Detailed Description

class LibSVMOneClass

Definition at line 25 of file LibSVMOneClass.h.

Inheritance diagram for CLibSVMOneClass:

Public Types
typedef rxcpp::subjects::subject< ObservedValue >	SGSubject

typedef rxcpp::observable< ObservedValue, rxcpp::dynamic_observable< ObservedValue > >	SGObservable

typedef rxcpp::subscriber< ObservedValue, rxcpp::observer< ObservedValue, void, void, void, void > >	SGSubscriber

Public Member Functions
	CLibSVMOneClass ()

	CLibSVMOneClass (float64_t C, CKernel *k)

virtual	~CLibSVMOneClass ()

virtual EMachineType	get_classifier_type ()

virtual const char *	get_name () const

	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 ()

bool	get_loaded_status ()

void	set_loaded_status (bool loaded)

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

SG_FORCED_INLINE bool	cancel_computation () const

SG_FORCED_INLINE void	pause_computation ()

SG_FORCED_INLINE void	resume_computation ()

int32_t	ref ()

int32_t	ref_count ()

int32_t	unref ()

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)

bool	has (const std::string &name) const

template<typename T >
bool	has (const Tag< T > &tag) const

template<typename T , typename U = void>
bool	has (const std::string &name) const

template<typename T >
void	set (const Tag< T > &_tag, const T &value)

template<typename T , typename U = void>
void	set (const std::string &name, const T &value)

template<typename T >
T	get (const Tag< T > &_tag) const

template<typename T , typename U = void>
T	get (const std::string &name) const

SGObservable *	get_parameters_observable ()

void	subscribe_to_parameters (ParameterObserverInterface *obs)

void	list_observable_parameters ()

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 Attributes
SGIO *	io

Parallel *	parallel

Version *	version

Parameter *	m_parameters

Parameter *	m_model_selection_parameters

Parameter *	m_gradient_parameters

uint32_t	m_hash

Protected Member Functions
virtual bool	train_require_labels () const

virtual bool	train_machine (CFeatures *data=NULL)

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

rxcpp::subscription	connect_to_signal_handler ()

void	reset_computation_variables ()

virtual void	on_next ()

virtual void	on_pause ()

virtual void	on_complete ()

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)

template<typename T >
void	register_param (Tag< T > &_tag, const T &value)

template<typename T >
void	register_param (const std::string &name, const T &value)

bool	clone_parameters (CSGObject *other)

void	observe (const ObservedValue value)

void	register_observable_param (const std::string &name, const SG_OBS_VALUE_TYPE type, const std::string &description)

Protected Attributes
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

std::atomic< bool >	m_cancel_computation

std::atomic< bool >	m_pause_computation_flag

std::condition_variable	m_pause_computation

std::mutex	m_mutex

Member Typedef Documentation

◆ SGObservable

typedef rxcpp::observable<ObservedValue, rxcpp::dynamic_observable<ObservedValue> > SGObservable

inherited

Definition at line 130 of file SGObject.h.

◆ SGSubject

typedef rxcpp::subjects::subject<ObservedValue> SGSubject

inherited

Definition at line 127 of file SGObject.h.

◆ SGSubscriber

typedef rxcpp::subscriber< ObservedValue, rxcpp::observer<ObservedValue, void, void, void, void> > SGSubscriber

inherited

Definition at line 133 of file SGObject.h.

Constructor & Destructor Documentation

◆ CLibSVMOneClass() [1/2]

CLibSVMOneClass ( )

default constructor

Definition at line 17 of file LibSVMOneClass.cpp.

◆ CLibSVMOneClass() [2/2]

CLibSVMOneClass	(	float64_t	C,
		CKernel *	k
	)

constructor

Parameters

C	constant C
k	kernel

Definition at line 22 of file LibSVMOneClass.cpp.

◆ ~CLibSVMOneClass()

~CLibSVMOneClass ( )

virtual

Definition at line 27 of file LibSVMOneClass.cpp.

Member Function Documentation

◆ apply()

CLabels * apply ( CFeatures * data = NULL )

virtualinherited

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

Parameters

data	(test)data to be classified

Returns: classified labels

Definition at line 159 of file Machine.cpp.

◆ apply_binary()

CBinaryLabels * apply_binary ( CFeatures * data = NULL )

virtualinherited

apply kernel machine to data for binary classification task

Parameters

data	(test)data to be classified

Returns: classified labels

Reimplemented from CMachine.

Reimplemented in CDomainAdaptationSVM.

Definition at line 253 of file KernelMachine.cpp.

◆ apply_get_outputs()

SGVector< float64_t > apply_get_outputs ( CFeatures * data )

protectedinherited

apply get outputs

Parameters

data	features to compute outputs

Returns: outputs

Definition at line 259 of file KernelMachine.cpp.

◆ apply_latent()

CLatentLabels * apply_latent ( CFeatures * data = NULL )

virtualinherited

apply machine to data in means of latent problem

Reimplemented in CLinearLatentMachine.

Definition at line 239 of file Machine.cpp.

◆ apply_locked()

CLabels * apply_locked ( SGVector< index_t > indices )

virtualinherited

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

Parameters

indices index vector (of locked features) that is predicted

Definition at line 194 of file Machine.cpp.

◆ apply_locked_binary()

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

Parameters

indices index vector (of locked features) that is predicted

Returns: resulting labels

Reimplemented from CMachine.

Definition at line 470 of file KernelMachine.cpp.

◆ apply_locked_get_output()

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

Parameters

indices index vector (of locked features) that is predicted

Returns: raw output of machine

Definition at line 483 of file KernelMachine.cpp.

◆ apply_locked_latent()

CLatentLabels * apply_locked_latent ( SGVector< index_t > indices )

virtualinherited

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

Definition at line 273 of file Machine.cpp.

◆ apply_locked_multiclass()

CMulticlassLabels * apply_locked_multiclass ( SGVector< index_t > indices )

virtualinherited

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

Definition at line 259 of file Machine.cpp.

◆ apply_locked_regression()

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

Parameters

indices index vector (of locked features) that is predicted

Returns: resulting labels

Reimplemented from CMachine.

Definition at line 476 of file KernelMachine.cpp.

◆ apply_locked_structured()

CStructuredLabels * apply_locked_structured ( SGVector< index_t > indices )

virtualinherited

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

Definition at line 266 of file Machine.cpp.

◆ apply_multiclass()

CMulticlassLabels * apply_multiclass ( CFeatures * data = NULL )

virtualinherited

apply machine to data in means of multiclass classification problem

Reimplemented in CNeuralNetwork, CCHAIDTree, CCARTree, CGaussianProcessClassification, CKNN, CMulticlassMachine, CC45ClassifierTree, CID3ClassifierTree, CQDA, CDistanceMachine, CVwConditionalProbabilityTree, CGaussianNaiveBayes, CConditionalProbabilityTree, CMCLDA, CRelaxedTree, and CBaggingMachine.

Definition at line 227 of file Machine.cpp.

◆ apply_one()

float64_t apply_one ( int32_t num )

virtualinherited

apply kernel machine to one example

Parameters

num	which example to apply to

Returns: classified value

Reimplemented from CMachine.

Definition at line 559 of file KernelMachine.cpp.

◆ apply_regression()

CRegressionLabels * apply_regression ( CFeatures * data = NULL )

virtualinherited

apply kernel machine to data for regression task

Parameters

data	(test)data to be classified

Returns: classified labels

Reimplemented from CMachine.

Definition at line 247 of file KernelMachine.cpp.

◆ apply_structured()

CStructuredLabels * apply_structured ( CFeatures * data = NULL )

virtualinherited

apply machine to data in means of SO classification problem

Reimplemented in CLinearStructuredOutputMachine.

Definition at line 233 of file Machine.cpp.

◆ build_gradient_parameter_dictionary()

void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject *> * dict )

inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

Parameters

dict	dictionary of parameters to be built.

Definition at line 635 of file SGObject.cpp.

◆ cancel_computation()

SG_FORCED_INLINE bool cancel_computation ( ) const

inherited

Returns: whether the algorithm needs to be stopped

Definition at line 319 of file Machine.h.

◆ clone()

CSGObject * clone ( )

virtualinherited

Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.

Returns: 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

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicObjectArray, CAlphabet, and CMKL.

Definition at line 734 of file SGObject.cpp.

◆ clone_parameters()

bool clone_parameters ( CSGObject * other )

protectedinherited

Definition at line 759 of file SGObject.cpp.

◆ compute_svm_dual_objective()

float64_t compute_svm_dual_objective ( )

inherited

compute svm dual objective

Returns: computed dual objective

Definition at line 237 of file SVM.cpp.

◆ compute_svm_primal_objective()

float64_t compute_svm_primal_objective ( )

inherited

compute svm primal objective

Returns: computed svm primal objective

Definition at line 262 of file SVM.cpp.

◆ connect_to_signal_handler()

rxcpp::subscription connect_to_signal_handler ( )

protectedinherited

connect the machine instance to the signal handler

Definition at line 280 of file Machine.cpp.

◆ create_new_model()

bool create_new_model ( int32_t num )

inherited

create new model

Parameters

num	number of alphas and support vectors in new model

Definition at line 199 of file KernelMachine.cpp.

◆ data_lock()

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

Parameters

labs	labels used for locking
features	features used for locking

Reimplemented from CMachine.

Definition at line 578 of file KernelMachine.cpp.

◆ data_unlock()

void data_unlock ( )

virtualinherited

Unlocks a locked machine and restores previous state

Reimplemented from CMachine.

Definition at line 609 of file KernelMachine.cpp.

◆ deep_copy()

CSGObject * deep_copy ( ) const

virtualinherited

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

Definition at line 232 of file SGObject.cpp.

◆ equals()

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.

Parameters

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

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

Definition at line 656 of file SGObject.cpp.

◆ get() [1/2]

T get ( const Tag< T > & _tag ) const

inherited

Getter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters

_tag	name and type information of parameter

Returns: value of the parameter identified by the input tag

Definition at line 381 of file SGObject.h.

◆ get() [2/2]

T get ( const std::string & name ) const

inherited

Getter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters

name	name of the parameter

Returns: value of the parameter corresponding to the input name and type

Definition at line 404 of file SGObject.h.

◆ get_alpha()

float64_t get_alpha ( int32_t idx )

inherited

get alpha at given index

Parameters

idx	index of alpha

Returns: alpha

Definition at line 145 of file KernelMachine.cpp.

◆ get_alphas()

SGVector< float64_t > get_alphas ( )

inherited

Returns: vector of alphas

Definition at line 194 of file KernelMachine.cpp.

◆ get_batch_computation_enabled()

bool get_batch_computation_enabled ( )

inherited

check if batch computation is enabled

Returns: if batch computation is enabled

Definition at line 104 of file KernelMachine.cpp.

◆ get_bias()

float64_t get_bias ( )

inherited

get bias

Returns: bias

Definition at line 129 of file KernelMachine.cpp.

◆ get_bias_enabled()

bool get_bias_enabled ( )

inherited

get state of bias

Returns: state of bias

Definition at line 124 of file KernelMachine.cpp.

◆ get_C1()

float64_t get_C1 ( )

inherited

get C1

Returns: C1

Definition at line 161 of file SVM.h.

◆ get_C2()

float64_t get_C2 ( )

inherited

get C2

Returns: C2

Definition at line 167 of file SVM.h.

◆ get_classifier_type()

virtual EMachineType get_classifier_type ( )

virtual

get classifier type

Returns: classifier type LIBSVMONECLASS

Reimplemented from CMachine.

Definition at line 43 of file LibSVMOneClass.h.

◆ get_epsilon()

float64_t get_epsilon ( )

inherited

get epsilon

Returns: epsilon

Definition at line 149 of file SVM.h.

◆ get_global_io()

SGIO * get_global_io ( )

inherited

get the io object

Returns: io object

Definition at line 269 of file SGObject.cpp.

◆ get_global_parallel()

Parallel * get_global_parallel ( )

inherited

get the parallel object

Returns: parallel object

Definition at line 311 of file SGObject.cpp.

◆ get_global_version()

Version * get_global_version ( )

inherited

get the version object

Returns: version object

Definition at line 324 of file SGObject.cpp.

◆ get_kernel()

CKernel * get_kernel ( )

inherited

get kernel

Returns: kernel

Definition at line 93 of file KernelMachine.cpp.

◆ get_labels()

CLabels * get_labels ( )

virtualinherited

get labels

Returns: labels

Definition at line 83 of file Machine.cpp.

◆ get_linadd_enabled()

bool get_linadd_enabled ( )

inherited

check if linadd is enabled

Returns: if linadd is enabled

Definition at line 114 of file KernelMachine.cpp.

◆ get_linear_term()

SGVector< float64_t > get_linear_term ( )

virtualinherited

get linear term

Returns: the linear term

Definition at line 327 of file SVM.cpp.

◆ get_linear_term_array()

float64_t * get_linear_term_array ( )

protectedvirtualinherited

get linear term copy as dynamic array

Returns: linear term copied to a dynamic array

Definition at line 297 of file SVM.cpp.

◆ get_loaded_status()

bool get_loaded_status ( )

inherited

check if svm been loaded

Returns: if svm_loaded is true

Definition at line 227 of file SVM.h.

◆ get_machine_problem_type()

virtual EProblemType get_machine_problem_type ( ) const

virtualinherited

returns type of problem machine solves

Reimplemented in CNeuralNetwork, CRandomForest, CCHAIDTree, CCARTree, and CBaseMulticlassMachine.

Definition at line 311 of file Machine.h.

◆ get_max_train_time()

float64_t get_max_train_time ( )

inherited

get maximum training time

Returns: maximum training time

Definition at line 94 of file Machine.cpp.

◆ get_modelsel_names()

SGStringList< char > get_modelsel_names ( )

inherited

Returns: vector of names of all parameters which are registered for model selection

Definition at line 536 of file SGObject.cpp.

◆ get_modsel_param_descr()

char * get_modsel_param_descr ( const char * param_name )

inherited

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

Parameters

param_name name of the parameter

Returns: description of the parameter

Definition at line 560 of file SGObject.cpp.

◆ get_modsel_param_index()

index_t get_modsel_param_index ( const char * param_name )

inherited

Returns index of model selection parameter with provided index

Parameters

param_name name of model selection parameter

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

Definition at line 573 of file SGObject.cpp.

◆ get_name()

virtual const char* get_name ( ) const

virtual

Returns: object name

Reimplemented from CSVM.

Definition at line 46 of file LibSVMOneClass.h.

◆ get_nu()

float64_t get_nu ( )

inherited

get nu

Returns: nu

Definition at line 155 of file SVM.h.

◆ get_num_support_vectors()

int32_t get_num_support_vectors ( )

inherited

get number of support vectors

Returns: number of support vectors

Definition at line 174 of file KernelMachine.cpp.

◆ get_objective()

float64_t get_objective ( )

inherited

get objective

Returns: objective

Definition at line 218 of file SVM.h.

◆ get_parameters_observable()

SGObservable* get_parameters_observable ( )

inherited

Get parameters observable

Returns: RxCpp observable

Definition at line 415 of file SGObject.h.

◆ get_qpsize()

int32_t get_qpsize ( )

inherited

get qpsize

Returns: qpsize

Definition at line 173 of file SVM.h.

◆ get_shrinking_enabled()

bool get_shrinking_enabled ( )

inherited

get state of shrinking

Returns: if shrinking is enabled

Definition at line 188 of file SVM.h.

◆ get_solver_type()

ESolverType get_solver_type ( )

inherited

get solver type

Returns: solver

Definition at line 109 of file Machine.cpp.

◆ get_support_vector()

int32_t get_support_vector ( int32_t idx )

inherited

get support vector at given index

Parameters

idx	index of support vector

Returns: support vector

Definition at line 139 of file KernelMachine.cpp.

◆ get_support_vectors()

SGVector< int32_t > get_support_vectors ( )

inherited

Returns: all support vectors

Definition at line 189 of file KernelMachine.cpp.

◆ get_tube_epsilon()

float64_t get_tube_epsilon ( )

inherited

get tube epsilon

Returns: tube epsilon

Definition at line 137 of file SVM.h.

◆ has() [1/3]

bool has ( const std::string & name ) const

inherited

Checks if object has a class parameter identified by a name.

Parameters

name	name of the parameter

Returns: true if the parameter exists with the input name

Definition at line 304 of file SGObject.h.

◆ has() [2/3]

bool has ( const Tag< T > & tag ) const

inherited

Checks if object has a class parameter identified by a Tag.

Parameters

tag	tag of the parameter containing name and type information

Returns: true if the parameter exists with the input tag

Definition at line 315 of file SGObject.h.

◆ has() [3/3]

bool has ( const std::string & name ) const

inherited

Checks if a type exists for a class parameter identified by a name.

Parameters

name	name of the parameter

Returns: true if the parameter exists with the input name and type

Definition at line 326 of file SGObject.h.

◆ init_kernel_optimization()

bool init_kernel_optimization ( )

inherited

initialise kernel optimisation

Returns: if operation was successful

Definition at line 216 of file KernelMachine.cpp.

◆ is_data_locked()

bool is_data_locked ( ) const

inherited

Returns: whether this machine is locked

Definition at line 308 of file Machine.h.

◆ is_generic()

bool is_generic ( EPrimitiveType * generic ) const

virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

Parameters

generic set to the type of the generic if returning TRUE

Returns: TRUE if a class template.

Definition at line 330 of file SGObject.cpp.

◆ is_label_valid()

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.

Parameters

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

Reimplemented in CNeuralNetwork, CCARTree, CCHAIDTree, CGaussianProcessRegression, and CBaseMulticlassMachine.

Definition at line 391 of file Machine.h.

◆ list_observable_parameters()

void list_observable_parameters ( )

inherited

Print to stdout a list of observable parameters

Definition at line 878 of file SGObject.cpp.

◆ load()

bool load ( FILE * svm_file )

inherited

load a SVM from file

Parameters

svm_file the file handle

Definition at line 85 of file SVM.cpp.

◆ load_serializable()

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!

Parameters

file	where to load from
prefix	prefix for members

Returns: TRUE if done, otherwise FALSE

Definition at line 403 of file SGObject.cpp.

◆ load_serializable_post()

void load_serializable_post	(		)
throw	(	ShogunException
	)

protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.

Exceptions

ShogunException will be thrown if an error occurs.

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

Definition at line 460 of file SGObject.cpp.

◆ load_serializable_pre()

void load_serializable_pre	(		)
throw	(	ShogunException
	)

protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.

Exceptions

ShogunException will be thrown if an error occurs.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 455 of file SGObject.cpp.

◆ MACHINE_PROBLEM_TYPE()

MACHINE_PROBLEM_TYPE ( PT_BINARY )

inherited

problem type

◆ observe()

void observe ( const ObservedValue value )

protectedinherited

Observe a parameter value and emit them to observer.

Parameters

value Observed parameter's value

Definition at line 828 of file SGObject.cpp.

◆ on_complete()

virtual void on_complete ( )

protectedvirtualinherited

The action which will be done when the user decides to return to prompt and terminate the program execution

Definition at line 427 of file Machine.h.

◆ on_next()

virtual void on_next ( )

protectedvirtualinherited

The action which will be done when the user decides to premature stop the CMachine execution

Definition at line 411 of file Machine.h.

◆ on_pause()

virtual void on_pause ( )

protectedvirtualinherited

The action which will be done when the user decides to pause the CMachine execution

Definition at line 418 of file Machine.h.

◆ parameter_hash_changed()

bool parameter_hash_changed ( )

virtualinherited

Returns: whether parameter combination has changed since last update

Definition at line 296 of file SGObject.cpp.

◆ pause_computation()

SG_FORCED_INLINE void pause_computation ( )

inherited

Pause the algorithm if the flag is set

Definition at line 327 of file Machine.h.

◆ post_lock()

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

virtualinherited

post lock

Definition at line 299 of file Machine.h.

◆ print_modsel_params()

void print_modsel_params ( )

inherited

prints all parameter registered for model selection and their type

Definition at line 512 of file SGObject.cpp.

◆ print_serializable()

void print_serializable ( const char * prefix = "" )

virtualinherited

prints registered parameters out

Parameters

prefix prefix for members

Definition at line 342 of file SGObject.cpp.

◆ ref()

int32_t ref ( )

inherited

increase reference counter

Returns: reference count

Definition at line 186 of file SGObject.cpp.

◆ ref_count()

int32_t ref_count ( )

inherited

display reference counter

Returns: reference count

Definition at line 193 of file SGObject.cpp.

◆ register_observable_param()

void register_observable_param	(	const std::string &	name,
		const SG_OBS_VALUE_TYPE	type,
		const std::string &	description
	)

protectedinherited

Register which params this object can emit.

Parameters

name	the param name
type	the param type
description	a user oriented description

Definition at line 871 of file SGObject.cpp.

◆ register_param() [1/2]

void register_param	(	Tag< T > &	_tag,
		const T &	value
	)

protectedinherited

Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters

_tag	name and type information of parameter
value	value of the parameter

Definition at line 472 of file SGObject.h.

◆ register_param() [2/2]

void register_param	(	const std::string &	name,
		const T &	value
	)

protectedinherited

Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters

name	name of the parameter
value	value of the parameter along with type information

Definition at line 485 of file SGObject.h.

◆ reset_computation_variables()

void reset_computation_variables ( )

protectedinherited

reset the computation variables

Definition at line 403 of file Machine.h.

◆ resume_computation()

SG_FORCED_INLINE void resume_computation ( )

inherited

Resume current computation (sets the flag)

Definition at line 340 of file Machine.h.

◆ save()

bool save ( FILE * svm_file )

inherited

write a SVM to a file

Parameters

svm_file the file handle

Definition at line 201 of file SVM.cpp.

◆ save_serializable()

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

virtualinherited

Save this object to file.

Parameters

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

Returns: TRUE if done, otherwise FALSE

Definition at line 348 of file SGObject.cpp.

◆ save_serializable_post()

void save_serializable_post	(		)
throw	(	ShogunException
	)

protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.

Exceptions

ShogunException will be thrown if an error occurs.

Reimplemented in CKernel.

Definition at line 470 of file SGObject.cpp.

◆ save_serializable_pre()

void save_serializable_pre	(		)
throw	(	ShogunException
	)

protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.

Exceptions

ShogunException will be thrown if an error occurs.

Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 465 of file SGObject.cpp.

◆ set() [1/2]

void set	(	const Tag< T > &	_tag,
		const T &	value
	)

inherited

Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters

_tag	name and type information of parameter
value	value of the parameter

Definition at line 342 of file SGObject.h.

◆ set() [2/2]

void set	(	const std::string &	name,
		const T &	value
	)

inherited

Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters

name	name of the parameter
value	value of the parameter along with type information

Definition at line 368 of file SGObject.h.

◆ set_alpha()

bool set_alpha	(	int32_t	idx,
		float64_t	val
	)

inherited

set alpha at given index to given value

Parameters

idx	index of alpha vector
val	new value of alpha vector

Returns: if operation was successful

Definition at line 164 of file KernelMachine.cpp.

◆ set_alphas()

void set_alphas ( SGVector< float64_t > alphas )

inherited

set alphas to given values

Parameters

alphas float vector with all alphas to set

Definition at line 179 of file KernelMachine.cpp.

◆ set_batch_computation_enabled()

void set_batch_computation_enabled ( bool enable )

inherited

set batch computation enabled

Parameters

enable if batch computation shall be enabled

Definition at line 99 of file KernelMachine.cpp.

◆ set_bias()

void set_bias ( float64_t bias )

inherited

set bias to given value

Parameters

bias new bias

Definition at line 134 of file KernelMachine.cpp.

◆ set_bias_enabled()

void set_bias_enabled ( bool enable_bias )

inherited

set state of bias

Parameters

enable_bias if bias shall be enabled

Definition at line 119 of file KernelMachine.cpp.

◆ set_C()

void set_C	(	float64_t	c_neg,
		float64_t	c_pos
	)

inherited

set C

Parameters

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)

Definition at line 118 of file SVM.h.

◆ set_callback_function()

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

Parameters

m	pointer to mkl object
cb	callback function

Definition at line 227 of file SVM.cpp.

◆ set_defaults()

void set_defaults ( int32_t num_sv = 0 )

inherited

set default values for members a SVM object

Definition at line 44 of file SVM.cpp.

◆ set_epsilon()

void set_epsilon ( float64_t eps )

inherited

set epsilon

Parameters

eps	new epsilon

Definition at line 125 of file SVM.h.

◆ set_generic() [1/16]

void set_generic ( )

inherited

Definition at line 73 of file SGObject.cpp.

◆ set_generic() [2/16]

void set_generic ( )

inherited

Definition at line 78 of file SGObject.cpp.

◆ set_generic() [3/16]

void set_generic ( )

inherited

Definition at line 83 of file SGObject.cpp.

◆ set_generic() [4/16]

void set_generic ( )

inherited

Definition at line 88 of file SGObject.cpp.

◆ set_generic() [5/16]

void set_generic ( )

inherited

Definition at line 93 of file SGObject.cpp.

◆ set_generic() [6/16]

void set_generic ( )

inherited

Definition at line 98 of file SGObject.cpp.

◆ set_generic() [7/16]

void set_generic ( )

inherited

Definition at line 103 of file SGObject.cpp.

◆ set_generic() [8/16]

void set_generic ( )

inherited

Definition at line 108 of file SGObject.cpp.

◆ set_generic() [9/16]

void set_generic ( )

inherited

Definition at line 113 of file SGObject.cpp.

◆ set_generic() [10/16]

void set_generic ( )

inherited

Definition at line 118 of file SGObject.cpp.

◆ set_generic() [11/16]

void set_generic ( )

inherited

Definition at line 123 of file SGObject.cpp.

◆ set_generic() [12/16]

void set_generic ( )

inherited

Definition at line 128 of file SGObject.cpp.

◆ set_generic() [13/16]

void set_generic ( )

inherited

Definition at line 133 of file SGObject.cpp.

◆ set_generic() [14/16]

void set_generic ( )

inherited

Definition at line 138 of file SGObject.cpp.

◆ set_generic() [15/16]

void set_generic ( )

inherited

Definition at line 143 of file SGObject.cpp.

◆ set_generic() [16/16]

void set_generic ( )

inherited

set generic type to T

◆ set_global_io()

void set_global_io ( SGIO * io )

inherited

set the io object

Parameters

io	io object to use

Definition at line 262 of file SGObject.cpp.

◆ set_global_parallel()

void set_global_parallel ( Parallel * parallel )

inherited

set the parallel object

Parameters

parallel parallel object to use

Definition at line 275 of file SGObject.cpp.

◆ set_global_version()

void set_global_version ( Version * version )

inherited

set the version object

Parameters

version version object to use

Definition at line 317 of file SGObject.cpp.

◆ set_kernel()

void set_kernel ( CKernel * k )

inherited

set kernel

Parameters

k kernel

Definition at line 86 of file KernelMachine.cpp.

◆ set_labels()

void set_labels ( CLabels * lab )

virtualinherited

set labels

Parameters

lab labels

Reimplemented in CNeuralNetwork, CGaussianProcessMachine, CCARTree, CStructuredOutputMachine, CRelaxedTree, and CMulticlassMachine.

Definition at line 72 of file Machine.cpp.

◆ set_linadd_enabled()

void set_linadd_enabled ( bool enable )

inherited

set linadd enabled

Parameters

enable if linadd shall be enabled

Definition at line 109 of file KernelMachine.cpp.

◆ set_linear_term()

void set_linear_term ( const SGVector< float64_t > linear_term )

virtualinherited

set linear term of the QP

Parameters

linear_term the linear term

Definition at line 309 of file SVM.cpp.

◆ set_loaded_status()

void set_loaded_status ( bool loaded )

inherited

set svm loaded status

if svm been loaded

Definition at line 233 of file SVM.h.

◆ set_max_train_time()

void set_max_train_time ( float64_t t )

inherited

set maximum training time

Parameters

t	maximimum training time

Definition at line 89 of file Machine.cpp.

◆ set_nu()

void set_nu ( float64_t nue )

inherited

set nu

Parameters

nue new nu

Definition at line 107 of file SVM.h.

◆ set_objective()

void set_objective ( float64_t v )

inherited

set objective

Parameters

v objective

Definition at line 209 of file SVM.h.

◆ set_qpsize()

void set_qpsize ( int32_t qps )

inherited

set qpsize

Parameters

qps	new qpsize

Definition at line 143 of file SVM.h.

◆ set_shrinking_enabled()

void set_shrinking_enabled ( bool enable )

inherited

set state of shrinking

Parameters

enable if shrinking will be enabled

Definition at line 179 of file SVM.h.

◆ set_solver_type()

void set_solver_type ( ESolverType st )

inherited

set solver type

Parameters

st	solver type

Definition at line 104 of file Machine.cpp.

◆ set_store_model_features()

void set_store_model_features ( bool store_model )

virtualinherited

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

Parameters

store_model whether model should be stored after training

Definition at line 114 of file Machine.cpp.

◆ set_support_vector()

bool set_support_vector	(	int32_t	idx,
		int32_t	val
	)

inherited

set support vector at given index to given value

Parameters

idx	index of support vector
val	new value of support vector

Returns: if operation was successful

Definition at line 154 of file KernelMachine.cpp.

◆ set_support_vectors()

void set_support_vectors ( SGVector< int32_t > svs )

inherited

set support vectors to given values

Parameters

svs	integer vector with all support vectors indexes to set

Definition at line 184 of file KernelMachine.cpp.

◆ set_tube_epsilon()

void set_tube_epsilon ( float64_t eps )

inherited

set tube epsilon

Parameters

eps	new tube epsilon

Definition at line 131 of file SVM.h.

◆ shallow_copy()

CSGObject * shallow_copy ( ) const

virtualinherited

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

Reimplemented in CGaussianKernel.

Definition at line 226 of file SGObject.cpp.

◆ store_model_features()

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.

Reimplemented from CMachine.

Definition at line 405 of file KernelMachine.cpp.

◆ subscribe_to_parameters()

void subscribe_to_parameters ( ParameterObserverInterface * obs )

inherited

Subscribe a parameter observer to watch over params

Definition at line 811 of file SGObject.cpp.

◆ supports_locking()

bool supports_locking ( ) const

virtualinherited

Returns: whether machine supports locking

Reimplemented from CMachine.

Definition at line 654 of file KernelMachine.cpp.

◆ train()

bool train ( CFeatures * data = NULL )

virtualinherited

train machine

Parameters

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.

Returns: whether training was successful

Reimplemented in CRelaxedTree, CAutoencoder, CLinearMachine, CSGDQN, and COnlineSVMSGD.

Definition at line 43 of file Machine.cpp.

◆ train_locked()

bool train_locked ( SGVector< index_t > indices )

virtualinherited

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

Parameters

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

Returns: whether training was successful

Reimplemented from CMachine.

Definition at line 434 of file KernelMachine.cpp.

◆ train_machine()

bool train_machine ( CFeatures * data = NULL )

protectedvirtual

train SVM

Parameters

data	training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data)

Returns: whether training was successful

Reimplemented from CMachine.

Definition at line 31 of file LibSVMOneClass.cpp.

◆ train_require_labels()

virtual bool train_require_labels ( ) const

protectedvirtual

returns whether machine require labels for training

Reimplemented from CMachine.

Definition at line 50 of file LibSVMOneClass.h.

◆ unref()

int32_t unref ( )

inherited

decrement reference counter and deallocate object if refcount is zero before or after decrementing it

Returns: reference count

Definition at line 200 of file SGObject.cpp.

◆ unset_generic()

void unset_generic ( )

inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 337 of file SGObject.cpp.

◆ update_parameter_hash()

void update_parameter_hash ( )

virtualinherited

Updates the hash of current parameter combination

Definition at line 282 of file SGObject.cpp.

Member Data Documentation

◆ C1

float64_t C1

protectedinherited

C1 regularization const

Definition at line 272 of file SVM.h.

◆ C2

float64_t C2

protectedinherited

C2

Definition at line 274 of file SVM.h.

◆ callback

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

Definition at line 284 of file SVM.h.

◆ epsilon

float64_t epsilon

protectedinherited

epsilon

Definition at line 266 of file SVM.h.

◆ io

SGIO* io

inherited

io

Definition at line 600 of file SGObject.h.

◆ kernel

CKernel* kernel

protectedinherited

kernel

Definition at line 307 of file KernelMachine.h.

◆ m_alpha

SGVector<float64_t> m_alpha

protectedinherited

coefficients alpha

Definition at line 328 of file KernelMachine.h.

◆ m_bias

float64_t m_bias

protectedinherited

bias term b

Definition at line 325 of file KernelMachine.h.

◆ m_cancel_computation

std::atomic<bool> m_cancel_computation

protectedinherited

Cancel computation

Definition at line 448 of file Machine.h.

◆ m_custom_kernel

CCustomKernel* m_custom_kernel

protectedinherited

is filled with pre-computed custom kernel on data lock

Definition at line 310 of file KernelMachine.h.

◆ m_data_locked

bool m_data_locked

protectedinherited

whether data is locked

Definition at line 445 of file Machine.h.

◆ m_gradient_parameters

Parameter* m_gradient_parameters

inherited

parameters wrt which we can compute gradients

Definition at line 615 of file SGObject.h.

◆ m_hash

uint32_t m_hash

inherited

Hash of parameter values

Definition at line 618 of file SGObject.h.

◆ m_kernel_backup

CKernel* m_kernel_backup

protectedinherited

old kernel is stored here on data lock

Definition at line 313 of file KernelMachine.h.

◆ m_labels

CLabels* m_labels

protectedinherited

labels

Definition at line 436 of file Machine.h.

◆ m_linear_term

SGVector<float64_t> m_linear_term

protectedinherited

linear term in qp

Definition at line 261 of file SVM.h.

◆ m_max_train_time

float64_t m_max_train_time

protectedinherited

maximum training time

Definition at line 433 of file Machine.h.

◆ m_model_selection_parameters

Parameter* m_model_selection_parameters

inherited

model selection parameters

Definition at line 612 of file SGObject.h.

◆ m_mutex

std::mutex m_mutex

protectedinherited

Mutex used to pause threads

Definition at line 457 of file Machine.h.

◆ m_parameters

Parameter* m_parameters

inherited

parameters

Definition at line 609 of file SGObject.h.

◆ m_pause_computation

std::condition_variable m_pause_computation

protectedinherited

Conditional variable to make threads wait

Definition at line 454 of file Machine.h.

◆ m_pause_computation_flag

std::atomic<bool> m_pause_computation_flag

protectedinherited

Pause computation flag

Definition at line 451 of file Machine.h.

◆ m_solver_type

ESolverType m_solver_type

protectedinherited

solver type

Definition at line 439 of file Machine.h.

◆ m_store_model_features

bool m_store_model_features

protectedinherited

whether model features should be stored after training

Definition at line 442 of file Machine.h.

◆ m_svs

SGVector<int32_t> m_svs

protectedinherited

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

Definition at line 331 of file KernelMachine.h.

◆ mkl

CMKL* mkl

protectedinherited

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

Definition at line 287 of file SVM.h.

◆ nu

float64_t nu

protectedinherited

nu

Definition at line 270 of file SVM.h.

◆ objective

float64_t objective

protectedinherited

objective

Definition at line 276 of file SVM.h.

◆ parallel

Parallel* parallel

inherited

parallel

Definition at line 603 of file SGObject.h.

◆ qpsize

int32_t qpsize

protectedinherited

qpsize

Definition at line 278 of file SVM.h.

◆ svm_loaded

bool svm_loaded

protectedinherited

if SVM is loaded

Definition at line 264 of file SVM.h.

◆ tube_epsilon

float64_t tube_epsilon

protectedinherited

tube epsilon for support vector regression

Definition at line 268 of file SVM.h.

◆ use_batch_computation

bool use_batch_computation

protectedinherited

if batch computation is enabled

Definition at line 316 of file KernelMachine.h.

◆ use_bias

bool use_bias

protectedinherited

if bias shall be used

Definition at line 322 of file KernelMachine.h.

◆ use_linadd

bool use_linadd

protectedinherited

if linadd is enabled

Definition at line 319 of file KernelMachine.h.

◆ use_shrinking

bool use_shrinking

protectedinherited

if shrinking shall be used

Definition at line 280 of file SVM.h.

◆ version

Version* version

inherited

version

Definition at line 606 of file SGObject.h.

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

Detailed Description

Public Types

Public Member Functions

Public Attributes

Protected Member Functions

Protected Attributes

Member Typedef Documentation

◆ SGObservable

◆ SGSubject

◆ SGSubscriber

Constructor & Destructor Documentation

◆ CLibSVMOneClass() [1/2]

◆ CLibSVMOneClass() [2/2]

◆ ~CLibSVMOneClass()

Member Function Documentation

◆ apply()

◆ apply_binary()

◆ apply_get_outputs()

◆ apply_latent()

◆ apply_locked()

◆ apply_locked_binary()

◆ apply_locked_get_output()

◆ apply_locked_latent()

◆ apply_locked_multiclass()

◆ apply_locked_regression()

◆ apply_locked_structured()

◆ apply_multiclass()

◆ apply_one()

◆ apply_regression()

◆ apply_structured()

◆ build_gradient_parameter_dictionary()

◆ cancel_computation()

◆ clone()

◆ clone_parameters()

◆ compute_svm_dual_objective()

◆ compute_svm_primal_objective()

◆ connect_to_signal_handler()

◆ create_new_model()

◆ data_lock()

◆ data_unlock()

◆ deep_copy()

◆ equals()

◆ get() [1/2]

◆ get() [2/2]

◆ get_alpha()

◆ get_alphas()

◆ get_batch_computation_enabled()

◆ get_bias()

◆ get_bias_enabled()

◆ get_C1()

◆ get_C2()

◆ get_classifier_type()

◆ get_epsilon()

◆ get_global_io()

◆ get_global_parallel()

◆ get_global_version()

◆ get_kernel()

◆ get_labels()

◆ get_linadd_enabled()

◆ get_linear_term()

◆ get_linear_term_array()

◆ get_loaded_status()

◆ get_machine_problem_type()

◆ get_max_train_time()

◆ get_modelsel_names()

◆ get_modsel_param_descr()

◆ get_modsel_param_index()

◆ get_name()

◆ get_nu()

◆ get_num_support_vectors()

◆ get_objective()

◆ get_parameters_observable()

◆ get_qpsize()

◆ get_shrinking_enabled()

◆ get_solver_type()

◆ get_support_vector()

◆ get_support_vectors()

◆ get_tube_epsilon()

◆ has() [1/3]

◆ has() [2/3]