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CLinearHMM Class Reference

Detailed Description

The class LinearHMM is for learning Higher Order Markov chains.

While learning the parameters \({\bf \theta}\) in

\begin{eqnarray*} P({\bf x}|{\bf \theta}^\pm)&=&P(x_1, \ldots, x_N|{\bf \theta}^\pm)\\ &=&P(x_1,\ldots,x_{d}|{\bf \theta}^\pm)\prod_{i=d+1}^N P(x_i|x_{i-1},\ldots,x_{i-d},{\bf \theta}^\pm) \end{eqnarray*}

are determined.

A more detailed description can be found in

Durbin et.al, Biological Sequence Analysis -Probabilistic Models of Proteins and Nucleic Acids, 1998

Definition at line 41 of file LinearHMM.h.

Inheritance diagram for CLinearHMM:
Inheritance graph
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Public Member Functions

 CLinearHMM ()
 CLinearHMM (CStringFeatures< uint16_t > *f)
 CLinearHMM (int32_t p_num_features, int32_t p_num_symbols)
virtual ~CLinearHMM ()
virtual bool train (CFeatures *data=NULL)
bool train (const int32_t *indizes, int32_t num_indizes, float64_t pseudo_count)
float64_t get_log_likelihood_example (uint16_t *vector, int32_t len)
float64_t get_likelihood_example (uint16_t *vector, int32_t len)
float64_t get_likelihood_example (int32_t num_example)
virtual float64_t get_log_likelihood_example (int32_t num_example)
virtual float64_t get_log_derivative (int32_t num_param, int32_t num_example)
virtual float64_t get_log_derivative_obsolete (uint16_t obs, int32_t pos)
virtual float64_t get_derivative_obsolete (uint16_t *vector, int32_t len, int32_t pos)
virtual int32_t get_sequence_length ()
virtual int32_t get_num_symbols ()
virtual int32_t get_num_model_parameters ()
virtual float64_t get_positional_log_parameter (uint16_t obs, int32_t position)
virtual float64_t get_log_model_parameter (int32_t num_param)
virtual SGVector< float64_tget_log_transition_probs ()
virtual bool set_log_transition_probs (const SGVector< float64_t > probs)
virtual SGVector< float64_tget_transition_probs ()
virtual bool set_transition_probs (const SGVector< float64_t > probs)
virtual const char * get_name () const
virtual int32_t get_num_relevant_model_parameters ()
virtual float64_t get_log_likelihood_sample ()
virtual SGVector< float64_tget_log_likelihood ()
virtual float64_t get_model_parameter (int32_t num_param)
virtual float64_t get_derivative (int32_t num_param, int32_t num_example)
virtual SGVector< float64_tget_likelihood_for_all_examples ()
virtual void set_features (CFeatures *f)
virtual CFeaturesget_features ()
virtual void set_pseudo_count (float64_t pseudo)
virtual float64_t get_pseudo_count ()
virtual CSGObjectshallow_copy () const
virtual CSGObjectdeep_copy () const
virtual bool is_generic (EPrimitiveType *generic) const
template<class T >
void set_generic ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
void set_global_io (SGIO *io)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_global_version ()
SGStringList< char > get_modelsel_names ()
void print_modsel_params ()
char * get_modsel_param_descr (const char *param_name)
index_t get_modsel_param_index (const char *param_name)
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
virtual void update_parameter_hash ()
virtual bool parameter_hash_changed ()
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
virtual CSGObjectclone ()

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
Parameterm_gradient_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

virtual void load_serializable_post () throw (ShogunException)
virtual TParametermigrate (DynArray< TParameter * > *param_base, const SGParamInfo *target)
virtual void one_to_one_migration_prepare (DynArray< TParameter * > *param_base, const SGParamInfo *target, TParameter *&replacement, TParameter *&to_migrate, char *old_name=NULL)
virtual void load_serializable_pre () throw (ShogunException)
virtual void save_serializable_pre () throw (ShogunException)
virtual void save_serializable_post () throw (ShogunException)

Protected Attributes

int32_t sequence_length
int32_t num_symbols
int32_t num_params
float64_ttransition_probs
float64_tlog_transition_probs
CFeaturesfeatures
float64_t pseudo_count

Constructor & Destructor Documentation

default constructor

Definition at line 22 of file LinearHMM.cpp.

CLinearHMM ( CStringFeatures< uint16_t > *  f)

constructor

Parameters
ffeatures to use

Definition at line 27 of file LinearHMM.cpp.

CLinearHMM ( int32_t  p_num_features,
int32_t  p_num_symbols 
)

constructor

Parameters
p_num_featuresnumber of features
p_num_symbolsnumber of symbols in features

Definition at line 38 of file LinearHMM.cpp.

~CLinearHMM ( )
virtual

Definition at line 48 of file LinearHMM.cpp.

Member Function Documentation

void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject * > *  dict)
inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

Parameters
dictdictionary of parameters to be built.

Definition at line 1185 of file SGObject.cpp.

CSGObject * clone ( )
virtualinherited

Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.

Returns
an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

Definition at line 1302 of file SGObject.cpp.

CSGObject * deep_copy ( ) const
virtualinherited

A deep copy. All the instance variables will also be copied.

Definition at line 146 of file SGObject.cpp.

bool equals ( CSGObject other,
float64_t  accuracy = 0.0,
bool  tolerant = false 
)
virtualinherited

Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!

May be overwritten but please do with care! Should not be necessary in most cases.

Parameters
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 1206 of file SGObject.cpp.

virtual float64_t get_derivative ( int32_t  num_param,
int32_t  num_example 
)
virtualinherited

get partial derivative of likelihood function

Parameters
num_parampartial derivative against which param
num_examplewhich example
Returns
derivative of likelihood function

Definition at line 133 of file Distribution.h.

virtual float64_t get_derivative_obsolete ( uint16_t *  vector,
int32_t  len,
int32_t  pos 
)
virtual

obsolete get one example's derivative

Parameters
vectorvector
lenlength
posposition

Definition at line 140 of file LinearHMM.h.

virtual CFeatures* get_features ( )
virtualinherited

get feature vectors

Returns
feature vectors

Definition at line 170 of file Distribution.h.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 183 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 224 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 237 of file SGObject.cpp.

float64_t get_likelihood_example ( uint16_t *  vector,
int32_t  len 
)

get one example's likelihood

Parameters
vectorthe example
lenlength of vector
Returns
likelihood

Definition at line 210 of file LinearHMM.cpp.

float64_t get_likelihood_example ( int32_t  num_example)
virtual

compute likelihood for example

Parameters
num_examplewhich example
Returns
likelihood for example

Reimplemented from CDistribution.

Definition at line 220 of file LinearHMM.cpp.

SGVector< float64_t > get_likelihood_for_all_examples ( )
virtualinherited

compute likelihood for all vectors in sample

Returns
likelihood vector for all examples

Definition at line 63 of file Distribution.cpp.

float64_t get_log_derivative ( int32_t  num_param,
int32_t  num_example 
)
virtual

get logarithm of one example's derivative's likelihood

Parameters
num_paramwhich example's param
num_examplewhich example
Returns
logarithm of example's derivative

Implements CDistribution.

Definition at line 235 of file LinearHMM.cpp.

virtual float64_t get_log_derivative_obsolete ( uint16_t  obs,
int32_t  pos 
)
virtual

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

Parameters
obsobservation
posposition

Definition at line 128 of file LinearHMM.h.

SGVector< float64_t > get_log_likelihood ( )
virtualinherited

compute log likelihood for each example

Returns
log likelihood vector

Definition at line 37 of file Distribution.cpp.

float64_t get_log_likelihood_example ( uint16_t *  vector,
int32_t  len 
)

get logarithm of one example's likelihood

Parameters
vectorthe example
lenlength of vector
Returns
logarithm of likelihood

Definition at line 186 of file LinearHMM.cpp.

float64_t get_log_likelihood_example ( int32_t  num_example)
virtual

get logarithm of one example's likelihood

Parameters
num_examplewhich example
Returns
logarithm of example's likelihood

Implements CDistribution.

Definition at line 196 of file LinearHMM.cpp.

float64_t get_log_likelihood_sample ( )
virtualinherited

compute log likelihood for whole sample

Returns
log likelihood for whole sample

Definition at line 26 of file Distribution.cpp.

virtual float64_t get_log_model_parameter ( int32_t  num_param)
virtual

get logarithm of given model parameter

Parameters
num_paramwhich param
Returns
logarithm of given model parameter

Implements CDistribution.

Definition at line 182 of file LinearHMM.h.

SGVector< float64_t > get_log_transition_probs ( )
virtual

get logarithm of all transition probs

Returns
logarithm of transition probs vector

Definition at line 278 of file LinearHMM.cpp.

virtual float64_t get_model_parameter ( int32_t  num_param)
virtualinherited

get model parameter

Parameters
num_paramwhich param
Returns
model parameter

Definition at line 122 of file Distribution.h.

SGStringList< char > get_modelsel_names ( )
inherited
Returns
vector of names of all parameters which are registered for model selection

Definition at line 1077 of file SGObject.cpp.

char * get_modsel_param_descr ( const char *  param_name)
inherited

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

Parameters
param_namename of the parameter
Returns
description of the parameter

Definition at line 1101 of file SGObject.cpp.

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

Parameters
param_namename of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1114 of file SGObject.cpp.

virtual const char* get_name ( ) const
virtual
Returns
object name

Implements CSGObject.

Definition at line 217 of file LinearHMM.h.

virtual int32_t get_num_model_parameters ( )
virtual

get number of model parameters

Returns
number of model parameters

Implements CDistribution.

Definition at line 163 of file LinearHMM.h.

int32_t get_num_relevant_model_parameters ( )
virtualinherited

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

Returns
number of relevant model parameters

Definition at line 50 of file Distribution.cpp.

virtual int32_t get_num_symbols ( )
virtual

get number of symbols in examples

Returns
number of symbols in examples

Definition at line 157 of file LinearHMM.h.

virtual float64_t get_positional_log_parameter ( uint16_t  obs,
int32_t  position 
)
virtual

get positional log parameter

Parameters
obsobservation
positionposition
Returns
positional log parameter

Definition at line 171 of file LinearHMM.h.

virtual float64_t get_pseudo_count ( )
virtualinherited

get pseudo count

Returns
pseudo count

Definition at line 186 of file Distribution.h.

virtual int32_t get_sequence_length ( )
virtual

get sequence length of each example

Returns
sequence length of each example

Definition at line 151 of file LinearHMM.h.

SGVector< float64_t > get_transition_probs ( )
virtual

get all transition probs

Returns
vector of transition probs

Definition at line 254 of file LinearHMM.cpp.

bool is_generic ( EPrimitiveType *  generic) const
virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

Parameters
genericset to the type of the generic if returning TRUE
Returns
TRUE if a class template.

Definition at line 243 of file SGObject.cpp.

DynArray< TParameter * > * load_all_file_parameters ( int32_t  file_version,
int32_t  current_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)

Parameters
file_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_version_parameter() for this in most cases)
filefile to load from
prefixprefix for members
Returns
(sorted) array of created TParameter instances with file data

Definition at line 648 of file SGObject.cpp.

DynArray< TParameter * > * load_file_parameters ( const SGParamInfo param_info,
int32_t  file_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned

Parameters
param_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
Returns
new array with TParameter instances with the attached data

Definition at line 489 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

Parameters
filewhere to load from
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Definition at line 320 of file SGObject.cpp.

void load_serializable_post ( ) throw (ShogunException)
protectedvirtual

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Reimplemented from CSGObject.

Definition at line 302 of file LinearHMM.cpp.

void load_serializable_pre ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 999 of file SGObject.cpp.

void map_parameters ( DynArray< TParameter * > *  param_base,
int32_t &  base_version,
DynArray< const SGParamInfo * > *  target_param_infos 
)
inherited

Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match

Parameters
param_baseset of TParameter instances that are mapped to the provided target parameter infos
base_versionversion of the parameter base
target_param_infosset of SGParamInfo instances that specify the target parameter base

Definition at line 686 of file SGObject.cpp.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 
)
protectedvirtualinherited

creates a new TParameter instance, which contains migrated data from the version that is provided. The provided parameter data base is used for migration, this base is a collection of all parameter data of the previous version. Migration is done FROM the data in param_base TO the provided param info Migration is always one version step. Method has to be implemented in subclasses, if no match is found, base method has to be called.

If there is an element in the param_base which equals the target, a copy of the element is returned. This represents the case when nothing has changed and therefore, the migrate method is not overloaded in a subclass

Parameters
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
Returns
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

Definition at line 893 of file SGObject.cpp.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 
)
protectedvirtualinherited

This method prepares everything for a one-to-one parameter migration. One to one here means that only ONE element of the parameter base is needed for the migration (the one with the same name as the target). Data is allocated for the target (in the type as provided in the target SGParamInfo), and a corresponding new TParameter instance is written to replacement. The to_migrate pointer points to the single needed TParameter instance needed for migration. If a name change happened, the old name may be specified by old_name. In addition, the m_delete_data flag of to_migrate is set to true. So if you want to migrate data, the only thing to do after this call is converting the data in the m_parameter fields. If unsure how to use - have a look into an example for this. (base_migration_type_conversion.cpp for example)

Parameters
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
replacement(used as output) here the TParameter instance which is returned by migration is created into
to_migratethe only source that is used for migration
old_namewith this parameter, a name change may be specified

Definition at line 833 of file SGObject.cpp.

bool parameter_hash_changed ( )
virtualinherited
Returns
whether parameter combination has changed since last update

Definition at line 209 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1053 of file SGObject.cpp.

void print_serializable ( const char *  prefix = "")
virtualinherited

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 255 of file SGObject.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Save this object to file.

Parameters
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Definition at line 261 of file SGObject.cpp.

void save_serializable_post ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1014 of file SGObject.cpp.

void save_serializable_pre ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 1009 of file SGObject.cpp.

virtual void set_features ( CFeatures f)
virtualinherited

set feature vectors

Parameters
fnew feature vectors

Definition at line 159 of file Distribution.h.

void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 38 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 176 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 189 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 230 of file SGObject.cpp.

bool set_log_transition_probs ( const SGVector< float64_t probs)
virtual

set logarithm of all transition probs

Parameters
probsnew logarithm transition probs
Returns
if setting was successful

Definition at line 283 of file LinearHMM.cpp.

virtual void set_pseudo_count ( float64_t  pseudo)
virtualinherited

set pseudo count

Parameters
pseudonew pseudo count

Definition at line 180 of file Distribution.h.

bool set_transition_probs ( const SGVector< float64_t probs)
virtual

set all transition probs

Parameters
probsnew transition probs
Returns
if setting was successful

Definition at line 259 of file LinearHMM.cpp.

CSGObject * shallow_copy ( ) const
virtualinherited

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

Reimplemented in CGaussianKernel.

Definition at line 140 of file SGObject.cpp.

bool train ( CFeatures data = NULL)
virtual

estimate LinearHMM distribution

Parameters
datatraining 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 54 of file LinearHMM.cpp.

bool train ( const int32_t *  indizes,
int32_t  num_indizes,
float64_t  pseudo_count 
)

alternative train distribution

Parameters
indizesindices
num_indizesnumber of indices
pseudo_countpseudo count
Returns
if training was successful

Definition at line 123 of file LinearHMM.cpp.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 250 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 196 of file SGObject.cpp.

Member Data Documentation

CFeatures* features
protectedinherited

feature vectors

Definition at line 190 of file Distribution.h.

SGIO* io
inherited

io

Definition at line 461 of file SGObject.h.

float64_t* log_transition_probs
protected

logarithm of transition probs

Definition at line 235 of file LinearHMM.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 476 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 482 of file SGObject.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 473 of file SGObject.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 479 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 470 of file SGObject.h.

int32_t num_params
protected

number of parameters

Definition at line 231 of file LinearHMM.h.

int32_t num_symbols
protected

number of symbols in examples

Definition at line 229 of file LinearHMM.h.

Parallel* parallel
inherited

parallel

Definition at line 464 of file SGObject.h.

float64_t pseudo_count
protectedinherited

pseudo count

Definition at line 192 of file Distribution.h.

int32_t sequence_length
protected

examples' sequence length

Definition at line 227 of file LinearHMM.h.

float64_t* transition_probs
protected

transition probs

Definition at line 233 of file LinearHMM.h.

Version* version
inherited

version

Definition at line 467 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation