CGHMM Class Reference

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Detailed Description

class GHMM - this class is non-functional and was meant to implement a Generalize Hidden Markov Model (aka Semi Hidden Markov HMM).

Definition at line 22 of file GHMM.h.

Inheritance diagram for CGHMM:

List of all members.

Public Member Functions
	CGHMM ()
virtual	~CGHMM ()
virtual bool	train (CFeatures *data=NULL)
virtual int32_t	get_num_model_parameters ()
virtual float64_t	get_log_model_parameter (int32_t param_num)
virtual float64_t	get_log_derivative (int32_t param_num, int32_t num_example)
virtual float64_t	get_log_likelihood_example (int32_t num_example)
virtual const char *	get_name () const

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Constructor & Destructor Documentation

CGHMM

(

)

default constructor

Definition at line 15 of file GHMM.cpp.

~CGHMM

(

)

[virtual]

Definition at line 20 of file GHMM.cpp.

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Member Function Documentation

float64_t get_log_derivative	(	int32_t	param_num,
		int32_t	num_example
	)		[virtual]

get logarithm of one example's derivative's likelihood

Parameters:

param_num	which example's param
num_example	which example

Returns:

logarithm of example's derivative's likelihood

Implements CDistribution.

Definition at line 39 of file GHMM.cpp.

float64_t get_log_likelihood_example

(

int32_t

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 44 of file GHMM.cpp.

float64_t get_log_model_parameter

(

int32_t

param_num

)

[virtual]

get logarithm of given model parameter

Parameters:

param_num

which param

Returns:

logarithm of given model parameter

Implements CDistribution.

Definition at line 34 of file GHMM.cpp.

virtual const char* get_name

(

)

const [virtual]

Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.

Returns:

name of the SGSerializable

Implements CSGObject.

Definition at line 72 of file GHMM.h.

int32_t get_num_model_parameters

(

)

[virtual]

get number of model parameters

Returns:

number of model parameters

Implements CDistribution.

Definition at line 29 of file GHMM.cpp.

bool train

(

CFeatures *

data = NULL

)

[virtual]

learn distribution

Parameters:

data	training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data)

Returns:

whether training was successful

Implements CDistribution.

Definition at line 24 of file GHMM.cpp.

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

• GHMM.h
• GHMM.cpp