详细描述

Balanced Conditional Probability Tree.

The tree is constructed to trade-off the existing regressor's prediction and the balance (depth) of the tree. The parameter alpha in [0,1] control the trade-off.

when alpha = 1, best efforts are made to ensure the tree is balanced
when alpha = 0, the balance of tree is complete ignored

more balanced tree means better computational efficiency, but usually worse performance. See the following paper for more details:

Alina Beygelzimer, John Langford, Yuri Lifshits, Gregory Sorkin, Alex Strehl. Conditional Probability Tree Estimation Analysis and Algorithms. UAI 2009.

在文件 BalancedConditionalProbabilityTree.h 第 37 行定义.

类 CBalancedConditionalProbabilityTree 继承关系图:

[图例]

Public 类型
typedef CTreeMachineNode < ConditionalProbabilityTreeNodeData >	node_t

typedef CBinaryTreeMachineNode < ConditionalProbabilityTreeNodeData >	bnode_t

Public 成员函数
	CBalancedConditionalProbabilityTree ()

virtual	~CBalancedConditionalProbabilityTree ()

virtual const char *	get_name () const

void	set_alpha (float64_t alpha)

float64_t	get_alpha () const

void	set_num_passes (int32_t num_passes)

int32_t	get_num_passes () const

void	set_features (CStreamingDenseFeatures< float32_t > *feats)

virtual CMulticlassLabels *	apply_multiclass (CFeatures *data=NULL)

virtual int32_t	apply_multiclass_example (SGVector< float32_t > ex)

void	print_tree ()

void	set_root (CTreeMachineNode< ConditionalProbabilityTreeNodeData > *root)

CTreeMachineNode < ConditionalProbabilityTreeNodeData > *	get_root ()

CTreeMachine *	clone_tree ()

int32_t	get_num_machines () const

virtual EProblemType	get_machine_problem_type () const

virtual bool	is_label_valid (CLabels *lab) const

virtual bool	train (CFeatures *data=NULL)

virtual CLabels *	apply (CFeatures *data=NULL)

virtual CBinaryLabels *	apply_binary (CFeatures *data=NULL)

virtual CRegressionLabels *	apply_regression (CFeatures *data=NULL)

virtual CStructuredLabels *	apply_structured (CFeatures *data=NULL)

virtual CLatentLabels *	apply_latent (CFeatures *data=NULL)

virtual void	set_labels (CLabels *lab)

virtual CLabels *	get_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 CLabels *	apply_locked (SGVector< index_t > indices)

virtual CBinaryLabels *	apply_locked_binary (SGVector< index_t > indices)

virtual CRegressionLabels *	apply_locked_regression (SGVector< index_t > indices)

virtual CMulticlassLabels *	apply_locked_multiclass (SGVector< index_t > indices)

virtual CStructuredLabels *	apply_locked_structured (SGVector< index_t > indices)

virtual CLatentLabels *	apply_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 CSGObject *	shallow_copy () const

virtual CSGObject *	deep_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="")

virtual bool	load_serializable (CSerializableFile file, const char prefix="")

void	set_global_io (SGIO *io)

SGIO *	get_global_io ()

void	set_global_parallel (Parallel *parallel)

Parallel *	get_global_parallel ()

void	set_global_version (Version *version)

Version *	get_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 CSGObject *	clone ()

Public 属性
SGIO *	io

Parallel *	parallel

Version *	version

Parameter *	m_parameters

Parameter *	m_model_selection_parameters

Parameter *	m_gradient_parameters

uint32_t	m_hash

Protected 成员函数
virtual bool	which_subtree (bnode_t *node, SGVector< float32_t > ex)

virtual bool	train_require_labels () const

virtual bool	train_machine (CFeatures *data)

void	train_example (SGVector< float32_t > ex, int32_t label)

void	train_path (SGVector< float32_t > ex, bnode_t *node)

void	train_node (SGVector< float32_t > ex, float64_t label, bnode_t *node)

float64_t	predict_node (SGVector< float32_t > ex, bnode_t *node)

int32_t	create_machine (SGVector< float32_t > ex)

virtual bool	which_subtree (bnode_t *node, SGVector< float32_t > ex)=0

void	compute_conditional_probabilities (SGVector< float32_t > ex)

float64_t	accumulate_conditional_probability (bnode_t *leaf)

virtual void	store_model_features ()

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)

Protected 属性
int32_t	m_num_passes
	number of passes for online training 更多...

std::map< int32_t, bnode_t * >	m_leaves
	class => leaf mapping 更多...

CStreamingDenseFeatures < float32_t > *	m_feats
	online features 更多...

CTreeMachineNode < ConditionalProbabilityTreeNodeData > *	m_root

CDynamicObjectArray *	m_machines

float64_t	m_max_train_time

CLabels *	m_labels

ESolverType	m_solver_type

bool	m_store_model_features

bool	m_data_locked

成员类型定义说明

typedef CBinaryTreeMachineNode<ConditionalProbabilityTreeNodeData > bnode_t

inherited

bnode_t type- Tree node with max 2 possible children

在文件 TreeMachine.h 第 55 行定义.

typedef CTreeMachineNode<ConditionalProbabilityTreeNodeData > node_t

inherited

node_t type- Tree node with many possible children

在文件 TreeMachine.h 第 52 行定义.

构造及析构函数说明

CBalancedConditionalProbabilityTree ( )

constructor

在文件 BalancedConditionalProbabilityTree.cpp 第 15 行定义.

virtual ~CBalancedConditionalProbabilityTree ( )

virtual

destructor

在文件 BalancedConditionalProbabilityTree.h 第 44 行定义.

成员函数说明

float64_t accumulate_conditional_probability ( bnode_t * leaf )

protectedinherited

accumulate along the path to the root the conditional probability for a particular leaf node.

在文件 ConditionalProbabilityTree.cpp 第 80 行定义.

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.cpp 第 152 行定义.

CBinaryLabels * apply_binary ( CFeatures * data = NULL )

virtualinherited

apply machine to data in means of binary classification problem

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

在文件 Machine.cpp 第 208 行定义.

CLatentLabels * apply_latent ( CFeatures * data = NULL )

virtualinherited

apply machine to data in means of latent problem

被 CLinearLatentMachine 重载.

在文件 Machine.cpp 第 232 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

indices index vector (of locked features) that is predicted

在文件 Machine.cpp 第 187 行定义.

CBinaryLabels * apply_locked_binary ( SGVector< index_t > indices )

virtualinherited

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

被 CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.cpp 第 238 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.cpp 第 266 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.cpp 第 252 行定义.

CRegressionLabels * apply_locked_regression ( SGVector< index_t > indices )

virtualinherited

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

被 CKernelMachine 重载.

在文件 Machine.cpp 第 245 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.cpp 第 259 行定义.

CMulticlassLabels * apply_multiclass ( CFeatures * data = NULL )

virtualinherited

apply machine to data in means of multiclass classification problem

重载 CMachine .

在文件 ConditionalProbabilityTree.cpp 第 21 行定义.

int32_t apply_multiclass_example ( SGVector< float32_t > ex )

virtualinherited

apply machine one single example.

参数

ex	a vector to be applied

在文件 ConditionalProbabilityTree.cpp 第 49 行定义.

virtual float64_t apply_one ( int32_t i )

virtualinherited

applies to one vector

被 CKernelMachine, CRelaxedTree, CWDSVMOcas, COnlineLinearMachine, CLinearMachine, CMultitaskLinearMachine, CMulticlassMachine, CKNN, CDistanceMachine, CMultitaskLogisticRegression, CMultitaskLeastSquaresRegression, CScatterSVM, CGaussianNaiveBayes, CPluginEstimate , 以及 CFeatureBlockLogisticRegression 重载.

在文件 Machine.h 第 247 行定义.

CRegressionLabels * apply_regression ( CFeatures * data = NULL )

virtualinherited

apply machine to data in means of regression problem

被 CKernelMachine, CWDSVMOcas, COnlineLinearMachine, CNeuralNetwork, CCHAIDTree, CStochasticGBMachine, CCARTree, CLinearMachine, CGaussianProcessRegression , 以及 CBaggingMachine 重载.

在文件 Machine.cpp 第 214 行定义.

CStructuredLabels * apply_structured ( CFeatures * data = NULL )

virtualinherited

apply machine to data in means of SO classification problem

被 CLinearStructuredOutputMachine 重载.

在文件 Machine.cpp 第 226 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

dict	dictionary of parameters to be built.

在文件 SGObject.cpp 第 597 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.cpp 第 714 行定义.

CTreeMachine* clone_tree ( )

inherited

clone tree

返回: clone of entire tree

在文件 TreeMachine.h 第 97 行定义.

void compute_conditional_probabilities ( SGVector< float32_t > ex )

protectedinherited

compute conditional probabilities for ex along the whole tree for predicting

在文件 ConditionalProbabilityTree.cpp 第 60 行定义.

int32_t create_machine ( SGVector< float32_t > ex )

protectedinherited

create a new OnlineLinear machine for a node

参数

ex	the Example instance for training the new machine

在文件 ConditionalProbabilityTree.cpp 第 248 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

labs	labels used for locking
features	features used for locking

被 CKernelMachine 重载.

在文件 Machine.cpp 第 112 行定义.

void data_unlock ( )

virtualinherited

Unlocks a locked machine and restores previous state

被 CKernelMachine 重载.

在文件 Machine.cpp 第 143 行定义.

CSGObject * deep_copy ( ) const

virtualinherited

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

在文件 SGObject.cpp 第 198 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

other	object to compare with
accuracy	accuracy to use for comparison (optional)
tolerant	allows linient check on float equality (within accuracy)

返回: true if all parameters were equal, false if not

在文件 SGObject.cpp 第 618 行定义.

float64_t get_alpha ( ) const

get alpha

在文件 BalancedConditionalProbabilityTree.h 第 53 行定义.

EMachineType get_classifier_type ( )

virtualinherited

get classifier type

返回: classifier type NONE

被 CLaRank, CSVMLight, CDualLibQPBMSOSVM, CNeuralNetwork, CCCSOSVM, CLeastAngleRegression, CLDA, CKernelRidgeRegression, CLibLinearMTL, CBaggingMachine, CLibLinear, CGaussianProcessClassification, CKMeans, CLibSVR, CQDA, CGaussianNaiveBayes, CSVRLight, CMCLDA, CLinearRidgeRegression, CKNN, CScatterSVM, CGaussianProcessRegression, CSGDQN, CSVMSGD, CSVMOcas, COnlineSVMSGD, CLeastSquaresRegression, CMKLRegression, CDomainAdaptationSVMLinear, CMKLMulticlass, CWDSVMOcas, CHierarchical, CMKLOneClass, CLibSVM, CStochasticSOSVM, CMKLClassification, CDomainAdaptationSVM, CLPBoost, CPerceptron, CAveragedPerceptron, CFWSOSVM, CNewtonSVM, CLPM, CGMNPSVM, CSVMLightOneClass, CSVMLin, CMulticlassLibSVM, CLibSVMOneClass, CMPDSVM, CGPBTSVM, CGNPPSVM , 以及 CCPLEXSVM 重载.

在文件 Machine.cpp 第 92 行定义.

SGIO * get_global_io ( )

inherited

get the io object

返回: io object

在文件 SGObject.cpp 第 235 行定义.

Parallel * get_global_parallel ( )

inherited

get the parallel object

返回: parallel object

在文件 SGObject.cpp 第 277 行定义.

Version * get_global_version ( )

inherited

get the version object

返回: version object

在文件 SGObject.cpp 第 290 行定义.

CLabels * get_labels ( )

virtualinherited

get labels

返回: labels

在文件 Machine.cpp 第 76 行定义.

EProblemType get_machine_problem_type ( ) const

virtualinherited

get problem type

重载 CMachine .

被 CCHAIDTree , 以及 CCARTree 重载.

在文件 BaseMulticlassMachine.cpp 第 32 行定义.

float64_t get_max_train_time ( )

inherited

get maximum training time

返回: maximum training time

在文件 Machine.cpp 第 87 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.cpp 第 498 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_name name of the parameter

返回: description of the parameter

在文件 SGObject.cpp 第 522 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_name name of model selection parameter

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

在文件 SGObject.cpp 第 535 行定义.

virtual const char* get_name ( ) const

virtual

get name

重载 CConditionalProbabilityTree .

在文件 BalancedConditionalProbabilityTree.h 第 47 行定义.

int32_t get_num_machines ( ) const

inherited

get number of machines

返回: number of machines

在文件 BaseMulticlassMachine.cpp 第 27 行定义.

int32_t get_num_passes ( ) const

inherited

get number of passes

在文件 ConditionalProbabilityTree.h 第 55 行定义.

CTreeMachineNode<ConditionalProbabilityTreeNodeData >* get_root ( )

inherited

get root

返回: root the root node of the tree

在文件 TreeMachine.h 第 88 行定义.

ESolverType get_solver_type ( )

inherited

get solver type

返回: solver

在文件 Machine.cpp 第 102 行定义.

bool is_data_locked ( ) const

inherited

返回: whether this machine is locked

在文件 Machine.h 第 296 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

generic set to the type of the generic if returning TRUE

返回: TRUE if a class template.

在文件 SGObject.cpp 第 296 行定义.

bool is_label_valid ( CLabels * lab ) const

virtualinherited

check whether the labels is valid.

参数

lab	the labels being checked, guaranteed to be non-NULL

重载 CMachine .

被 CCARTree , 以及 CCHAIDTree 重载.

在文件 BaseMulticlassMachine.cpp 第 37 行定义.

bool load_serializable	(	CSerializableFile *	file,
		const char *	prefix = `""`
	)

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

file	where to load from
prefix	prefix for members

返回: TRUE if done, otherwise FALSE

在文件 SGObject.cpp 第 369 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

ShogunException will be thrown if an error occurs.

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

在文件 SGObject.cpp 第 426 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

ShogunException will be thrown if an error occurs.

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

在文件 SGObject.cpp 第 421 行定义.

bool parameter_hash_changed ( )

virtualinherited

返回: whether parameter combination has changed since last update

在文件 SGObject.cpp 第 262 行定义.

virtual void post_lock	(	CLabels *	labs,
		CFeatures *	features
	)

virtualinherited

post lock

被 CMultitaskLinearMachine 重载.

在文件 Machine.h 第 287 行定义.

float64_t predict_node	(	SGVector< float32_t >	ex,
		bnode_t *	node
	)

protectedinherited

predict a single node

参数

ex	the example being predicted
node	the node

在文件 ConditionalProbabilityTree.cpp 第 237 行定义.

void print_modsel_params ( )

inherited

prints all parameter registered for model selection and their type

在文件 SGObject.cpp 第 474 行定义.

void print_serializable ( const char * prefix = "" )

virtualinherited

prints registered parameters out

参数

prefix prefix for members

在文件 SGObject.cpp 第 308 行定义.

void print_tree ( )

inherited

print the tree structure for debug purpose

在文件 ConditionalProbabilityTree.cpp 第 144 行定义.

bool save_serializable	(	CSerializableFile *	file,
		const char *	prefix = `""`
	)

virtualinherited

Save this object to file.

参数

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

返回: TRUE if done, otherwise FALSE

在文件 SGObject.cpp 第 314 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

ShogunException will be thrown if an error occurs.

被 CKernel 重载.

在文件 SGObject.cpp 第 436 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

ShogunException will be thrown if an error occurs.

被 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.cpp 第 431 行定义.

void set_alpha ( float64_t alpha )

set alpha

在文件 BalancedConditionalProbabilityTree.cpp 第 21 行定义.

void set_features ( CStreamingDenseFeatures< float32_t > * feats )

inherited

set features

参数

feats features

在文件 ConditionalProbabilityTree.h 第 63 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 41 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 46 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 51 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 56 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 61 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 66 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 71 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 76 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 81 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 86 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 91 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 96 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 101 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 106 行定义.

void set_generic ( )

inherited

在文件 SGObject.cpp 第 111 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

io	io object to use

在文件 SGObject.cpp 第 228 行定义.

void set_global_parallel ( Parallel * parallel )

inherited

set the parallel object

参数

parallel parallel object to use

在文件 SGObject.cpp 第 241 行定义.

void set_global_version ( Version * version )

inherited

set the version object

参数

version version object to use

在文件 SGObject.cpp 第 283 行定义.

void set_labels ( CLabels * lab )

virtualinherited

set labels

参数

lab labels

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

在文件 Machine.cpp 第 65 行定义.

void set_max_train_time ( float64_t t )

inherited

set maximum training time

参数

t	maximimum training time

在文件 Machine.cpp 第 82 行定义.

void set_num_passes ( int32_t num_passes )

inherited

set number of passes

在文件 ConditionalProbabilityTree.h 第 49 行定义.

void set_root ( CTreeMachineNode< ConditionalProbabilityTreeNodeData > * root )

inherited

set root

参数

root	the root node of the tree

在文件 TreeMachine.h 第 78 行定义.

void set_solver_type ( ESolverType st )

inherited

set solver type

参数

st	solver type

在文件 Machine.cpp 第 97 行定义.

void set_store_model_features ( bool store_model )

virtualinherited

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

参数

store_model whether model should be stored after training

在文件 Machine.cpp 第 107 行定义.

CSGObject * shallow_copy ( ) const

virtualinherited

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

被 CGaussianKernel 重载.

在文件 SGObject.cpp 第 192 行定义.

virtual void store_model_features ( )

protectedvirtualinherited

enable unlocked cross-validation - no model features to store

重载 CMachine .

在文件 TreeMachine.h 第 152 行定义.

virtual bool supports_locking ( ) const

virtualinherited

返回: whether this machine supports locking

被 CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.h 第 293 行定义.

bool train ( CFeatures * data = NULL )

virtualinherited

train machine

参数

data	training 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

被 CRelaxedTree, CAutoencoder, CSGDQN , 以及 COnlineSVMSGD 重载.

在文件 Machine.cpp 第 39 行定义.

void train_example	(	SGVector< float32_t >	ex,
		int32_t	label
	)

protectedinherited

train on a single example (online learning)

参数

ex	the example being trained
label	the label of this training example

在文件 ConditionalProbabilityTree.cpp 第 152 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

indices index vector (of locked features) that is used for training

返回: whether training was successful

被 CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.h 第 239 行定义.

bool train_machine ( CFeatures * data )

protectedvirtualinherited

train machine

参数

data	training data

返回: whether training was successful

重载 CMachine .

在文件 ConditionalProbabilityTree.cpp 第 98 行定义.

void train_node	(	SGVector< float32_t >	ex,
		float64_t	label,
		bnode_t *	node
	)

protectedinherited

train a single node

参数

ex	the example being trained
label	label
node	the node

在文件 ConditionalProbabilityTree.cpp 第 228 行定义.

void train_path	(	SGVector< float32_t >	ex,
		bnode_t *	node
	)

protectedinherited

train on a path from a node up to the root

参数

ex	the instance of the training example
node	the leaf node

在文件 ConditionalProbabilityTree.cpp 第 209 行定义.

virtual bool train_require_labels ( ) const

protectedvirtualinherited

the labels will be embedded in the streaming features

重载 CMachine .

在文件 ConditionalProbabilityTree.h 第 82 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.cpp 第 303 行定义.

void update_parameter_hash ( )

virtualinherited

Updates the hash of current parameter combination

在文件 SGObject.cpp 第 248 行定义.

bool which_subtree	(	bnode_t *	node,
		SGVector< float32_t >	ex
	)

protectedvirtual

decide which subtree to go, when training the tree structure.

参数

node	the node being decided
ex	the example being decided

返回: true if should go left, false otherwise

在文件 BalancedConditionalProbabilityTree.cpp 第 28 行定义.

virtual bool which_subtree	(	bnode_t *	node,
		SGVector< float32_t >	ex
	)

protectedpure virtualinherited

decide which subtree to go, when training the tree structure.

参数

node	the node being decided
ex	the example being decided

返回: true if should go left, false otherwise

类成员变量说明

SGIO* io

inherited

io

在文件 SGObject.h 第 369 行定义.

bool m_data_locked

protectedinherited

whether data is locked

在文件 Machine.h 第 370 行定义.

CStreamingDenseFeatures<float32_t>* m_feats

protectedinherited

online features

在文件 ConditionalProbabilityTree.h 第 139 行定义.

Parameter* m_gradient_parameters

inherited

parameters wrt which we can compute gradients

在文件 SGObject.h 第 384 行定义.

uint32_t m_hash

inherited

Hash of parameter values

在文件 SGObject.h 第 387 行定义.

CLabels* m_labels

protectedinherited

labels

在文件 Machine.h 第 361 行定义.

std::map<int32_t, bnode_t*> m_leaves

protectedinherited

class => leaf mapping

在文件 ConditionalProbabilityTree.h 第 138 行定义.

CDynamicObjectArray* m_machines

protectedinherited

machines

在文件 BaseMulticlassMachine.h 第 56 行定义.

float64_t m_max_train_time

protectedinherited

maximum training time

在文件 Machine.h 第 358 行定义.

Parameter* m_model_selection_parameters

inherited

model selection parameters

在文件 SGObject.h 第 381 行定义.

int32_t m_num_passes

protectedinherited

number of passes for online training

在文件 ConditionalProbabilityTree.h 第 137 行定义.

Parameter* m_parameters

inherited

parameters

在文件 SGObject.h 第 378 行定义.

CTreeMachineNode<ConditionalProbabilityTreeNodeData >* m_root

protectedinherited

tree root

在文件 TreeMachine.h 第 156 行定义.

ESolverType m_solver_type

protectedinherited

solver type

在文件 Machine.h 第 364 行定义.

bool m_store_model_features

protectedinherited

whether model features should be stored after training

在文件 Machine.h 第 367 行定义.

Parallel* parallel

inherited

parallel

在文件 SGObject.h 第 372 行定义.

Version* version

inherited

version

在文件 SGObject.h 第 375 行定义.

该类的文档由以下文件生成:

详细描述

Public 类型

Public 成员函数

Public 属性

Protected 成员函数

Protected 属性

成员类型定义说明

构造及析构函数说明

成员函数说明

类成员变量说明