SHOGUN  v3.2.0
所有成员列表 | Public 成员函数 | Public 属性 | Protected 成员函数 | 静态 Protected 成员函数 | Protected 属性
CExactInferenceMethod类 参考

详细描述

The Gaussian exact form inference method class.

This inference method computes the Gaussian Method exactly using matrix equations.

\[ L = cholesky(K + \sigma^{2}I) \]

\(L\) is the cholesky decomposition of \(K\), the covariance matrix, plus a diagonal matrix with entries \(\sigma^{2}\), the observation noise.

\[ \boldsymbol{\alpha} = L^{T} \backslash(L \backslash \boldsymbol{y}}) \]

where \(L\) is the matrix mentioned above, \(\boldsymbol{y}\) are the labels, and \(\backslash\) is an operator ( \(x = A \backslash B\) means \(Ax=B\).)

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

在文件 ExactInferenceMethod.h47 行定义.

类 CExactInferenceMethod 继承关系图:
Inheritance graph
[图例]

Public 成员函数

 CExactInferenceMethod ()
 
 CExactInferenceMethod (CKernel *kernel, CFeatures *features, CMeanFunction *mean, CLabels *labels, CLikelihoodModel *model)
 
virtual ~CExactInferenceMethod ()
 
virtual EInferenceType get_inference_type () const
 
virtual const char * get_name () const
 
virtual float64_t get_negative_log_marginal_likelihood ()
 
virtual SGVector< float64_tget_alpha ()
 
virtual SGMatrix< float64_tget_cholesky ()
 
virtual SGVector< float64_tget_diagonal_vector ()
 
virtual SGVector< float64_tget_posterior_mean ()
 
virtual SGMatrix< float64_tget_posterior_covariance ()
 
virtual bool supports_regression () const
 
virtual void update ()
 
float64_t get_marginal_likelihood_estimate (int32_t num_importance_samples=1, float64_t ridge_size=1e-15)
 
virtual CMap< TParameter *, SGVector< float64_t > > * get_negative_log_marginal_likelihood_derivatives (CMap< TParameter *, CSGObject *> *parameters)
 
virtual CMap< TParameter *, SGVector< float64_t > > * get_gradient (CMap< TParameter *, CSGObject *> *parameters)
 
virtual SGVector< float64_tget_value ()
 
virtual CFeaturesget_features ()
 
virtual void set_features (CFeatures *feat)
 
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 float64_t get_scale () const
 
virtual void set_scale (float64_t scale)
 
virtual bool supports_binary () const
 
virtual bool supports_multiclass () const
 
virtual CSGObjectshallow_copy () const
 
virtual CSGObjectdeep_copy () const
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
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 bool update_parameter_hash ()
 
virtual bool equals (CSGObject *other, float64_t accuracy=0.0)
 
virtual CSGObjectclone ()
 

Public 属性

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
ParameterMapm_parameter_map
 
uint32_t m_hash
 

Protected 成员函数

virtual void check_members () const
 
virtual void update_alpha ()
 
virtual void update_chol ()
 
virtual void update_mean ()
 
virtual void update_cov ()
 
virtual void update_deriv ()
 
virtual SGVector< float64_tget_derivative_wrt_inference_method (const TParameter *param)
 
virtual SGVector< float64_tget_derivative_wrt_likelihood_model (const TParameter *param)
 
virtual SGVector< float64_tget_derivative_wrt_kernel (const TParameter *param)
 
virtual SGVector< float64_tget_derivative_wrt_mean (const TParameter *param)
 
virtual void update_train_kernel ()
 
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)
 

静态 Protected 成员函数

static void * get_derivative_helper (void *p)
 

Protected 属性

CKernelm_kernel
 
CMeanFunctionm_mean
 
CLikelihoodModelm_model
 
CFeaturesm_features
 
CLabelsm_labels
 
SGVector< float64_tm_alpha
 
SGMatrix< float64_tm_L
 
float64_t m_scale
 
SGMatrix< float64_tm_ktrtr
 

构造及析构函数说明

§ CExactInferenceMethod() [1/2]

default constructor

在文件 ExactInferenceMethod.cpp27 行定义.

§ CExactInferenceMethod() [2/2]

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

constructor

参数
kernelcovariance function
featuresfeatures to use in inference
meanmean function to use
labelslabels of the features
modellikelihood model to use

在文件 ExactInferenceMethod.cpp31 行定义.

§ ~CExactInferenceMethod()

~CExactInferenceMethod ( )
virtual

在文件 ExactInferenceMethod.cpp37 行定义.

成员函数说明

§ build_gradient_parameter_dictionary()

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.

参数
dictdictionary of parameters to be built.

在文件 SGObject.cpp1156 行定义.

§ check_members()

void check_members ( ) const
protectedvirtual

check if members of object are valid for inference

重载 CInferenceMethod .

在文件 ExactInferenceMethod.cpp51 行定义.

§ clone()

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.

返回
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

在文件 SGObject.cpp1273 行定义.

§ deep_copy()

virtual CSGObject* deep_copy ( ) const
virtualinherited

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

在文件 SGObject.h126 行定义.

§ equals()

bool equals ( CSGObject other,
float64_t  accuracy = 0.0 
)
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.

参数
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
返回
true if all parameters were equal, false if not

在文件 SGObject.cpp1177 行定义.

§ get_alpha()

SGVector< float64_t > get_alpha ( )
virtual

get alpha vector

返回
vector to compute posterior mean of Gaussian Process:

\[ \mu = K\alpha \]

where \(\mu\) is the mean and \(K\) is the prior covariance matrix.

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp107 行定义.

§ get_cholesky()

SGMatrix< float64_t > get_cholesky ( )
virtual

get Cholesky decomposition matrix

返回
Cholesky decomposition of matrix:

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

where \(K\) is the prior covariance matrix, \(sW\) is the vector returned by get_diagonal_vector(), and \(I\) is the identity matrix.

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp115 行定义.

§ get_derivative_helper()

void * get_derivative_helper ( void *  p)
staticprotectedinherited

pthread helper method to compute negative log marginal likelihood derivatives wrt hyperparameter

在文件 InferenceMethod.cpp209 行定义.

§ get_derivative_wrt_inference_method()

SGVector< float64_t > get_derivative_wrt_inference_method ( const TParameter param)
protectedvirtual

returns derivative of negative log marginal likelihood wrt parameter of CInferenceMethod class

参数
paramparameter of CInferenceMethod class
返回
derivative of negative log marginal likelihood

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp246 行定义.

§ get_derivative_wrt_kernel()

SGVector< float64_t > get_derivative_wrt_kernel ( const TParameter param)
protectedvirtual

returns derivative of negative log marginal likelihood wrt kernel's parameter

参数
paramparameter of given kernel
返回
derivative of negative log marginal likelihood

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp288 行定义.

§ get_derivative_wrt_likelihood_model()

SGVector< float64_t > get_derivative_wrt_likelihood_model ( const TParameter param)
protectedvirtual

returns derivative of negative log marginal likelihood wrt parameter of likelihood model

参数
paramparameter of given likelihood model
返回
derivative of negative log marginal likelihood

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp264 行定义.

§ get_derivative_wrt_mean()

SGVector< float64_t > get_derivative_wrt_mean ( const TParameter param)
protectedvirtual

returns derivative of negative log marginal likelihood wrt mean function's parameter

参数
paramparameter of given mean function
返回
derivative of negative log marginal likelihood

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp326 行定义.

§ get_diagonal_vector()

SGVector< float64_t > get_diagonal_vector ( )
virtual

get diagonal vector

返回
diagonal of matrix used to calculate posterior covariance matrix

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

where \(Cov\) is the posterior covariance matrix, \(K\) is the prior covariance matrix, and \(sW\) is the diagonal vector.

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp61 行定义.

§ get_features()

virtual CFeatures* get_features ( )
virtualinherited

get features

返回
features

在文件 InferenceMethod.h241 行定义.

§ get_global_io()

SGIO * get_global_io ( )
inherited

get the io object

返回
io object

在文件 SGObject.cpp174 行定义.

§ get_global_parallel()

Parallel * get_global_parallel ( )
inherited

get the parallel object

返回
parallel object

在文件 SGObject.cpp209 行定义.

§ get_global_version()

Version * get_global_version ( )
inherited

get the version object

返回
version object

在文件 SGObject.cpp222 行定义.

§ get_gradient()

virtual CMap<TParameter*, SGVector<float64_t> >* get_gradient ( CMap< TParameter *, CSGObject *> *  parameters)
virtualinherited

get the gradient

参数
parametersparameter's dictionary
返回
map of gradient. Keys are names of parameters, values are values of derivative with respect to that parameter.

实现了 CDifferentiableFunction.

在文件 InferenceMethod.h220 行定义.

§ get_inference_type()

virtual EInferenceType get_inference_type ( ) const
virtual

return what type of inference we are

返回
inference type EXACT

重载 CInferenceMethod .

在文件 ExactInferenceMethod.h70 行定义.

§ get_kernel()

virtual CKernel* get_kernel ( )
virtualinherited

get kernel

返回
kernel

在文件 InferenceMethod.h258 行定义.

§ get_labels()

virtual CLabels* get_labels ( )
virtualinherited

get labels

返回
labels

在文件 InferenceMethod.h292 行定义.

§ get_marginal_likelihood_estimate()

float64_t get_marginal_likelihood_estimate ( int32_t  num_importance_samples = 1,
float64_t  ridge_size = 1e-15 
)
inherited

Computes an unbiased estimate of the log-marginal-likelihood,

\[ log(p(y|X,\theta)), \]

where \(y\) are the labels, \(X\) are the features (omitted from in the following expressions), and \(\theta\) represent hyperparameters.

This is done via an approximation to the posterior \(q(f|y, \theta)\approx p(f|y, \theta)\), which is computed by the underlying CInferenceMethod instance (if implemented, otherwise error), and then using an importance sample estimator

\[ p(y|\theta)=\int p(y|f)p(f|\theta)df =\int p(y|f)\frac{p(f|\theta)}{q(f|y, \theta)}q(f|y, \theta)df \approx\frac{1}{n}\sum_{i=1}^n p(y|f^{(i)})\frac{p(f^{(i)}|\theta)} {q(f^{(i)}|y, \theta)}, \]

where \( f^{(i)} \) are samples from the posterior approximation \( q(f|y, \theta) \). The resulting estimator has a low variance if \( q(f|y, \theta) \) is a good approximation. It has large variance otherwise (while still being consistent).

参数
num_importance_samplesthe number of importance samples \(n\) from \( q(f|y, \theta) \).
ridge_sizescalar that is added to the diagonal of the involved Gaussian distribution's covariance of GP prior and posterior approximation to stabilise things. Increase if Cholesky factorization fails.
返回
unbiased estimate of the log of the marginal likelihood function \( log(p(y|\theta)) \)

在文件 InferenceMethod.cpp79 行定义.

§ get_mean()

virtual CMeanFunction* get_mean ( )
virtualinherited

get mean

返回
mean

在文件 InferenceMethod.h275 行定义.

§ get_model()

CLikelihoodModel* get_model ( )
inherited

get likelihood model

返回
likelihood

在文件 InferenceMethod.h309 行定义.

§ get_modelsel_names()

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

在文件 SGObject.cpp1060 行定义.

§ get_modsel_param_descr()

char * get_modsel_param_descr ( const char *  param_name)
inherited

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

参数
param_namename of the parameter
返回
description of the parameter

在文件 SGObject.cpp1084 行定义.

§ get_modsel_param_index()

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

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

在文件 SGObject.cpp1097 行定义.

§ get_name()

virtual const char* get_name ( ) const
virtual

returns the name of the inference method

返回
name Exact

实现了 CSGObject.

在文件 ExactInferenceMethod.h76 行定义.

§ get_negative_log_marginal_likelihood()

float64_t get_negative_log_marginal_likelihood ( )
virtual

get negative log marginal likelihood

返回
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.

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp78 行定义.

§ get_negative_log_marginal_likelihood_derivatives()

CMap< TParameter *, SGVector< float64_t > > * get_negative_log_marginal_likelihood_derivatives ( CMap< TParameter *, CSGObject *> *  parameters)
virtualinherited

get log marginal likelihood gradient

返回
vector of the marginal likelihood function gradient with respect to hyperparameters (under the current approximation to the posterior \(q(f|y)\approx p(f|y)\):

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

where \(y\) are the labels, \(X\) are the features, and \(\theta\) represent hyperparameters.

在文件 InferenceMethod.cpp138 行定义.

§ get_posterior_covariance()

SGMatrix< float64_t > get_posterior_covariance ( )
virtual

returns covariance matrix \(\Sigma\) of the posterior Gaussian distribution \(\mathcal{N}(\mu,\Sigma)\)

\[ p(f|y) = \mathcal{N}(\mu,\Sigma) \]

返回
covariance matrix

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp131 行定义.

§ get_posterior_mean()

SGVector< float64_t > get_posterior_mean ( )
virtual

returns mean vector \(\mu\) of the posterior Gaussian distribution \(\mathcal{N}(\mu,\Sigma)\)

\[ p(f|y) = \mathcal{N}(\mu,\Sigma) \]

返回
mean vector

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp123 行定义.

§ get_scale()

virtual float64_t get_scale ( ) const
virtualinherited

get kernel scale

返回
kernel scale

在文件 InferenceMethod.h326 行定义.

§ get_value()

virtual SGVector<float64_t> get_value ( )
virtualinherited

get the function value

返回
vector that represents the function value

实现了 CDifferentiableFunction.

在文件 InferenceMethod.h230 行定义.

§ is_generic()

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.

参数
genericset to the type of the generic if returning TRUE
返回
TRUE if a class template.

在文件 SGObject.cpp228 行定义.

§ load_all_file_parameters()

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)

参数
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
返回
(sorted) array of created TParameter instances with file data

在文件 SGObject.cpp633 行定义.

§ load_file_parameters()

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

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

在文件 SGObject.cpp474 行定义.

§ load_serializable()

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!

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

在文件 SGObject.cpp305 行定义.

§ load_serializable_post()

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.

异常
ShogunExceptionWill be thrown if an error occurres.

CWeightedDegreePositionStringKernel, CKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.

在文件 SGObject.cpp989 行定义.

§ load_serializable_pre()

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.

异常
ShogunExceptionWill be thrown if an error occurres.

CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.

在文件 SGObject.cpp984 行定义.

§ map_parameters()

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

参数
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

在文件 SGObject.cpp671 行定义.

§ migrate()

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

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

在文件 SGObject.cpp878 行定义.

§ one_to_one_migration_prepare()

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)

参数
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

在文件 SGObject.cpp818 行定义.

§ print_modsel_params()

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

在文件 SGObject.cpp1036 行定义.

§ print_serializable()

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

prints registered parameters out

参数
prefixprefix for members

在文件 SGObject.cpp240 行定义.

§ save_serializable()

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

Save this object to file.

参数
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)
返回
TRUE if done, otherwise FALSE

在文件 SGObject.cpp246 行定义.

§ save_serializable_post()

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.

异常
ShogunExceptionWill be thrown if an error occurres.

CKernel 重载.

在文件 SGObject.cpp999 行定义.

§ save_serializable_pre()

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.

异常
ShogunExceptionWill be thrown if an error occurres.

CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.

在文件 SGObject.cpp994 行定义.

§ set_features()

virtual void set_features ( CFeatures feat)
virtualinherited

set features

参数
featfeatures to set

在文件 InferenceMethod.h247 行定义.

§ set_generic() [1/16]

void set_generic ( )
inherited

在文件 SGObject.cpp41 行定义.

§ set_generic() [2/16]

void set_generic ( )
inherited

在文件 SGObject.cpp46 行定义.

§ set_generic() [3/16]

void set_generic ( )
inherited

在文件 SGObject.cpp51 行定义.

§ set_generic() [4/16]

void set_generic ( )
inherited

在文件 SGObject.cpp56 行定义.

§ set_generic() [5/16]

void set_generic ( )
inherited

在文件 SGObject.cpp61 行定义.

§ set_generic() [6/16]

void set_generic ( )
inherited

在文件 SGObject.cpp66 行定义.

§ set_generic() [7/16]

void set_generic ( )
inherited

在文件 SGObject.cpp71 行定义.

§ set_generic() [8/16]

void set_generic ( )
inherited

在文件 SGObject.cpp76 行定义.

§ set_generic() [9/16]

void set_generic ( )
inherited

在文件 SGObject.cpp81 行定义.

§ set_generic() [10/16]

void set_generic ( )
inherited

在文件 SGObject.cpp86 行定义.

§ set_generic() [11/16]

void set_generic ( )
inherited

在文件 SGObject.cpp91 行定义.

§ set_generic() [12/16]

void set_generic ( )
inherited

在文件 SGObject.cpp96 行定义.

§ set_generic() [13/16]

void set_generic ( )
inherited

在文件 SGObject.cpp101 行定义.

§ set_generic() [14/16]

void set_generic ( )
inherited

在文件 SGObject.cpp106 行定义.

§ set_generic() [15/16]

void set_generic ( )
inherited

在文件 SGObject.cpp111 行定义.

§ set_generic() [16/16]

void set_generic ( )
inherited

set generic type to T

§ set_global_io()

void set_global_io ( SGIO io)
inherited

set the io object

参数
ioio object to use

在文件 SGObject.cpp167 行定义.

§ set_global_parallel()

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

参数
parallelparallel object to use

在文件 SGObject.cpp180 行定义.

§ set_global_version()

void set_global_version ( Version version)
inherited

set the version object

参数
versionversion object to use

在文件 SGObject.cpp215 行定义.

§ set_kernel()

virtual void set_kernel ( CKernel kern)
virtualinherited

set kernel

参数
kernkernel to set

在文件 InferenceMethod.h264 行定义.

§ set_labels()

virtual void set_labels ( CLabels lab)
virtualinherited

set labels

参数
lablabel to set

在文件 InferenceMethod.h298 行定义.

§ set_mean()

virtual void set_mean ( CMeanFunction m)
virtualinherited

set mean

参数
mmean function to set

在文件 InferenceMethod.h281 行定义.

§ set_model()

virtual void set_model ( CLikelihoodModel mod)
virtualinherited

set likelihood model

参数
modmodel to set

在文件 InferenceMethod.h315 行定义.

§ set_scale()

virtual void set_scale ( float64_t  scale)
virtualinherited

set kernel scale

参数
scalescale to be set

在文件 InferenceMethod.h332 行定义.

§ shallow_copy()

virtual CSGObject* shallow_copy ( ) const
virtualinherited

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

CGaussianKernel 重载.

在文件 SGObject.h117 行定义.

§ supports_binary()

virtual bool supports_binary ( ) const
virtualinherited

whether combination of inference method and given likelihood function supports binary classification

返回
false

CLaplacianInferenceMethod , 以及 CEPInferenceMethod 重载.

在文件 InferenceMethod.h346 行定义.

§ supports_multiclass()

virtual bool supports_multiclass ( ) const
virtualinherited

whether combination of inference method and given likelihood function supports multiclass classification

返回
false

在文件 InferenceMethod.h353 行定义.

§ supports_regression()

virtual bool supports_regression ( ) const
virtual
返回
whether combination of exact inference method and given likelihood function supports regression

重载 CInferenceMethod .

在文件 ExactInferenceMethod.h155 行定义.

§ unset_generic()

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

在文件 SGObject.cpp235 行定义.

§ update()

void update ( )
virtual

update all matrices

重载 CInferenceMethod .

在文件 ExactInferenceMethod.cpp41 行定义.

§ update_alpha()

void update_alpha ( )
protectedvirtual

update alpha matrix

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp158 行定义.

§ update_chol()

void update_chol ( )
protectedvirtual

update Cholesky matrix

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp139 行定义.

§ update_cov()

void update_cov ( )
protectedvirtual

update covariance matrix of the posterior Gaussian

在文件 ExactInferenceMethod.cpp201 行定义.

§ update_deriv()

void update_deriv ( )
protectedvirtual

update matrices which are required to compute negative log marginal likelihood derivatives wrt hyperparameter

实现了 CInferenceMethod.

在文件 ExactInferenceMethod.cpp220 行定义.

§ update_mean()

void update_mean ( )
protectedvirtual

update mean vector of the posterior Gaussian

在文件 ExactInferenceMethod.cpp184 行定义.

§ update_parameter_hash()

bool update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination.

返回
bool if parameter combination has changed since last update.

在文件 SGObject.cpp187 行定义.

§ update_train_kernel()

void update_train_kernel ( )
protectedvirtualinherited

update train kernel matrix

CFITCInferenceMethod 重载.

在文件 InferenceMethod.cpp279 行定义.

类成员变量说明

§ io

SGIO* io
inherited

io

在文件 SGObject.h473 行定义.

§ m_alpha

SGVector<float64_t> m_alpha
protectedinherited

alpha vector used in process mean calculation

在文件 InferenceMethod.h441 行定义.

§ m_features

CFeatures* m_features
protectedinherited

features to use

在文件 InferenceMethod.h435 行定义.

§ m_gradient_parameters

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

在文件 SGObject.h488 行定义.

§ m_hash

uint32_t m_hash
inherited

Hash of parameter values

在文件 SGObject.h494 行定义.

§ m_kernel

CKernel* m_kernel
protectedinherited

covariance function

在文件 InferenceMethod.h426 行定义.

§ m_ktrtr

SGMatrix<float64_t> m_ktrtr
protectedinherited

kernel matrix from features (non-scalled by inference scalling)

在文件 InferenceMethod.h450 行定义.

§ m_L

SGMatrix<float64_t> m_L
protectedinherited

upper triangular factor of Cholesky decomposition

在文件 InferenceMethod.h444 行定义.

§ m_labels

CLabels* m_labels
protectedinherited

labels of features

在文件 InferenceMethod.h438 行定义.

§ m_mean

CMeanFunction* m_mean
protectedinherited

mean function

在文件 InferenceMethod.h429 行定义.

§ m_model

CLikelihoodModel* m_model
protectedinherited

likelihood function to use

在文件 InferenceMethod.h432 行定义.

§ m_model_selection_parameters

Parameter* m_model_selection_parameters
inherited

model selection parameters

在文件 SGObject.h485 行定义.

§ m_parameter_map

ParameterMap* m_parameter_map
inherited

map for different parameter versions

在文件 SGObject.h491 行定义.

§ m_parameters

Parameter* m_parameters
inherited

parameters

在文件 SGObject.h482 行定义.

§ m_scale

float64_t m_scale
protectedinherited

kernel scale

在文件 InferenceMethod.h447 行定义.

§ parallel

Parallel* parallel
inherited

parallel

在文件 SGObject.h476 行定义.

§ version

Version* version
inherited

version

在文件 SGObject.h479 行定义.


该类的文档由以下文件生成:

SHOGUN Machine Learning Toolbox - Documentation