAL CDistribution::get_log_likelihood_sample (  )  [virtual, inherited]

compute log likelihood for whole sample

Returns:
log likelihood for whole sample

Definition at line 24 of file Distribution.cpp.

void CDistribution::get_log_likelihood ( DREAL **  dst,
INT *  num 
) [virtual, inherited]

compute log likelihood for each example

Parameters:
dst where likelihood will be stored
num where number of likelihoods will be stored

Definition at line 35 of file Distribution.cpp.

virtual DREAL CDistribution::get_model_parameter ( INT  num_param  )  [virtual, inherited]

get model parameter

Parameters:
num_param which param
Returns:
model parameter

Definition at line 94 of file Distribution.h.

virtual DREAL CDistribution::get_derivative ( INT  num_param,
INT  num_example 
) [virtual, inherited]

get derivative of likelihood function

Parameters:
num_param which param
num_example which example
Returns:
derivative of likelihood function

Definition at line 105 of file Distribution.h.

virtual DREAL CDistribution::get_likelihood_example ( INT  num_example  )  [virtual, inherited]

compute likelihood for example

Parameters:
num_example which example
Returns:
likelihood for example

Definition at line 115 of file Distribution.h.

virtual void CDistribution::set_features ( CFeatures *  f  )  [virtual, inherited]

set feature vectors

Parameters:
f new feature vectors

Definition at line 124 of file Distribution.h.

virtual CFeatures* CDistribution::get_features (  )  [virtual, inherited]

get feature vectors

Returns:
feature vectors

Definition at line 130 of file Distribution.h.

virtual void CDistribution::set_pseudo_count ( DREAL  pseudo  )  [virtual, inherited]

set pseudo count

Parameters:
pseudo new pseudo count

Definition at line 136 of file Distribution.h.

virtual DREAL CDistribution::get_pseudo_count (  )  [virtual, inherited]

get pseudo count

Returns:
pseudo count

Definition at line 142 of file Distribution.h.

Member Data Documentation

DREAL* CHistogram::hist [protected]

histogram

Definition at line 82 of file Histogram.h.

CFeatures* CDistribution::features [protected, inherited]

feature vectors

Definition at line 146 of file Distribution.h.

DREAL CDistribution::pseudo_count [protected, inherited]

pseudo count

Definition at line 148 of file Distribution.h.

CParallel CSGObject::parallel [static, inherited]

Definition at line 105 of file SGObject.h.

CIO CSGObject::io [static, inherited]

Definition at line 106 of file SGObject.h.

CVersion CSGObject::version [static, inherited]

Definition at line 107 of file SGObject.h.

The documentation for this class was generated from the following files:
SHOGUN Machine Learning Toolbox - Documentation