CLinearHMM Class Reference

Inheritance diagram for CLinearHMM:

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List of all members.

Detailed Description

class LinearHMM

Definition at line 20 of file LinearHMM.h.


Public Member Functions

 CLinearHMM (CStringFeatures< WORD > *f)
 CLinearHMM (INT p_num_features, INT p_num_symbols)
 ~CLinearHMM ()
bool train ()
bool train (const INT *indizes, INT num_indizes, DREAL pseudo_count)
DREAL get_log_likelihood_example (WORD *vector, INT len)
DREAL get_likelihood_example (WORD *vector, INT len)
virtual DREAL get_log_likelihood_example (INT num_example)
virtual DREAL get_log_derivative (INT num_param, INT num_example)
virtual DREAL get_log_derivative_obsolete (WORD obs, INT pos)
virtual DREAL get_derivative_obsolete (WORD *vector, INT len, INT pos)
virtual INT get_sequence_length ()
virtual INT get_num_symbols ()
virtual INT get_num_model_parameters ()
virtual DREAL get_positional_log_parameter (WORD obs, INT position)
virtual DREAL get_log_model_parameter (INT num_param)
virtual void get_log_transition_probs (DREAL **dst, INT *num)
virtual bool set_log_transition_probs (const DREAL *src, INT num)
virtual void get_transition_probs (DREAL **dst, INT *num)
virtual bool set_transition_probs (const DREAL *src, 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

INT sequence_length
INT num_symbols
INT num_params
DREAL * transition_probs
DREAL * log_transition_probs
CFeatures * features
DREAL pseudo_count

Constructor & Destructor Documentation

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

constructor

Parameters:
f features to use

Definition at line 17 of file LinearHMM.cpp.

CLinearHMM::CLinearHMM ( INT  p_num_features,
INT  p_num_symbols 
)

constructor

Parameters:
p_num_features number of features
p_num_symbols number of symbols in features

Definition at line 26 of file LinearHMM.cpp.

CLinearHMM::~CLinearHMM (  ) 

Definition at line 34 of file LinearHMM.cpp.

Member Function Documentation

bool CLinearHMM::train (  )  [virtual]

train distribution

Returns:
if training was successful

Implements CDistribution.

Definition at line 40 of file LinearHMM.cpp.

bool CLinearHMM::train ( const INT *  indizes,
INT  num_indizes,
DREAL  pseudo_count 
)

alternative train distribution

Parameters:
indizes indices
num_indizes number of indices
pseudo_count pseudo count
Returns:
if training was successful

Definition at line 87 of file LinearHMM.cpp.

DREAL CLinearHMM::get_log_likelihood_example ( WORD *  vector,
INT  len 
)

get logarithm of one example's likelihood

Parameters:
vector the example
len length of vector
Returns:
logarithm of likelihood

Definition at line 137 of file LinearHMM.cpp.

DREAL CLinearHMM::get_likelihood_example ( WORD *  vector,
INT  len 
)

get one example's likelihood

Parameters:
vector the example
len length of vector
Returns:
likelihood

Definition at line 159 of file LinearHMM.cpp.

DREAL CLinearHMM::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 147 of file LinearHMM.cpp.

DREAL CLinearHMM::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

Implements CDistribution.

Definition at line 169 of file LinearHMM.cpp.

virtual DREAL CLinearHMM::get_log_derivative_obsolete ( WORD  obs,
INT  pos 
) [virtual]

obsolete get logarithm of one example's derivative's likelihood

Parameters:
obs observation
pos position

Definition at line 89 of file LinearHMM.h.

virtual DREAL CLinearHMM::get_derivative_obsolete ( WORD *  vector,
INT  len,
INT  pos 
) [virtual]

obsolete get one example's derivative

Parameters:
vector vector
len length
pos position

Definition at line 100 of file LinearHMM.h.

virtual INT CLinearHMM::get_sequence_length (  )  [virtual]

get sequence length of each example

Returns:
sequence length of each example

Definition at line 110 of file LinearHMM.h.

virtual INT CLinearHMM::get_num_symbols (  )  [virtual]

get number of symbols in examples

Returns:
number of symbols in examples

Definition at line 116 of file LinearHMM.h.

virtual INT CLinearHMM::get_num_model_parameters (  )  [virtual]

get number of model parameters

Returns:
number of model parameters

Implements CDistribution.

Definition at line 122 of file LinearHMM.h.

virtual DREAL CLinearHMM::get_positional_log_parameter ( WORD  obs,
INT  position 
) [virtual]

get positional log parameter

Parameters:
obs observation
position position
Returns:
positional log parameter

Definition at line 130 of file LinearHMM.h.

virtual DREAL CLinearHMM::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 140 of file LinearHMM.h.

void CLinearHMM::get_log_transition_probs ( DREAL **  dst,
INT *  num 
) [virtual]

get logarithm of all transition probs

Parameters:
dst where logarithm of transition probs will be stored
num where number of logarithm of transition probs will be stored

Definition at line 214 of file LinearHMM.cpp.

bool CLinearHMM::set_log_transition_probs ( const DREAL *  src,
INT  num 
) [virtual]

set logarithm of all transition probs

Parameters:
src new logarithms of transition probs
num number of logarithms of transition probs
Returns:
if setting was succesful

Definition at line 224 of file LinearHMM.cpp.

void CLinearHMM::get_transition_probs ( DREAL **  dst,
INT *  num 
) [virtual]

get all transition probs

Parameters:
dst where transition probs will be stored
num where number of transition probs will be stored

Definition at line 184 of file LinearHMM.cpp.

bool CLinearHMM::set_transition_probs ( const DREAL *  src,
INT  num 
) [virtual]

set all transition probs

Parameters:
src new transition probs
num number of transition probs
Returns:
if setting was succesful

Definition at line 194 of file LinearHMM.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

INT CLinearHMM::sequence_length [protected]

examples' sequence length

Definition at line 182 of file LinearHMM.h.

INT CLinearHMM::num_symbols [protected]

number of symbols in examples

Definition at line 184 of file LinearHMM.h.

INT CLinearHMM::num_params [protected]

number of parameters

Definition at line 186 of file LinearHMM.h.

DREAL* CLinearHMM::transition_probs [protected]

transition probs

Definition at line 188 of file LinearHMM.h.

DREAL* CLinearHMM::log_transition_probs [protected]

logarithm of transition probs

Definition at line 190 of file LinearHMM.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