详细描述

Multiple Kernel Learning for one-class-classification.

Learns a One-Class SVM classifier and its kernel weights. Makes only sense if multiple kernels are used.

参见: CMKL

在文件 MKLOneClass.h 第 27 行定义.

类 CMKLOneClass 继承关系图:

[图例]

Public 成员函数
	CMKLOneClass (CSVM *s=NULL)

virtual	~CMKLOneClass ()

virtual float64_t	compute_sum_alpha ()

virtual const char *	get_name () const

void	set_constraint_generator (CSVM *s)

void	set_svm (CSVM *s)

CSVM *	get_svm ()

void	set_C_mkl (float64_t C)

void	set_mkl_norm (float64_t norm)

void	set_elasticnet_lambda (float64_t elasticnet_lambda)

void	set_mkl_block_norm (float64_t q)

void	set_interleaved_optimization_enabled (bool enable)

bool	get_interleaved_optimization_enabled ()

float64_t	compute_mkl_primal_objective ()

virtual float64_t	compute_mkl_dual_objective ()

float64_t	compute_elasticnet_dual_objective ()

void	set_mkl_epsilon (float64_t eps)

float64_t	get_mkl_epsilon ()

int32_t	get_mkl_iterations ()

virtual bool	perform_mkl_step (const float64_t *sumw, float64_t suma)

virtual void	compute_sum_beta (float64_t *sumw)

	MACHINE_PROBLEM_TYPE (PT_BINARY)

void	set_defaults (int32_t num_sv=0)

virtual SGVector< float64_t >	get_linear_term ()

virtual void	set_linear_term (const SGVector< float64_t > linear_term)

bool	load (FILE *svm_file)

bool	save (FILE *svm_file)

void	set_nu (float64_t nue)

void	set_C (float64_t c_neg, float64_t c_pos)

void	set_epsilon (float64_t eps)

void	set_tube_epsilon (float64_t eps)

float64_t	get_tube_epsilon ()

void	set_qpsize (int32_t qps)

float64_t	get_epsilon ()

float64_t	get_nu ()

float64_t	get_C1 ()

float64_t	get_C2 ()

int32_t	get_qpsize ()

void	set_shrinking_enabled (bool enable)

bool	get_shrinking_enabled ()

float64_t	compute_svm_dual_objective ()

float64_t	compute_svm_primal_objective ()

void	set_objective (float64_t v)

float64_t	get_objective ()

void	set_callback_function (CMKL m, bool(cb)(CMKL mkl, const float64_t sumw, const float64_t suma))

void	set_kernel (CKernel *k)

CKernel *	get_kernel ()

void	set_batch_computation_enabled (bool enable)

bool	get_batch_computation_enabled ()

void	set_linadd_enabled (bool enable)

bool	get_linadd_enabled ()

void	set_bias_enabled (bool enable_bias)

bool	get_bias_enabled ()

float64_t	get_bias ()

void	set_bias (float64_t bias)

int32_t	get_support_vector (int32_t idx)

float64_t	get_alpha (int32_t idx)

bool	set_support_vector (int32_t idx, int32_t val)

bool	set_alpha (int32_t idx, float64_t val)

int32_t	get_num_support_vectors ()

void	set_alphas (SGVector< float64_t > alphas)

void	set_support_vectors (SGVector< int32_t > svs)

SGVector< int32_t >	get_support_vectors ()

SGVector< float64_t >	get_alphas ()

bool	create_new_model (int32_t num)

bool	init_kernel_optimization ()

virtual CRegressionLabels *	apply_regression (CFeatures *data=NULL)

virtual CBinaryLabels *	apply_binary (CFeatures *data=NULL)

virtual float64_t	apply_one (int32_t num)

virtual bool	train_locked (SGVector< index_t > indices)

virtual CBinaryLabels *	apply_locked_binary (SGVector< index_t > indices)

virtual CRegressionLabels *	apply_locked_regression (SGVector< index_t > indices)

virtual SGVector< float64_t >	apply_locked_get_output (SGVector< index_t > indices)

virtual void	data_lock (CLabels labs, CFeatures features=NULL)

virtual void	data_unlock ()

virtual bool	supports_locking () const

virtual bool	train (CFeatures *data=NULL)

virtual CLabels *	apply (CFeatures *data=NULL)

virtual CMulticlassLabels *	apply_multiclass (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 ()

void	set_solver_type (ESolverType st)

ESolverType	get_solver_type ()

virtual void	set_store_model_features (bool store_model)

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

bool	is_data_locked () const

virtual EProblemType	get_machine_problem_type () 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 ()

静态 Public 成员函数
static bool	perform_mkl_step_helper (CMKL mkl, const float64_t sumw, const float64_t suma)

static void *	apply_helper (void *p)

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 void	init_training ()

virtual EMachineType	get_classifier_type ()

void	perform_mkl_step (float64_t beta, float64_t old_beta, int num_kernels, int32_t label, int32_t active2dnum, float64_t a, float64_t lin, float64_t *sumw, int32_t &inner_iters)

virtual bool	train_machine (CFeatures *data=NULL)

float64_t	compute_optimal_betas_via_cplex (float64_t beta, const float64_t old_beta, int32_t num_kernels, const float64_t *sumw, float64_t suma, int32_t &inner_iters)

float64_t	compute_optimal_betas_via_glpk (float64_t beta, const float64_t old_beta, int num_kernels, const float64_t *sumw, float64_t suma, int32_t &inner_iters)

float64_t	compute_optimal_betas_elasticnet (float64_t beta, const float64_t old_beta, const int32_t num_kernels, const float64_t *sumw, const float64_t suma, const float64_t mkl_objective)

void	elasticnet_transform (float64_t *beta, float64_t lmd, int32_t len)

void	elasticnet_dual (float64_t ff, float64_t gg, float64_t hh, const float64_t &del, const float64_t nm, int32_t len, const float64_t &lambda)

float64_t	compute_optimal_betas_directly (float64_t beta, const float64_t old_beta, const int32_t num_kernels, const float64_t *sumw, const float64_t suma, const float64_t mkl_objective)

float64_t	compute_optimal_betas_block_norm (float64_t beta, const float64_t old_beta, const int32_t num_kernels, const float64_t *sumw, const float64_t suma, const float64_t mkl_objective)

float64_t	compute_optimal_betas_newton (float64_t beta, const float64_t old_beta, int32_t num_kernels, const float64_t *sumw, float64_t suma, float64_t mkl_objective)

virtual bool	converged ()

void	init_solver ()

bool	init_cplex ()

void	set_qnorm_constraints (float64_t *beta, int32_t num_kernels)

bool	cleanup_cplex ()

bool	init_glpk ()

bool	cleanup_glpk ()

bool	check_glp_status (glp_prob *lp)

virtual float64_t *	get_linear_term_array ()

SGVector< float64_t >	apply_get_outputs (CFeatures *data)

virtual void	store_model_features ()

virtual bool	is_label_valid (CLabels *lab) const

virtual bool	train_require_labels () const

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
CSVM *	svm

float64_t	C_mkl

float64_t	mkl_norm

float64_t	ent_lambda

float64_t	mkl_block_norm

float64_t *	beta_local

int32_t	mkl_iterations

float64_t	mkl_epsilon

bool	interleaved_optimization

float64_t *	W

float64_t	w_gap

float64_t	rho

CTime	training_time_clock

CPXENVptr	env

CPXLPptr	lp_cplex

glp_prob *	lp_glpk

glp_smcp *	lp_glpk_parm

bool	lp_initialized

SGVector< float64_t >	m_linear_term

bool	svm_loaded

float64_t	epsilon

float64_t	tube_epsilon

float64_t	nu

float64_t	C1

float64_t	C2

float64_t	objective

int32_t	qpsize

bool	use_shrinking

bool(*	callback )(CMKL mkl, const float64_t sumw, const float64_t suma)

CMKL *	mkl

CKernel *	kernel

CCustomKernel *	m_custom_kernel

CKernel *	m_kernel_backup

bool	use_batch_computation

bool	use_linadd

bool	use_bias

float64_t	m_bias

SGVector< float64_t >	m_alpha

SGVector< int32_t >	m_svs

float64_t	m_max_train_time

CLabels *	m_labels

ESolverType	m_solver_type

bool	m_store_model_features

bool	m_data_locked

构造及析构函数说明

CMKLOneClass ( CSVM * s = NULL )

Constructor

参数

s	SVM to use as constraint generator in MKL SILP

在文件 MKLOneClass.cpp 第 6 行定义.

~CMKLOneClass ( )

virtual

Destructor

在文件 MKLOneClass.cpp 第 12 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.cpp 第 152 行定义.

CBinaryLabels * apply_binary ( CFeatures * data = NULL )

virtualinherited

apply kernel machine to data for binary classification task

参数

data	(test)data to be classified

返回: classified labels

重载 CMachine .

在文件 KernelMachine.cpp 第 248 行定义.

SGVector< float64_t > apply_get_outputs ( CFeatures * data )

protectedinherited

apply get outputs

参数

data	features to compute outputs

返回: outputs

在文件 KernelMachine.cpp 第 254 行定义.

void * apply_helper ( void * p )

staticinherited

apply example helper, used in threads

参数

p	params of the thread

返回: nothing really

在文件 KernelMachine.cpp 第 424 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. Error if machine is not locked. Binary case

参数

indices index vector (of locked features) that is predicted

返回: resulting labels

重载 CMachine .

在文件 KernelMachine.cpp 第 518 行定义.

SGVector< float64_t > apply_locked_get_output ( 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

返回: raw output of machine

在文件 KernelMachine.cpp 第 531 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. Error if machine is not locked. Binary case

参数

indices index vector (of locked features) that is predicted

返回: resulting labels

重载 CMachine .

在文件 KernelMachine.cpp 第 524 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

被 CNeuralNetwork, CCHAIDTree, CCARTree, CGaussianProcessClassification, CMulticlassMachine, CKNN, CC45ClassifierTree, CID3ClassifierTree, CDistanceMachine, CVwConditionalProbabilityTree, CGaussianNaiveBayes, CConditionalProbabilityTree, CMCLDA, CQDA, CRelaxedTree , 以及 CBaggingMachine 重载.

在文件 Machine.cpp 第 220 行定义.

float64_t apply_one ( int32_t num )

virtualinherited

apply kernel machine to one example

参数

num	which example to apply to

返回: classified value

重载 CMachine .

在文件 KernelMachine.cpp 第 405 行定义.

CRegressionLabels * apply_regression ( CFeatures * data = NULL )

virtualinherited

apply kernel machine to data for regression task

参数

data	(test)data to be classified

返回: classified labels

重载 CMachine .

在文件 KernelMachine.cpp 第 242 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.

bool check_glp_status ( glp_prob * lp )

protectedinherited

check glpk error status

返回: if in good status

在文件 MKL.cpp 第 179 行定义.

bool cleanup_cplex ( )

protectedinherited

cleanup cplex

返回: if cleanup was successful

在文件 MKL.cpp 第 119 行定义.

bool cleanup_glpk ( )

protectedinherited

cleanup glpk

返回: if cleanup was successful

在文件 MKL.cpp 第 169 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.

float64_t compute_elasticnet_dual_objective ( )

inherited

compute ElasticnetMKL dual objective

返回: computed dual objective

在文件 MKL.cpp 第 591 行定义.

float64_t compute_mkl_dual_objective ( )

virtualinherited

compute mkl dual objective

返回: computed dual objective

被 CMKLRegression 重载.

在文件 MKL.cpp 第 1525 行定义.

float64_t compute_mkl_primal_objective ( )

inherited

compute mkl primal objective

返回: computed mkl primal objective

在文件 MKL.h 第 187 行定义.

float64_t compute_optimal_betas_block_norm	(	float64_t *	beta,
		const float64_t *	old_beta,
		const int32_t	num_kernels,
		const float64_t *	sumw,
		const float64_t	suma,
		const float64_t	mkl_objective
	)

protectedinherited

given the alphas, compute the corresponding optimal betas

参数

beta	new betas (kernel weights)
old_beta	old betas (previous kernel weights)
num_kernels	number of kernels
sumw	1/2alpha'K_j*alpha for each kernel j
suma	(sum over alphas)
mkl_objective	the current mkl objective

返回: new objective value

在文件 MKL.cpp 第 666 行定义.

float64_t compute_optimal_betas_directly	(	float64_t *	beta,
		const float64_t *	old_beta,
		const int32_t	num_kernels,
		const float64_t *	sumw,
		const float64_t	suma,
		const float64_t	mkl_objective
	)

protectedinherited

given the alphas, compute the corresponding optimal betas

参数

beta	new betas (kernel weights)
old_beta	old betas (previous kernel weights)
num_kernels	number of kernels
sumw	1/2alpha'K_j*alpha for each kernel j
suma	(sum over alphas)
mkl_objective	the current mkl objective

返回: new objective value

在文件 MKL.cpp 第 702 行定义.

float64_t compute_optimal_betas_elasticnet	(	float64_t *	beta,
		const float64_t *	old_beta,
		const int32_t	num_kernels,
		const float64_t *	sumw,
		const float64_t	suma,
		const float64_t	mkl_objective
	)

protectedinherited

given the alphas, compute the corresponding optimal betas

参数

beta	new betas (kernel weights)
old_beta	old betas (previous kernel weights)
num_kernels	number of kernels
sumw	1/2alpha'K_j*alpha for each kernel j
suma	(sum over alphas)
mkl_objective	the current mkl objective

返回: new objective value

在文件 MKL.cpp 第 472 行定义.

float64_t compute_optimal_betas_newton	(	float64_t *	beta,
		const float64_t *	old_beta,
		int32_t	num_kernels,
		const float64_t *	sumw,
		float64_t	suma,
		float64_t	mkl_objective
	)

protectedinherited

given the alphas, compute the corresponding optimal betas

参数

beta	new betas (kernel weights)
old_beta	old betas (previous kernel weights)
num_kernels	number of kernels
sumw	1/2alpha'K_j*alpha for each kernel j
suma	(sum over alphas)
mkl_objective	the current mkl objective

返回: new objective value

在文件 MKL.cpp 第 791 行定义.

float64_t compute_optimal_betas_via_cplex	(	float64_t *	beta,
		const float64_t *	old_beta,
		int32_t	num_kernels,
		const float64_t *	sumw,
		float64_t	suma,
		int32_t &	inner_iters
	)

protectedinherited

given the alphas, compute the corresponding optimal betas using a lp for 1-norm mkl, a qcqp for 2-norm mkl and an iterated qcqp for general q-norm mkl.

参数

beta	new betas (kernel weights)
old_beta	old betas (previous kernel weights)
num_kernels	number of kernels
sumw	1/2alpha'K_j*alpha for each kernel j
suma	(sum over alphas)
inner_iters	number of internal iterations (for statistics)

返回: new objective value

在文件 MKL.cpp 第 983 行定义.

float64_t compute_optimal_betas_via_glpk	(	float64_t *	beta,
		const float64_t *	old_beta,
		int	num_kernels,
		const float64_t *	sumw,
		float64_t	suma,
		int32_t &	inner_iters
	)

protectedinherited

given the alphas, compute the corresponding optimal betas using a lp for 1-norm mkl

参数

beta	new betas (kernel weights)
old_beta	old betas (previous kernel weights)
num_kernels	number of kernels
sumw	1/2alpha'K_j*alpha for each kernel j
suma	(sum over alphas)
inner_iters	number of internal iterations (for statistics)

返回: new objective value

在文件 MKL.cpp 第 1326 行定义.

float64_t compute_sum_alpha ( )

virtual

compute beta independent term from objective, e.g., in 2-class MKL sum_i alpha_i etc

实现了 CMKL.

在文件 MKLOneClass.cpp 第 16 行定义.

void compute_sum_beta ( float64_t * sumw )

virtualinherited

compute 1/2*alpha'*K_j*alpha for each kernel j (beta dependent term from objective)

参数

sumw	vector of size num_kernels to hold the result

在文件 MKL.cpp 第 1480 行定义.

float64_t compute_svm_dual_objective ( )

inherited

compute svm dual objective

返回: computed dual objective

在文件 SVM.cpp 第 242 行定义.

float64_t compute_svm_primal_objective ( )

inherited

compute svm primal objective

返回: computed svm primal objective

在文件 SVM.cpp 第 267 行定义.

virtual bool converged ( )

protectedvirtualinherited

check if mkl converged, i.e. 'gap' is below epsilon

返回: whether mkl converged

在文件 MKL.h 第 404 行定义.

bool create_new_model ( int32_t num )

inherited

create new model

参数

num	number of alphas and support vectors in new model

在文件 KernelMachine.cpp 第 194 行定义.

void data_lock	(	CLabels *	labs,
		CFeatures *	features = `NULL`
	)

virtualinherited

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

Computes kernel matrix to speed up train/apply calls

参数

labs	labels used for locking
features	features used for locking

重载 CMachine .

在文件 KernelMachine.cpp 第 623 行定义.

void data_unlock ( )

virtualinherited

Unlocks a locked machine and restores previous state

重载 CMachine .

在文件 KernelMachine.cpp 第 654 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.

void elasticnet_dual	(	float64_t *	ff,
		float64_t *	gg,
		float64_t *	hh,
		const float64_t &	del,
		const float64_t *	nm,
		int32_t	len,
		const float64_t &	lambda
	)

protectedinherited

helper function to compute the elastic-net objective

在文件 MKL.cpp 第 564 行定义.

void elasticnet_transform	(	float64_t *	beta,
		float64_t	lmd,
		int32_t	len
	)

protectedinherited

helper function to compute the elastic-net sub-kernel weights

在文件 MKL.h 第 345 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 ( int32_t idx )

inherited

get alpha at given index

参数

idx	index of alpha

返回: alpha

在文件 KernelMachine.cpp 第 140 行定义.

SGVector< float64_t > get_alphas ( )

inherited

返回: vector of alphas

在文件 KernelMachine.cpp 第 189 行定义.

bool get_batch_computation_enabled ( )

inherited

check if batch computation is enabled

返回: if batch computation is enabled

在文件 KernelMachine.cpp 第 99 行定义.

float64_t get_bias ( )

inherited

get bias

返回: bias

在文件 KernelMachine.cpp 第 124 行定义.

bool get_bias_enabled ( )

inherited

get state of bias

返回: state of bias

在文件 KernelMachine.cpp 第 119 行定义.

float64_t get_C1 ( )

inherited

get C1

返回: C1

在文件 SVM.h 第 161 行定义.

float64_t get_C2 ( )

inherited

get C2

返回: C2

在文件 SVM.h 第 167 行定义.

virtual EMachineType get_classifier_type ( )

protectedvirtual

get classifier type

返回: classifier type MKL ONECLASS

重载 CMachine .

在文件 MKLOneClass.h 第 58 行定义.

float64_t get_epsilon ( )

inherited

get epsilon

返回: epsilon

在文件 SVM.h 第 149 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.

bool get_interleaved_optimization_enabled ( )

inherited

get state of optimization (interleaved or wrapper)

返回: true if interleaved optimization is used; wrapper otherwise

在文件 MKL.h 第 178 行定义.

CKernel * get_kernel ( )

inherited

get kernel

返回: kernel

在文件 KernelMachine.cpp 第 88 行定义.

CLabels * get_labels ( )

virtualinherited

get labels

返回: labels

在文件 Machine.cpp 第 76 行定义.

bool get_linadd_enabled ( )

inherited

check if linadd is enabled

返回: if linadd is enabled

在文件 KernelMachine.cpp 第 109 行定义.

SGVector< float64_t > get_linear_term ( )

virtualinherited

get linear term

返回: the linear term

在文件 SVM.cpp 第 332 行定义.

float64_t * get_linear_term_array ( )

protectedvirtualinherited

get linear term copy as dynamic array

返回: linear term copied to a dynamic array

在文件 SVM.cpp 第 302 行定义.

virtual EProblemType get_machine_problem_type ( ) const

virtualinherited

returns type of problem machine solves

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

在文件 Machine.h 第 299 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.

float64_t get_mkl_epsilon ( )

inherited

get mkl epsilon for weights (optimization accuracy for kernel weights)

返回: epsilon for weights

在文件 MKL.h 第 215 行定义.

int32_t get_mkl_iterations ( )

inherited

get number of MKL iterations

返回: mkl_iterations

在文件 MKL.h 第 221 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

返回: object name

重载 CMKL .

在文件 MKLOneClass.h 第 46 行定义.

float64_t get_nu ( )

inherited

get nu

返回: nu

在文件 SVM.h 第 155 行定义.

int32_t get_num_support_vectors ( )

inherited

get number of support vectors

返回: number of support vectors

在文件 KernelMachine.cpp 第 169 行定义.

float64_t get_objective ( )

inherited

get objective

返回: objective

在文件 SVM.h 第 218 行定义.

int32_t get_qpsize ( )

inherited

get qpsize

返回: qpsize

在文件 SVM.h 第 173 行定义.

bool get_shrinking_enabled ( )

inherited

get state of shrinking

返回: if shrinking is enabled

在文件 SVM.h 第 188 行定义.

ESolverType get_solver_type ( )

inherited

get solver type

返回: solver

在文件 Machine.cpp 第 102 行定义.

int32_t get_support_vector ( int32_t idx )

inherited

get support vector at given index

参数

idx	index of support vector

返回: support vector

在文件 KernelMachine.cpp 第 134 行定义.

SGVector< int32_t > get_support_vectors ( )

inherited

返回: all support vectors

在文件 KernelMachine.cpp 第 184 行定义.

CSVM* get_svm ( )

inherited

get SVM that is used as constraint generator in MKL SIP

返回: svm

在文件 MKL.h 第 132 行定义.

float64_t get_tube_epsilon ( )

inherited

get tube epsilon

返回: tube epsilon

在文件 SVM.h 第 137 行定义.

bool init_cplex ( )

protectedinherited

init cplex

返回: if init was successful

在文件 MKL.cpp 第 70 行定义.

bool init_glpk ( )

protectedinherited

init glpk

返回: if init was successful

在文件 MKL.cpp 第 155 行定义.

bool init_kernel_optimization ( )

inherited

initialise kernel optimisation

返回: if operation was successful

在文件 KernelMachine.cpp 第 211 行定义.

void init_solver ( )

protectedinherited

initialize solver such as glpk or cplex

在文件 MKL.cpp 第 52 行定义.

void init_training ( )

protectedvirtual

check run before starting training (to e.g. check if labeling is two-class labeling in classification case

实现了 CMKL.

在文件 MKLOneClass.cpp 第 21 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.

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

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

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

在文件 Machine.h 第 348 行定义.

bool load ( FILE * svm_file )

inherited

load a SVM from file

参数

svm_file the file handle

在文件 SVM.cpp 第 90 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.

MACHINE_PROBLEM_TYPE ( PT_BINARY )

inherited

problem type

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.

bool perform_mkl_step	(	const float64_t *	sumw,
		float64_t	suma
	)

virtualinherited

perform single mkl iteration

given sum of alphas, objectives for current alphas for each kernel and current kernel weighting compute the corresponding optimal kernel weighting (all via get/set_subkernel_weights in CCombinedKernel)

参数

sumw	vector of 1/2alpha'K_j*alpha for each kernel j
suma	scalar sum_i alpha_i etc.

在文件 MKL.cpp 第 403 行定义.

void perform_mkl_step	(	float64_t *	beta,
		float64_t *	old_beta,
		int	num_kernels,
		int32_t *	label,
		int32_t *	active2dnum,
		float64_t *	a,
		float64_t *	lin,
		float64_t *	sumw,
		int32_t &	inner_iters
	)

protectedinherited

perform single mkl iteration

given the alphas, compute the corresponding optimal betas

参数

beta	new betas (kernel weights)
old_beta	old betas (previous kernel weights)
num_kernels	number of kernels
label	(from svmlight label)
active2dnum	(from svmlight active2dnum)
a	(from svmlight alphas)
lin	(from svmlight linear components)
sumw	1/2alpha'K_j*alpha for each kernel j
inner_iters	number of required internal iterations

static bool perform_mkl_step_helper	(	CMKL *	mkl,
		const float64_t *	sumw,
		const float64_t	suma
	)

staticinherited

callback helper function calling perform_mkl_step

参数

mkl	MKL object
sumw	vector of 1/2alpha'K_j*alpha for each kernel j
suma	scalar sum_i alpha_i etc.

在文件 MKL.h 第 241 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.

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.

bool save ( FILE * svm_file )

inherited

write a SVM to a file

参数

svm_file the file handle

在文件 SVM.cpp 第 206 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.

bool set_alpha	(	int32_t	idx,
		float64_t	val
	)

inherited

set alpha at given index to given value

参数

idx	index of alpha vector
val	new value of alpha vector

返回: if operation was successful

在文件 KernelMachine.cpp 第 159 行定义.

void set_alphas ( SGVector< float64_t > alphas )

inherited

set alphas to given values

参数

alphas float vector with all alphas to set

在文件 KernelMachine.cpp 第 174 行定义.

void set_batch_computation_enabled ( bool enable )

inherited

set batch computation enabled

参数

enable if batch computation shall be enabled

在文件 KernelMachine.cpp 第 94 行定义.

void set_bias ( float64_t bias )

inherited

set bias to given value

参数

bias new bias

在文件 KernelMachine.cpp 第 129 行定义.

void set_bias_enabled ( bool enable_bias )

inherited

set state of bias

参数

enable_bias if bias shall be enabled

在文件 KernelMachine.cpp 第 114 行定义.

void set_C	(	float64_t	c_neg,
		float64_t	c_pos
	)

inherited

set C

参数

c_neg	new C constant for negatively labeled examples
c_pos	new C constant for positively labeled examples

Note that not all SVMs support this (however at least CLibSVM and CSVMLight do)

在文件 SVM.h 第 118 行定义.

void set_C_mkl ( float64_t C )

inherited

set C mkl

参数

C new C_mkl

在文件 MKL.h 第 142 行定义.

void set_callback_function	(	CMKL *	m,
		bool()(CMKL mkl, const float64_t *sumw, const float64_t suma)	cb
	)

inherited

set callback function svm optimizers may call when they have a new (small) set of alphas

参数

m	pointer to mkl object
cb	callback function

在文件 SVM.cpp 第 232 行定义.

void set_constraint_generator ( CSVM * s )

inherited

SVM to use as constraint generator in MKL SIP

参数

s svm

在文件 MKL.h 第 112 行定义.

void set_defaults ( int32_t num_sv = 0 )

inherited

set default values for members a SVM object

在文件 SVM.cpp 第 48 行定义.

void set_elasticnet_lambda ( float64_t elasticnet_lambda )

inherited

set elasticnet lambda

参数

elasticnet_lambda new elastic net lambda (must be 0<=lambda<=1) lambda=0: L1-MKL lambda=1: Linfinity-MKL

在文件 MKL.cpp 第 382 行定义.

void set_epsilon ( float64_t eps )

inherited

set epsilon

参数

eps	new epsilon

在文件 SVM.h 第 125 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_interleaved_optimization_enabled ( bool enable )

inherited

set state of optimization (interleaved or wrapper)

参数

enable if true interleaved optimization is used; wrapper otherwise

在文件 MKL.h 第 169 行定义.

void set_kernel ( CKernel * k )

inherited

set kernel

参数

k kernel

在文件 KernelMachine.cpp 第 81 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_linadd_enabled ( bool enable )

inherited

set linadd enabled

参数

enable if linadd shall be enabled

在文件 KernelMachine.cpp 第 104 行定义.

void set_linear_term ( const SGVector< float64_t > linear_term )

virtualinherited

set linear term of the QP

参数

linear_term the linear term

在文件 SVM.cpp 第 314 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_mkl_block_norm ( float64_t q )

inherited

set block norm q (used in block norm mkl)

参数

q	mixed norm (1<=q<=inf)

在文件 MKL.cpp 第 395 行定义.

void set_mkl_epsilon ( float64_t eps )

inherited

set mkl epsilon (optimization accuracy for kernel weights)

参数

eps	new weight_epsilon

在文件 MKL.h 第 209 行定义.

void set_mkl_norm ( float64_t norm )

inherited

set mkl norm

参数

norm	new mkl norm (must be greater equal 1)

在文件 MKL.cpp 第 373 行定义.

void set_nu ( float64_t nue )

inherited

set nu

参数

nue new nu

在文件 SVM.h 第 107 行定义.

void set_objective ( float64_t v )

inherited

set objective

参数

v objective

在文件 SVM.h 第 209 行定义.

void set_qnorm_constraints	(	float64_t *	beta,
		int32_t	num_kernels
	)

protectedinherited

set qnorm mkl constraints

在文件 MKL.cpp 第 1575 行定义.

void set_qpsize ( int32_t qps )

inherited

set qpsize

参数

qps	new qpsize

在文件 SVM.h 第 143 行定义.

void set_shrinking_enabled ( bool enable )

inherited

set state of shrinking

参数

enable if shrinking will be enabled

在文件 SVM.h 第 179 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.

bool set_support_vector	(	int32_t	idx,
		int32_t	val
	)

inherited

set support vector at given index to given value

参数

idx	index of support vector
val	new value of support vector

返回: if operation was successful

在文件 KernelMachine.cpp 第 149 行定义.

void set_support_vectors ( SGVector< int32_t > svs )

inherited

set support vectors to given values

参数

svs	integer vector with all support vectors indexes to set

在文件 KernelMachine.cpp 第 179 行定义.

void set_svm ( CSVM * s )

inherited

SVM to use as constraint generator in MKL SIP

参数

s svm

在文件 MKL.h 第 121 行定义.

void set_tube_epsilon ( float64_t eps )

inherited

set tube epsilon

参数

eps	new tube epsilon

在文件 SVM.h 第 131 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.

void store_model_features ( )

protectedvirtualinherited

Stores feature data of the SV indices and sets it to the lhs of the underlying kernel. Then, all SV indices are set to identity.

May be overwritten by subclasses in case the model should be stored differently.

重载 CMachine .

在文件 KernelMachine.cpp 第 453 行定义.

bool supports_locking ( ) const

virtualinherited

返回: whether machine supports locking

重载 CMachine .

在文件 KernelMachine.cpp 第 699 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.

bool train_locked ( SGVector< index_t > indices )

virtualinherited

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

参数

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

返回: whether training was successful

重载 CMachine .

在文件 KernelMachine.cpp 第 482 行定义.

bool train_machine ( CFeatures * data = NULL )

protectedvirtualinherited

train MKL classifier

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)

返回: whether training was successful

重载 CMachine .

在文件 MKL.cpp 第 197 行定义.

virtual bool train_require_labels ( ) const

protectedvirtualinherited

returns whether machine require labels for training

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

在文件 Machine.h 第 354 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.

类成员变量说明

float64_t* beta_local

protectedinherited

sub-kernel weights on the L1-term of ElasticnetMKL

在文件 MKL.h 第 468 行定义.

float64_t C1

protectedinherited

C1 regularization const

在文件 SVM.h 第 257 行定义.

float64_t C2

protectedinherited

C2

在文件 SVM.h 第 259 行定义.

float64_t C_mkl

protectedinherited

C_mkl

在文件 MKL.h 第 453 行定义.

bool(* callback) (CMKL *mkl, const float64_t *sumw, const float64_t suma)

protectedinherited

callback function svm optimizers may call when they have a new (small) set of alphas

在文件 SVM.h 第 269 行定义.

float64_t ent_lambda

protectedinherited

Sparsity trade-off parameter used in ElasticnetMKL must be 0<=lambda<=1 lambda=0: L1-MKL lambda=1: Linfinity-MKL

在文件 MKL.h 第 461 行定义.

CPXENVptr env

protectedinherited

env

在文件 MKL.h 第 489 行定义.

float64_t epsilon

protectedinherited

epsilon

在文件 SVM.h 第 251 行定义.

bool interleaved_optimization

protectedinherited

whether to use mkl wrapper or interleaved opt.

在文件 MKL.h 第 474 行定义.

SGIO* io

inherited

io

在文件 SGObject.h 第 369 行定义.

CKernel* kernel

protectedinherited

kernel

在文件 KernelMachine.h 第 311 行定义.

CPXLPptr lp_cplex

protectedinherited

lp

在文件 MKL.h 第 491 行定义.

glp_prob* lp_glpk

protectedinherited

lp

在文件 MKL.h 第 496 行定义.

glp_smcp* lp_glpk_parm

protectedinherited

lp parameters

在文件 MKL.h 第 499 行定义.

bool lp_initialized

protectedinherited

if lp is initialized

在文件 MKL.h 第 502 行定义.

SGVector<float64_t> m_alpha

protectedinherited

coefficients alpha

在文件 KernelMachine.h 第 332 行定义.

float64_t m_bias

protectedinherited

bias term b

在文件 KernelMachine.h 第 329 行定义.

CCustomKernel* m_custom_kernel

protectedinherited

is filled with pre-computed custom kernel on data lock

在文件 KernelMachine.h 第 314 行定义.

bool m_data_locked

protectedinherited

whether data is locked

在文件 Machine.h 第 370 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.

CKernel* m_kernel_backup

protectedinherited

old kernel is stored here on data lock

在文件 KernelMachine.h 第 317 行定义.

CLabels* m_labels

protectedinherited

labels

在文件 Machine.h 第 361 行定义.

SGVector<float64_t> m_linear_term

protectedinherited

linear term in qp

在文件 SVM.h 第 246 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.

Parameter* m_parameters

inherited

parameters

在文件 SGObject.h 第 378 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.

SGVector<int32_t> m_svs

protectedinherited

array of ``support vectors'' (indices of feature objects)

在文件 KernelMachine.h 第 335 行定义.

CMKL* mkl

protectedinherited

mkl object that svm optimizers need to pass when calling the callback function

在文件 SVM.h 第 272 行定义.

float64_t mkl_block_norm

protectedinherited

Sparsity trade-off parameter used in block norm MKL should be 1 <= mkl_block_norm <= inf

在文件 MKL.h 第 465 行定义.

float64_t mkl_epsilon

protectedinherited

mkl_epsilon for multiple kernel learning

在文件 MKL.h 第 472 行定义.

int32_t mkl_iterations

protectedinherited

number of mkl steps

在文件 MKL.h 第 470 行定义.

float64_t mkl_norm

protectedinherited

norm used in mkl must be > 0

在文件 MKL.h 第 455 行定义.

float64_t nu

protectedinherited

nu

在文件 SVM.h 第 255 行定义.

float64_t objective

protectedinherited

objective

在文件 SVM.h 第 261 行定义.

Parallel* parallel

inherited

parallel

在文件 SGObject.h 第 372 行定义.

int32_t qpsize

protectedinherited

qpsize

在文件 SVM.h 第 263 行定义.

float64_t rho

protectedinherited

objective after mkl iterations

在文件 MKL.h 第 482 行定义.

CSVM* svm

protectedinherited

wrapper SVM

在文件 MKL.h 第 451 行定义.

bool svm_loaded

protectedinherited

if SVM is loaded

在文件 SVM.h 第 249 行定义.

CTime training_time_clock

protectedinherited

measures training time for use with get_max_train_time()

在文件 MKL.h 第 485 行定义.

float64_t tube_epsilon

protectedinherited

tube epsilon for support vector regression

在文件 SVM.h 第 253 行定义.

bool use_batch_computation

protectedinherited

if batch computation is enabled

在文件 KernelMachine.h 第 320 行定义.

bool use_bias

protectedinherited

if bias shall be used

在文件 KernelMachine.h 第 326 行定义.

bool use_linadd

protectedinherited

if linadd is enabled

在文件 KernelMachine.h 第 323 行定义.

bool use_shrinking

protectedinherited

if shrinking shall be used

在文件 SVM.h 第 265 行定义.

Version* version

inherited

version

在文件 SGObject.h 第 375 行定义.

float64_t* W

protectedinherited

partial objectives (one per kernel)

在文件 MKL.h 第 477 行定义.

float64_t w_gap

protectedinherited

gap between iterations

在文件 MKL.h 第 480 行定义.

该类的文档由以下文件生成:

详细描述

Public 成员函数

静态 Public 成员函数

Public 属性

Protected 成员函数

Protected 属性

构造及析构函数说明

成员函数说明

类成员变量说明