Public Member Functions | Public Attributes | Protected Member Functions | Protected Attributes

CGaussian Class Reference


Detailed Description

Gaussian distribution interface.

Takes as input a mean vector and covariance matrix. Also possible to train from data. Likelihood is computed using the Gaussian PDF $(2\pi)^{-\frac{k}{2}}|\Sigma|^{-\frac{1}{2}}e^{-\frac{1}{2}(x-\mu)'\Sigma^{-1}(x-\mu)}$ The actual computations depend on the type of covariance used.

Definition at line 46 of file Gaussian.h.

Inheritance diagram for CGaussian:
Inheritance graph
[legend]

List of all members.

Public Member Functions

 CGaussian ()
 CGaussian (const SGVector< float64_t > mean, SGMatrix< float64_t > cov, ECovType cov_type=FULL)
virtual ~CGaussian ()
void init ()
virtual bool train (CFeatures *data=NULL)
virtual int32_t get_num_model_parameters ()
virtual float64_t get_log_model_parameter (int32_t num_param)
virtual float64_t get_log_derivative (int32_t num_param, int32_t num_example)
virtual float64_t get_log_likelihood_example (int32_t num_example)
virtual float64_t compute_PDF (SGVector< float64_t > point)
virtual float64_t compute_log_PDF (SGVector< float64_t > point)
virtual SGVector< float64_tget_mean ()
virtual void set_mean (const SGVector< float64_t > mean)
virtual SGMatrix< float64_tget_cov ()
virtual void set_cov (SGMatrix< float64_t > cov)
ECovType get_cov_type ()
void set_cov_type (ECovType cov_type)
SGVector< float64_tget_d ()
void set_d (const SGVector< float64_t > d)
SGMatrix< float64_tget_u ()
void set_u (SGMatrix< float64_t > u)
SGVector< float64_tsample ()
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 float64_t get_likelihood_example (int32_t num_example)
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_PARAMETER)
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=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_parameter_dictionary (CMap< TParameter *, CSGObject * > &dict)

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

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 load_serializable_post () throw (ShogunException)
virtual void save_serializable_pre () throw (ShogunException)
virtual void save_serializable_post () throw (ShogunException)
virtual bool update_parameter_hash ()

Protected Attributes

float64_t m_constant
SGVector< float64_tm_d
SGMatrix< float64_tm_u
SGVector< float64_tm_mean
ECovType m_cov_type
CFeaturesfeatures
float64_t pseudo_count

Constructor & Destructor Documentation

CGaussian (  ) 

default constructor

Definition at line 20 of file Gaussian.cpp.

CGaussian ( const SGVector< float64_t mean,
SGMatrix< float64_t cov,
ECovType  cov_type = FULL 
)

constructor

Parameters:
mean mean of the Gaussian
cov covariance of the Gaussian
cov_type covariance type (full, diagonal or shperical)

Definition at line 25 of file Gaussian.cpp.

~CGaussian (  )  [virtual]

Definition at line 57 of file Gaussian.cpp.


Member Function Documentation

void build_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:
dict dictionary of parameters to be built.

Definition at line 1201 of file SGObject.cpp.

float64_t compute_log_PDF ( SGVector< float64_t point  )  [virtual]

compute log PDF

Parameters:
point point for which to compute the log PDF
Returns:
computed log PDF

Definition at line 113 of file Gaussian.cpp.

virtual float64_t compute_PDF ( SGVector< float64_t point  )  [virtual]

compute PDF

Parameters:
point point for which to compute the PDF
Returns:
computed PDF

Definition at line 107 of file Gaussian.h.

virtual CSGObject* deep_copy (  )  const [virtual, inherited]

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

Definition at line 131 of file SGObject.h.

SGMatrix< float64_t > get_cov (  )  [virtual]

get covariance

Parameters:
cov covariance, memory needs to be freed by user

Definition at line 179 of file Gaussian.cpp.

ECovType get_cov_type (  ) 

get covariance type

Returns:
covariance type

Definition at line 149 of file Gaussian.h.

SGVector<float64_t> get_d (  ) 

get diagonal

Returns:
diagonal

Definition at line 169 of file Gaussian.h.

virtual float64_t get_derivative ( int32_t  num_param,
int32_t  num_example 
) [virtual, inherited]

get partial derivative of likelihood function

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

Definition at line 129 of file Distribution.h.

virtual CFeatures* get_features (  )  [virtual, inherited]

get feature vectors

Returns:
feature vectors

Definition at line 160 of file Distribution.h.

SGIO * get_global_io (  )  [inherited]

get the io object

Returns:
io object

Definition at line 224 of file SGObject.cpp.

Parallel * get_global_parallel (  )  [inherited]

get the parallel object

Returns:
parallel object

Definition at line 259 of file SGObject.cpp.

Version * get_global_version (  )  [inherited]

get the version object

Returns:
version object

Definition at line 272 of file SGObject.cpp.

virtual float64_t get_likelihood_example ( int32_t  num_example  )  [virtual, inherited]

compute likelihood for example

Parameters:
num_example which example
Returns:
likelihood for example

Reimplemented in CGMM.

Definition at line 140 of file Distribution.h.

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

get partial derivative of likelihood function (logarithmic)

Parameters:
num_param derivative against which param
num_example which example
Returns:
derivative of likelihood (logarithmic)

Implements CDistribution.

Definition at line 99 of file Gaussian.cpp.

SGVector< float64_t > get_log_likelihood (  )  [virtual, inherited]

compute log likelihood for each example

Returns:
log likelihood vector

Definition at line 37 of file Distribution.cpp.

float64_t get_log_likelihood_example ( int32_t  num_example  )  [virtual]

compute log likelihood for example

abstract base method

Parameters:
num_example which example
Returns:
log likelihood for example

Implements CDistribution.

Definition at line 105 of file Gaussian.cpp.

float64_t get_log_likelihood_sample (  )  [virtual, inherited]

compute log likelihood for whole sample

Returns:
log likelihood for whole sample

Definition at line 26 of file Distribution.cpp.

float64_t get_log_model_parameter ( int32_t  num_param  )  [virtual]

get model parameter (logarithmic)

Returns:
model parameter (logarithmic) if num_param < m_dim returns an element from the mean, else return an element from the covariance

Implements CDistribution.

Definition at line 93 of file Gaussian.cpp.

SGVector< float64_t > get_mean (  )  [virtual]

get mean

Returns:
mean

Definition at line 152 of file Gaussian.cpp.

virtual float64_t get_model_parameter ( int32_t  num_param  )  [virtual, inherited]

get model parameter

Parameters:
num_param which param
Returns:
model parameter

Definition at line 118 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 1108 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_name name of the parameter
Returns:
description of the parameter

Definition at line 1132 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_name name of model selection parameter
Returns:
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1145 of file SGObject.cpp.

virtual const char* get_name (  )  const [virtual]
Returns:
object name

Implements CSGObject.

Definition at line 205 of file Gaussian.h.

int32_t get_num_model_parameters (  )  [virtual]

get number of parameters in model

Returns:
number of parameters in model

Implements CDistribution.

Definition at line 79 of file Gaussian.cpp.

int32_t 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 50 of file Distribution.cpp.

virtual float64_t get_pseudo_count (  )  [virtual, inherited]

get pseudo count

Returns:
pseudo count

Definition at line 176 of file Distribution.h.

SGMatrix<float64_t> get_u (  ) 

get unitary matrix

Returns:
unitary matrix

Definition at line 184 of file Gaussian.h.

void init (  ) 

Compute the constant part

Reimplemented from CSGObject.

Definition at line 41 of file Gaussian.cpp.

bool is_generic ( EPrimitiveType *  generic  )  const [virtual, inherited]

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

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

Definition at line 278 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_version parameter version of the file
current_version version from which mapping begins (you want to use VERSION_PARAMETER for this in most cases)
file file to load from
prefix prefix for members
Returns:
(sorted) array of created TParameter instances with file data

Definition at line 679 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_info information of parameter
file_version parameter version of the file, must be <= provided parameter version
file file to load from
prefix prefix for members
Returns:
new array with TParameter instances with the attached data

Definition at line 523 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = VERSION_PARAMETER 
) [virtual, inherited]

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

Parameters:
file where to load from
prefix prefix 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

Reimplemented in CModelSelectionParameters.

Definition at line 354 of file SGObject.cpp.

void load_serializable_post (  )  throw (ShogunException) [protected, virtual, inherited]

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:
ShogunException Will be thrown if an error occurres.

Reimplemented in CLinearHMM, CAlphabet, CANOVAKernel, CCircularKernel, CExponentialKernel, CGaussianKernel, CInverseMultiQuadricKernel, CKernel, CWeightedDegreePositionStringKernel, and CList.

Definition at line 1033 of file SGObject.cpp.

void load_serializable_pre (  )  throw (ShogunException) [protected, virtual, inherited]

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:
ShogunException Will be thrown if an error occurres.

Definition at line 1028 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_base set of TParameter instances that are mapped to the provided target parameter infos
base_version version of the parameter base
target_param_infos set of SGParamInfo instances that specify the target parameter base

Definition at line 717 of file SGObject.cpp.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 
) [protected, virtual, inherited]

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_base set of TParameter instances to use for migration
target parameter 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 923 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 
) [protected, virtual, inherited]

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_base set of TParameter instances to use for migration
target parameter info for the resulting TParameter
replacement (used as output) here the TParameter instance which is returned by migration is created into
to_migrate the only source that is used for migration
old_name with this parameter, a name change may be specified

Definition at line 864 of file SGObject.cpp.

void print_modsel_params (  )  [inherited]

prints all parameter registered for model selection and their type

Definition at line 1084 of file SGObject.cpp.

void print_serializable ( const char *  prefix = ""  )  [virtual, inherited]

prints registered parameters out

Parameters:
prefix prefix for members

Definition at line 290 of file SGObject.cpp.

SGVector< float64_t > sample (  ) 

sample from distribution

Returns:
sample

Definition at line 257 of file Gaussian.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = VERSION_PARAMETER 
) [virtual, inherited]

Save this object to file.

Parameters:
file where to save the object; will be closed during returning if PREFIX is an empty string.
prefix prefix 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

Reimplemented in CModelSelectionParameters.

Definition at line 296 of file SGObject.cpp.

void save_serializable_post (  )  throw (ShogunException) [protected, virtual, inherited]

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:
ShogunException Will be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1043 of file SGObject.cpp.

void save_serializable_pre (  )  throw (ShogunException) [protected, virtual, inherited]

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:
ShogunException Will be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1038 of file SGObject.cpp.

void set_cov ( SGMatrix< float64_t cov  )  [virtual]

set covariance

Doesn't store the covariance, but decomposes, thus the covariance can be freed after exit without harming the object

Parameters:
cov new covariance

Definition at line 165 of file Gaussian.cpp.

void set_cov_type ( ECovType  cov_type  ) 

set covariance type

Will only take effect after covariance is changed

Parameters:
cov_type new covariance type

Definition at line 160 of file Gaussian.h.

void set_d ( const SGVector< float64_t d  ) 

set diagonal

Parameters:
d new diagonal

Definition at line 173 of file Gaussian.cpp.

virtual void set_features ( CFeatures f  )  [virtual, inherited]

set feature vectors

Parameters:
f new feature vectors

Definition at line 149 of file Distribution.h.

void set_generic< floatmax_t > (  )  [inherited]

set generic type to T

void set_global_io ( SGIO io  )  [inherited]

set the io object

Parameters:
io io object to use

Definition at line 217 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel  )  [inherited]

set the parallel object

Parameters:
parallel parallel object to use

Definition at line 230 of file SGObject.cpp.

void set_global_version ( Version version  )  [inherited]

set the version object

Parameters:
version version object to use

Definition at line 265 of file SGObject.cpp.

void set_mean ( const SGVector< float64_t mean  )  [virtual]

set mean

Parameters:
mean new mean

Definition at line 157 of file Gaussian.cpp.

virtual void set_pseudo_count ( float64_t  pseudo  )  [virtual, inherited]

set pseudo count

Parameters:
pseudo new pseudo count

Definition at line 170 of file Distribution.h.

void set_u ( SGMatrix< float64_t u  ) 

set unitary matrix

Parameters:
u new unitary matrix

Definition at line 193 of file Gaussian.h.

virtual CSGObject* shallow_copy (  )  const [virtual, inherited]

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

Reimplemented in CGaussianKernel.

Definition at line 122 of file SGObject.h.

bool train ( CFeatures data = NULL  )  [virtual]

learn distribution

Parameters:
data training data
Returns:
whether training was successful

Implements CDistribution.

Definition at line 61 of file Gaussian.cpp.

void unset_generic (  )  [inherited]

unset generic type

this has to be called in classes specializing a template class

Definition at line 285 of file SGObject.cpp.

bool update_parameter_hash (  )  [protected, virtual, inherited]

Updates the hash of current parameter combination.

Returns:
bool if parameter combination has changed since last update.

Definition at line 237 of file SGObject.cpp.


Member Data Documentation

CFeatures* features [protected, inherited]

feature vectors

Definition at line 180 of file Distribution.h.

SGIO* io [inherited]

io

Definition at line 462 of file SGObject.h.

float64_t m_constant [protected]

constant part

Definition at line 219 of file Gaussian.h.

ECovType m_cov_type [protected]

covariance type

Definition at line 227 of file Gaussian.h.

SGVector<float64_t> m_d [protected]

diagonal

Definition at line 221 of file Gaussian.h.

uint32_t m_hash [inherited]

Hash of parameter values

Definition at line 480 of file SGObject.h.

SGVector<float64_t> m_mean [protected]

mean

Definition at line 225 of file Gaussian.h.

model selection parameters

Definition at line 474 of file SGObject.h.

map for different parameter versions

Definition at line 477 of file SGObject.h.

Parameter* m_parameters [inherited]

parameters

Definition at line 471 of file SGObject.h.

SGMatrix<float64_t> m_u [protected]

unitary matrix

Definition at line 223 of file Gaussian.h.

Parallel* parallel [inherited]

parallel

Definition at line 465 of file SGObject.h.

float64_t pseudo_count [protected, inherited]

pseudo count

Definition at line 182 of file Distribution.h.

Version* version [inherited]

version

Definition at line 468 of file SGObject.h.


The documentation for this class was generated from the following files:
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines

SHOGUN Machine Learning Toolbox - Documentation