SHOGUN  4.0.0
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CStochasticGBMachine类 参考

详细描述

This class implements the stochastic gradient boosting algorithm for ensemble learning invented by Jerome H. Friedman. This class works with a variety of loss functions like squared loss, exponential loss, Huber loss etc which can be accessed through Shogun's CLossFunction interface (cf. http://www.shogun-toolbox.org/doc/en/latest/classshogun_1_1CLossFunction.html). Additionally, it can create an ensemble of any regressor class derived from the CMachine class (cf. http://www.shogun-toolbox.org/doc/en/latest/classshogun_1_1CMachine.html). For one dimensional optimization, this class uses the backtracking linesearch accessed via Shogun's L-BFGS class. A concise description of the algorithm implemented can be found in the following link : http://en.wikipedia.org/wiki/Gradient_boosting#Algorithm.

在文件 StochasticGBMachine.h52 行定义.

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

Public 成员函数

 CStochasticGBMachine (CMachine *machine=NULL, CLossFunction *loss=NULL, int32_t num_iterations=100, float64_t learning_rate=1.0, float64_t subset_fraction=0.6)
 
virtual ~CStochasticGBMachine ()
 
virtual const char * get_name () const
 
void set_machine (CMachine *machine)
 
CMachineget_machine () const
 
virtual void set_loss_function (CLossFunction *f)
 
virtual CLossFunctionget_loss_function () const
 
void set_num_iterations (int32_t iter)
 
int32_t get_num_iterations () const
 
void set_subset_fraction (float64_t frac)
 
float64_t get_subset_fraction () const
 
void set_learning_rate (float64_t lr)
 
float64_t get_learning_rate () const
 
virtual CRegressionLabelsapply_regression (CFeatures *data=NULL)
 
virtual bool train (CFeatures *data=NULL)
 
virtual CLabelsapply (CFeatures *data=NULL)
 
virtual CBinaryLabelsapply_binary (CFeatures *data=NULL)
 
virtual CMulticlassLabelsapply_multiclass (CFeatures *data=NULL)
 
virtual CStructuredLabelsapply_structured (CFeatures *data=NULL)
 
virtual CLatentLabelsapply_latent (CFeatures *data=NULL)
 
virtual void set_labels (CLabels *lab)
 
virtual CLabelsget_labels ()
 
void set_max_train_time (float64_t t)
 
float64_t get_max_train_time ()
 
virtual EMachineType get_classifier_type ()
 
void set_solver_type (ESolverType st)
 
ESolverType get_solver_type ()
 
virtual void set_store_model_features (bool store_model)
 
virtual bool train_locked (SGVector< index_t > indices)
 
virtual float64_t apply_one (int32_t i)
 
virtual CLabelsapply_locked (SGVector< index_t > indices)
 
virtual CBinaryLabelsapply_locked_binary (SGVector< index_t > indices)
 
virtual CRegressionLabelsapply_locked_regression (SGVector< index_t > indices)
 
virtual CMulticlassLabelsapply_locked_multiclass (SGVector< index_t > indices)
 
virtual CStructuredLabelsapply_locked_structured (SGVector< index_t > indices)
 
virtual CLatentLabelsapply_locked_latent (SGVector< index_t > indices)
 
virtual void data_lock (CLabels *labs, CFeatures *features)
 
virtual void post_lock (CLabels *labs, CFeatures *features)
 
virtual void data_unlock ()
 
virtual bool supports_locking () const
 
bool is_data_locked () const
 
virtual EProblemType get_machine_problem_type () 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 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 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 bool train_machine (CFeatures *data=NULL)
 
float64_t compute_multiplier (CRegressionLabels *f, CRegressionLabels *hm)
 
CMachinefit_model (CDenseFeatures< float64_t > *feats, CRegressionLabels *labels)
 
CRegressionLabelscompute_pseudo_residuals (CRegressionLabels *inter_f)
 
void apply_subset (CDenseFeatures< float64_t > *f, CLabels *interf)
 
void initialize_learners ()
 
float64_t get_gamma (void *instance)
 
void init ()
 
virtual void store_model_features ()
 
virtual bool is_label_valid (CLabels *lab) const
 
virtual bool train_require_labels () const
 
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 float64_t lbfgs_evaluate (void *obj, const float64_t *parameters, float64_t *gradient, const int dim, const float64_t step)
 

Protected 属性

CMachinem_machine
 
CLossFunctionm_loss
 
int32_t m_num_iter
 
float64_t m_subset_frac
 
float64_t m_learning_rate
 
CDynamicObjectArraym_weak_learners
 
CDynamicArray< float64_t > * m_gamma
 
float64_t m_max_train_time
 
CLabelsm_labels
 
ESolverType m_solver_type
 
bool m_store_model_features
 
bool m_data_locked
 

构造及析构函数说明

CStochasticGBMachine ( CMachine machine = NULL,
CLossFunction loss = NULL,
int32_t  num_iterations = 100,
float64_t  learning_rate = 1.0,
float64_t  subset_fraction = 0.6 
)

Constructor

参数
machineThe class of machine which will constitute the ensemble
lossloss function
num_iterationsnumber of iterations of boosting
subset_fractionfraction of trainining vectors to be chosen randomly w/o replacement
learning_rateshrinkage factor

在文件 StochasticGBMachine.cpp37 行定义.

~CStochasticGBMachine ( )
virtual

Destructor

在文件 StochasticGBMachine.cpp60 行定义.

成员函数说明

CLabels * apply ( CFeatures data = NULL)
virtualinherited

apply machine to data if data is not specified apply to the current features

参数
data(test)data to be classified
返回
classified labels

在文件 Machine.cpp160 行定义.

CBinaryLabels * apply_binary ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of binary classification problem

CKernelMachine, COnlineLinearMachine, CWDSVMOcas, CNeuralNetwork, CLinearMachine, CGaussianProcessClassification, CDomainAdaptationSVMLinear, CPluginEstimate , 以及 CBaggingMachine 重载.

在文件 Machine.cpp216 行定义.

CLatentLabels * apply_latent ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of latent problem

CLinearLatentMachine 重载.

在文件 Machine.cpp240 行定义.

CLabels * apply_locked ( SGVector< index_t indices)
virtualinherited

Applies a locked machine on a set of indices. Error if machine is not locked

参数
indicesindex vector (of locked features) that is predicted

在文件 Machine.cpp195 行定义.

CBinaryLabels * apply_locked_binary ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for binary problems

CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.cpp246 行定义.

CLatentLabels * apply_locked_latent ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for latent problems

在文件 Machine.cpp274 行定义.

CMulticlassLabels * apply_locked_multiclass ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for multiclass problems

在文件 Machine.cpp260 行定义.

CRegressionLabels * apply_locked_regression ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for regression problems

CKernelMachine 重载.

在文件 Machine.cpp253 行定义.

CStructuredLabels * apply_locked_structured ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for structured problems

在文件 Machine.cpp267 行定义.

CMulticlassLabels * apply_multiclass ( CFeatures data = NULL)
virtualinherited
virtual float64_t apply_one ( int32_t  i)
virtualinherited
CRegressionLabels * apply_regression ( CFeatures data = NULL)
virtual

apply_regression

参数
datatest data
返回
Regression labels

重载 CMachine .

在文件 StochasticGBMachine.cpp142 行定义.

CStructuredLabels * apply_structured ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of SO classification problem

CLinearStructuredOutputMachine 重载.

在文件 Machine.cpp234 行定义.

void apply_subset ( CDenseFeatures< float64_t > *  f,
CLabels interf 
)
protected

add randomized subset to relevant parameters

参数
ftraining data
interfintermediate boosted model labels for training data

在文件 StochasticGBMachine.cpp275 行定义.

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.cpp1243 行定义.

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.cpp1360 行定义.

float64_t compute_multiplier ( CRegressionLabels f,
CRegressionLabels hm 
)
protected

compute gamma values

参数
flabels from the intermediate model
hmlabels from the newly trained base model
返回
gamma - the scalar weights given to individual weak learners in the ensemble model

在文件 StochasticGBMachine.cpp229 行定义.

CRegressionLabels * compute_pseudo_residuals ( CRegressionLabels inter_f)
protected

compute pseudo_residuals

参数
inter_fintermediate boosted model labels for training data
返回
pseudo_residuals

在文件 StochasticGBMachine.cpp262 行定义.

void data_lock ( CLabels labs,
CFeatures features 
)
virtualinherited

Locks the machine on given labels and data. After this call, only train_locked and apply_locked may be called

Only possible if supports_locking() returns true

参数
labslabels used for locking
featuresfeatures used for locking

CKernelMachine 重载.

在文件 Machine.cpp120 行定义.

void data_unlock ( )
virtualinherited

Unlocks a locked machine and restores previous state

CKernelMachine 重载.

在文件 Machine.cpp151 行定义.

CSGObject * deep_copy ( ) const
virtualinherited

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

在文件 SGObject.cpp200 行定义.

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.

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

在文件 SGObject.cpp1264 行定义.

CMachine * fit_model ( CDenseFeatures< float64_t > *  feats,
CRegressionLabels labels 
)
protected

train base model

参数
featstraining data
labelstraining labels
返回
trained base model

在文件 StochasticGBMachine.cpp245 行定义.

EMachineType get_classifier_type ( )
virtualinherited
float64_t get_gamma ( void *  instance)
protected

apply lbfgs to get gamma

参数
instancestores parameters to be passed to lbfgs_evaluate
返回
gamma

在文件 StochasticGBMachine.cpp301 行定义.

SGIO * get_global_io ( )
inherited

get the io object

返回
io object

在文件 SGObject.cpp237 行定义.

Parallel * get_global_parallel ( )
inherited

get the parallel object

返回
parallel object

在文件 SGObject.cpp278 行定义.

Version * get_global_version ( )
inherited

get the version object

返回
version object

在文件 SGObject.cpp291 行定义.

CLabels * get_labels ( )
virtualinherited

get labels

返回
labels

在文件 Machine.cpp84 行定义.

float64_t get_learning_rate ( ) const

get learning rate

返回
learning rate

在文件 StochasticGBMachine.cpp137 行定义.

CLossFunction * get_loss_function ( ) const
virtual

get loss function

返回
loss function

在文件 StochasticGBMachine.cpp98 行定义.

CMachine * get_machine ( ) const

get machine

返回
machine

在文件 StochasticGBMachine.cpp79 行定义.

virtual EProblemType get_machine_problem_type ( ) const
virtualinherited

returns type of problem machine solves

CNeuralNetwork, CRandomForest, CCHAIDTree, CCARTree , 以及 CBaseMulticlassMachine 重载.

在文件 Machine.h299 行定义.

float64_t get_max_train_time ( )
inherited

get maximum training time

返回
maximum training time

在文件 Machine.cpp95 行定义.

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

在文件 SGObject.cpp1135 行定义.

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.cpp1159 行定义.

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.cpp1172 行定义.

virtual const char* get_name ( ) const
virtual

get name

返回
StochasticGBMachine

重载 CMachine .

在文件 StochasticGBMachine.h73 行定义.

int32_t get_num_iterations ( ) const

get number of iterations

返回
number of iterations

在文件 StochasticGBMachine.cpp113 行定义.

ESolverType get_solver_type ( )
inherited

get solver type

返回
solver

在文件 Machine.cpp110 行定义.

float64_t get_subset_fraction ( ) const

get subset fraction

返回
subset fraction

在文件 StochasticGBMachine.cpp125 行定义.

void init ( )
protected

initialize

在文件 StochasticGBMachine.cpp385 行定义.

void initialize_learners ( )
protected

reset arrays of weak learners and gamma values

在文件 StochasticGBMachine.cpp290 行定义.

bool is_data_locked ( ) const
inherited
返回
whether this machine is locked

在文件 Machine.h296 行定义.

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.cpp297 行定义.

virtual bool is_label_valid ( CLabels lab) const
protectedvirtualinherited

check whether the labels is valid.

Subclasses can override this to implement their check of label types.

参数
labthe labels being checked, guaranteed to be non-NULL

CNeuralNetwork, CCARTree, CCHAIDTree, CGaussianProcessRegression , 以及 CBaseMulticlassMachine 重载.

在文件 Machine.h348 行定义.

float64_t lbfgs_evaluate ( void *  obj,
const float64_t parameters,
float64_t gradient,
const int  dim,
const float64_t  step 
)
staticprotected

call-back evaluate method for lbfgs

参数
objobject parameters required for loss calculation
parameterscurrent state of variables of target function
gradientstores gradient computed by this method
dimdimensions
stepstep in linesearch

在文件 StochasticGBMachine.cpp313 行定义.

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.cpp704 行定义.

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.cpp545 行定义.

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.cpp374 行定义.

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 occurs.

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

在文件 SGObject.cpp1062 行定义.

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 occurs.

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

在文件 SGObject.cpp1057 行定义.

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.cpp742 行定义.

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.cpp949 行定义.

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.cpp889 行定义.

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

在文件 SGObject.cpp263 行定义.

virtual void post_lock ( CLabels labs,
CFeatures features 
)
virtualinherited

post lock

CMultitaskLinearMachine 重载.

在文件 Machine.h287 行定义.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

在文件 SGObject.cpp1111 行定义.

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

prints registered parameters out

参数
prefixprefix for members

在文件 SGObject.cpp309 行定义.

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.cpp315 行定义.

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 occurs.

CKernel 重载.

在文件 SGObject.cpp1072 行定义.

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 occurs.

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.cpp1067 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp42 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp47 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp52 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp57 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp62 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp67 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp72 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp77 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp82 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp87 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp92 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp97 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp102 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp107 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp112 行定义.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO io)
inherited

set the io object

参数
ioio object to use

在文件 SGObject.cpp230 行定义.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

参数
parallelparallel object to use

在文件 SGObject.cpp243 行定义.

void set_global_version ( Version version)
inherited

set the version object

参数
versionversion object to use

在文件 SGObject.cpp284 行定义.

void set_labels ( CLabels lab)
virtualinherited

set labels

参数
lablabels

CNeuralNetwork, CGaussianProcessMachine, CCARTree, CStructuredOutputMachine, CRelaxedTree , 以及 CMulticlassMachine 重载.

在文件 Machine.cpp73 行定义.

void set_learning_rate ( float64_t  lr)

set learning rate

参数
lrlearning rate

在文件 StochasticGBMachine.cpp130 行定义.

void set_loss_function ( CLossFunction f)
virtual

set loss function

参数
floss function

在文件 StochasticGBMachine.cpp88 行定义.

void set_machine ( CMachine machine)

set machine

参数
machinemachine

在文件 StochasticGBMachine.cpp68 行定义.

void set_max_train_time ( float64_t  t)
inherited

set maximum training time

参数
tmaximimum training time

在文件 Machine.cpp90 行定义.

void set_num_iterations ( int32_t  iter)

set number of iterations

参数
iternumber of iterations

在文件 StochasticGBMachine.cpp107 行定义.

void set_solver_type ( ESolverType  st)
inherited

set solver type

参数
stsolver type

在文件 Machine.cpp105 行定义.

void set_store_model_features ( bool  store_model)
virtualinherited

Setter for store-model-features-after-training flag

参数
store_modelwhether model should be stored after training

在文件 Machine.cpp115 行定义.

void set_subset_fraction ( float64_t  frac)

set subset fraction

参数
fracsubset fraction (should lie between 0 and 1)

在文件 StochasticGBMachine.cpp118 行定义.

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.cpp194 行定义.

virtual void store_model_features ( )
protectedvirtualinherited

Stores feature data of underlying model. After this method has been called, it is possible to change the machine's feature data and call apply(), which is then performed on the training feature data that is part of the machine's model.

Base method, has to be implemented in order to allow cross-validation and model selection.

NOT IMPLEMENTED! Has to be done in subclasses

CKernelMachine, CKNN, CLinearMulticlassMachine, CTreeMachine< T >, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< id3TreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CTreeMachine< CARTreeNodeData >, CTreeMachine< C45TreeNodeData >, CTreeMachine< CHAIDTreeNodeData >, CTreeMachine< NbodyTreeNodeData >, CLinearMachine, CGaussianProcessMachine, CHierarchical, CDistanceMachine, CKernelMulticlassMachine , 以及 CLinearStructuredOutputMachine 重载.

在文件 Machine.h335 行定义.

virtual bool supports_locking ( ) const
virtualinherited
返回
whether this machine supports locking

CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.h293 行定义.

bool train ( CFeatures data = NULL)
virtualinherited

train machine

参数
datatraining data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data). If flag is set, model features will be stored after training.
返回
whether training was successful

CRelaxedTree, CAutoencoder, CSGDQN , 以及 COnlineSVMSGD 重载.

在文件 Machine.cpp47 行定义.

virtual bool train_locked ( SGVector< index_t indices)
virtualinherited

Trains a locked machine on a set of indices. Error if machine is not locked

NOT IMPLEMENTED

参数
indicesindex vector (of locked features) that is used for training
返回
whether training was successful

CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.h239 行定义.

bool train_machine ( CFeatures data = NULL)
protectedvirtual

train machine

参数
datatraining data
返回
true

重载 CMachine .

在文件 StochasticGBMachine.cpp170 行定义.

virtual bool train_require_labels ( ) const
protectedvirtualinherited

returns whether machine require labels for training

COnlineLinearMachine, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree , 以及 CLibSVMOneClass 重载.

在文件 Machine.h354 行定义.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

在文件 SGObject.cpp304 行定义.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

在文件 SGObject.cpp250 行定义.

类成员变量说明

SGIO* io
inherited

io

在文件 SGObject.h496 行定义.

bool m_data_locked
protectedinherited

whether data is locked

在文件 Machine.h370 行定义.

CDynamicArray<float64_t>* m_gamma
protected

gamma - weak learner weights

在文件 StochasticGBMachine.h223 行定义.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

在文件 SGObject.h511 行定义.

uint32_t m_hash
inherited

Hash of parameter values

在文件 SGObject.h517 行定义.

CLabels* m_labels
protectedinherited

labels

在文件 Machine.h361 行定义.

float64_t m_learning_rate
protected

learning_rate

在文件 StochasticGBMachine.h217 行定义.

CLossFunction* m_loss
protected

loss function

在文件 StochasticGBMachine.h208 行定义.

CMachine* m_machine
protected

machine to be used for GBoosting

在文件 StochasticGBMachine.h205 行定义.

float64_t m_max_train_time
protectedinherited

maximum training time

在文件 Machine.h358 行定义.

Parameter* m_model_selection_parameters
inherited

model selection parameters

在文件 SGObject.h508 行定义.

int32_t m_num_iter
protected

num of iterations

在文件 StochasticGBMachine.h211 行定义.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

在文件 SGObject.h514 行定义.

Parameter* m_parameters
inherited

parameters

在文件 SGObject.h505 行定义.

ESolverType m_solver_type
protectedinherited

solver type

在文件 Machine.h364 行定义.

bool m_store_model_features
protectedinherited

whether model features should be stored after training

在文件 Machine.h367 行定义.

float64_t m_subset_frac
protected

subset fraction

在文件 StochasticGBMachine.h214 行定义.

CDynamicObjectArray* m_weak_learners
protected

array of weak learners

在文件 StochasticGBMachine.h220 行定义.

Parallel* parallel
inherited

parallel

在文件 SGObject.h499 行定义.

Version* version
inherited

version

在文件 SGObject.h502 行定义.


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