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CFITCInferenceMethod Class Reference

Detailed Description

The Fully Independent Conditional Training Inference Method.

This inference method computes the Cholesky and Alpha vectors approximately with the help of latent variables. For more details, see "Sparse Gaussian Process using Pseudo-inputs", Edward Snelson, Zoubin Ghahramani, NIPS 18, MIT Press, 2005.

This specific implementation was inspired by the infFITC.m file in the GPML toolbox

The Gaussian Likelihood Function must be used for this inference method.

Definition at line 41 of file FITCInferenceMethod.h.

Inheritance diagram for CFITCInferenceMethod:
Inheritance graph
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Public Member Functions

 CFITCInferenceMethod ()
 CFITCInferenceMethod (CKernel *kernel, CFeatures *features, CMeanFunction *mean, CLabels *labels, CLikelihoodModel *model, CFeatures *latent_features)
virtual ~CFITCInferenceMethod ()
virtual float64_t get_negative_marginal_likelihood ()
virtual CMap< TParameter
*, SGVector< float64_t > > 
get_marginal_likelihood_derivatives (CMap< TParameter *, CSGObject * > &para_dict)
virtual SGVector< float64_tget_alpha ()
virtual SGMatrix< float64_tget_cholesky ()
virtual SGVector< float64_tget_diagonal_vector ()
virtual const char * get_name () const
virtual CMap< TParameter
*, SGVector< float64_t > > 
get_gradient (CMap< TParameter *, CSGObject * > &para_dict)
virtual SGVector< float64_tget_quantity ()
virtual void set_features (CFeatures *feat)
virtual CFeaturesget_features ()
virtual CKernelget_kernel ()
virtual void set_kernel (CKernel *kern)
virtual CMeanFunctionget_mean ()
virtual void set_mean (CMeanFunction *m)
virtual CLabelsget_labels ()
virtual void set_labels (CLabels *lab)
CLikelihoodModelget_model ()
virtual void set_model (CLikelihoodModel *mod)
virtual void set_scale (float64_t s)
virtual float64_t get_scale ()
virtual void set_latent_features (CFeatures *feat)
virtual CFeaturesget_latent_features ()
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 void update_alpha ()
virtual void update_chol ()
virtual void update_train_kernel ()
virtual void update_all ()
virtual void update_data_means ()
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

CKernelm_kernel
CFeaturesm_features
SGMatrix< float64_tm_feature_matrix
SGVector< float64_tm_data_means
SGVector< float64_tm_label_vector
CLabelsm_labels
CMeanFunctionm_mean
CFeaturesm_latent_features
CLikelihoodModelm_model
SGVector< float64_tm_alpha
SGMatrix< float64_tm_L
float64_t m_scale
SGMatrix< float64_tm_ktrtr
SGMatrix< float64_tm_latent_matrix

Constructor & Destructor Documentation

Definition at line 31 of file FITCInferenceMethod.cpp.

CFITCInferenceMethod ( CKernel kernel,
CFeatures features,
CMeanFunction mean,
CLabels labels,
CLikelihoodModel model,
CFeatures latent_features 
)

Definition at line 38 of file FITCInferenceMethod.cpp.

~CFITCInferenceMethod ( )
virtual

Definition at line 53 of file FITCInferenceMethod.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
dictdictionary of parameters to be built.

Definition at line 1204 of file SGObject.cpp.

virtual CSGObject* deep_copy ( ) const
virtualinherited

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

Definition at line 131 of file SGObject.h.

SGVector< float64_t > get_alpha ( )
virtual

get Alpha Matrix

Returns
Matrix to compute posterior mean of Gaussian Process:

\[ \mu = K\alpha \]

where is the mean and K is the prior covariance matrix

Implements CInferenceMethod.

Definition at line 609 of file FITCInferenceMethod.cpp.

SGMatrix< float64_t > get_cholesky ( )
virtual

get Cholesky Decomposition Matrix

Returns
Cholesky Decomposition of Matrix:

\[ L = Cholesky(sW*K*sW+I) \]

Where K is the prior covariance matrix, sW is the matrix returned by get_cholesky(), and I is the identity matrix.

Implements CInferenceMethod.

Definition at line 618 of file FITCInferenceMethod.cpp.

SGVector< float64_t > get_diagonal_vector ( )
virtual

get Diagonal Vector

Returns
Diagonal of matrix used to calculate posterior covariance matrix

\[ Cov = (K^{-1}+D^{2})^{-1}} \]

Where Cov is the posterior covariance matrix, K is the prior covariance matrix, and D is the diagonal matrix

Implements CInferenceMethod.

Definition at line 568 of file FITCInferenceMethod.cpp.

virtual CFeatures* get_features ( )
virtualinherited

get features

Returns
features

Definition at line 123 of file InferenceMethod.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 CMap<TParameter*, SGVector<float64_t> > get_gradient ( CMap< TParameter *, CSGObject * > &  para_dict)
virtual

Get the gradient

Parameters
para_dictdictionary to be built
Returns
Map of gradient. Keys are names of parameters, values are values of derivative with respect to that parameter.

Implements CDifferentiableFunction.

Definition at line 137 of file FITCInferenceMethod.h.

virtual CKernel* get_kernel ( )
virtualinherited

get kernel

Returns
kernel

Definition at line 133 of file InferenceMethod.h.

virtual CLabels* get_labels ( )
virtualinherited

get labels

Returns
labels

Definition at line 157 of file InferenceMethod.h.

virtual CFeatures* get_latent_features ( )
virtualinherited

get latent features

Returns
features

Definition at line 199 of file InferenceMethod.h.

CMap< TParameter *, SGVector< float64_t > > get_marginal_likelihood_derivatives ( CMap< TParameter *, CSGObject * > &  para_dict)
virtual

get Log Marginal Likelihood Gradient

Returns
Vector of the Marginal Likelihood Function Gradient with respect to hyperparameters

\[ -\frac{\partial {log(p(y|X, \theta))}}{\partial \theta} \]

Implements CInferenceMethod.

Definition at line 211 of file FITCInferenceMethod.cpp.

virtual CMeanFunction* get_mean ( )
virtualinherited

get mean

Returns
mean

Definition at line 145 of file InferenceMethod.h.

CLikelihoodModel* get_model ( )
inherited

get likelihood model

Returns
likelihood

Definition at line 169 of file InferenceMethod.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_namename 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_namename 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 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 127 of file FITCInferenceMethod.h.

float64_t get_negative_marginal_likelihood ( )
virtual

get Negative Log Marginal Likelihood

Returns
The Negative Log of the Marginal Likelihood function:

\[ -log(p(y|X, \theta)) Where y are the labels, X are the features, and \theta represent hyperparameters \]

Implements CInferenceMethod.

Definition at line 575 of file FITCInferenceMethod.cpp.

virtual SGVector<float64_t> get_quantity ( )
virtual

Get the function value

Returns
Vector that represents the function value

Implements CDifferentiableFunction.

Definition at line 147 of file FITCInferenceMethod.h.

virtual float64_t get_scale ( )
virtualinherited

get kernel scale

Returns
kernel scale

Definition at line 187 of file InferenceMethod.h.

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 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_versionparameter version of the file
current_versionversion from which mapping begins (you want to use 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 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_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 523 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = 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

Reimplemented in CModelSelectionParameters.

Definition at line 354 of file SGObject.cpp.

void load_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::LOAD_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

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

Definition at line 1033 of file SGObject.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.

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_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 717 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 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 
)
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 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 = "")
virtualinherited

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 290 of file SGObject.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = 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

Reimplemented in CModelSelectionParameters.

Definition at line 296 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 1043 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.

Definition at line 1038 of file SGObject.cpp.

void set_features ( CFeatures feat)
virtualinherited

set features

Parameters
featfeatures to set

Definition at line 74 of file InferenceMethod.cpp.

void set_generic< floatmax_t > ( )
inherited

set generic type to T

Definition at line 41 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 217 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 230 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 265 of file SGObject.cpp.

void set_kernel ( CKernel kern)
virtualinherited

set kernel

Parameters
kernkernel to set

Definition at line 130 of file InferenceMethod.cpp.

void set_labels ( CLabels lab)
virtualinherited

set labels

Parameters
lablabel to set

Definition at line 151 of file InferenceMethod.cpp.

void set_latent_features ( CFeatures feat)
virtualinherited

set latent features

Parameters
featfeatures to set

Definition at line 102 of file InferenceMethod.cpp.

void set_mean ( CMeanFunction m)
virtualinherited

set mean

Parameters
mmean function to set

Definition at line 140 of file InferenceMethod.cpp.

void set_model ( CLikelihoodModel mod)
virtualinherited

set likelihood model

Parameters
modmodel to set

Definition at line 167 of file InferenceMethod.cpp.

void set_scale ( float64_t  s)
virtualinherited

set kernel scale

Parameters
sscale to be set

Definition at line 177 of file InferenceMethod.cpp.

virtual 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 122 of file SGObject.h.

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.

void update_all ( )
protectedvirtual

Definition at line 57 of file FITCInferenceMethod.cpp.

void update_alpha ( )
protectedvirtual

Update Alpha and Cholesky Matrices.

Reimplemented from CInferenceMethod.

Definition at line 773 of file FITCInferenceMethod.cpp.

void update_chol ( )
protectedvirtual

Update cholesky matrix

Reimplemented from CInferenceMethod.

Definition at line 664 of file FITCInferenceMethod.cpp.

void update_data_means ( )
protectedvirtualinherited

Update data means

Definition at line 185 of file InferenceMethod.cpp.

bool update_parameter_hash ( )
protectedvirtualinherited

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.

void update_train_kernel ( )
protectedvirtual

Update train kernel matrix

Reimplemented from CInferenceMethod.

Definition at line 627 of file FITCInferenceMethod.cpp.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 462 of file SGObject.h.

SGVector< float64_t > m_alpha
protectedinherited

alpha matrix used in process mean calculation

Definition at line 262 of file InferenceMethod.h.

SGVector<float64_t> m_data_means
protectedinherited

Means of Features

Definition at line 235 of file InferenceMethod.h.

SGMatrix<float64_t> m_feature_matrix
protectedinherited

Feature Matrix

Definition at line 232 of file InferenceMethod.h.

CFeatures* m_features
protectedinherited

Features to use

Definition at line 229 of file InferenceMethod.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 480 of file SGObject.h.

CKernel* m_kernel
protectedinherited

Covariance Function

Definition at line 226 of file InferenceMethod.h.

SGMatrix<float64_t> m_ktrtr
protectedinherited

Kernel matrix from features

Definition at line 273 of file InferenceMethod.h.

SGMatrix<float64_t> m_L
protectedinherited

Lower triangle Cholesky decomposition of feature matrix

Definition at line 267 of file InferenceMethod.h.

SGVector<float64_t> m_label_vector
protectedinherited

Vector of labels

Definition at line 238 of file InferenceMethod.h.

CLabels* m_labels
protectedinherited

Labels of those features

Definition at line 242 of file InferenceMethod.h.

CFeatures* m_latent_features
protectedinherited

Latent Features for Approximation

Definition at line 248 of file InferenceMethod.h.

SGMatrix<float64_t> m_latent_matrix
protectedinherited

Kernel matrix from latent features

Definition at line 276 of file InferenceMethod.h.

CMeanFunction* m_mean
protectedinherited

Mean Function

Definition at line 245 of file InferenceMethod.h.

CLikelihoodModel* m_model
protectedinherited

Likelihood function to use

\[ p(y|f) \]

Where y are the labels and f is the prediction function

Definition at line 259 of file InferenceMethod.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 474 of file SGObject.h.

ParameterMap* m_parameter_map
inherited

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.

float64_t m_scale
protectedinherited

Kernel Scale

Definition at line 270 of file InferenceMethod.h.

Parallel* parallel
inherited

parallel

Definition at line 465 of file SGObject.h.

Version* version
inherited

version

Definition at line 468 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation