Detailed Description

Multiple Kernel Learning for two-class-classification.

Learns an SVM classifier and its kernel weights. Makes only sense if multiple kernels are used.

See Also: CMKL

Definition at line 25 of file MKLClassification.h.

Inheritance diagram for CMKLClassification:

Public Member Functions
	CMKLClassification (CSVM *s=NULL)

virtual	~CMKLClassification ()

virtual float64_t	compute_sum_alpha ()

Public Member Functions inherited from CMKL
	CMKL (CSVM *s=NULL)

virtual	~CMKL ()

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)

virtual const char *	get_name () const

Public Member Functions inherited from CSVM
	CSVM (int32_t num_sv=0)

	CSVM (float64_t C, CKernel k, CLabels lab)

virtual	~CSVM ()

void	set_defaults (int32_t num_sv=0)

virtual SGVector< float64_t >	get_linear_term ()

virtual void	set_linear_term (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))

Public Member Functions inherited from CKernelMachine
	CKernelMachine ()

virtual	~CKernelMachine ()

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 CLabels *	apply ()

virtual CLabels *	apply (CFeatures *data)

virtual float64_t	apply (int32_t num)

Public Member Functions inherited from CMachine
	CMachine ()

virtual	~CMachine ()

virtual bool	train (CFeatures *data=NULL)

virtual void	set_labels (CLabels *lab)

virtual CLabels *	get_labels ()

virtual float64_t	get_label (int32_t i)

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)

Public Member Functions inherited from CSGObject
	CSGObject ()

	CSGObject (const CSGObject &orig)

virtual	~CSGObject ()

virtual bool	is_generic (EPrimitiveType *generic) const

template<class T >
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 ()

SGVector< char * >	get_modelsel_names ()

char *	get_modsel_param_descr (const char *param_name)

index_t	get_modsel_param_index (const char *param_name)

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 ()

Protected Member Functions
virtual void	init_training ()

virtual EClassifierType	get_classifier_type ()

Protected Member Functions inherited from CMKL
virtual bool	train_machine (CFeatures *data=NULL)

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)

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_lpx_status (LPX *lp)

Protected Member Functions inherited from CSVM
virtual float64_t *	get_linear_term_array ()

Protected Member Functions inherited from CKernelMachine
virtual void	store_model_features ()

Protected Member Functions inherited from CSGObject
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)

Additional Inherited Members
Static Public Member Functions inherited from CMKL
static bool	perform_mkl_step_helper (CMKL mkl, const float64_t sumw, const float64_t suma)

Static Public Member Functions inherited from CKernelMachine
static void *	apply_helper (void *p)

Public Attributes inherited from CSGObject
SGIO *	io

Parallel *	parallel

Version *	version

Parameter *	m_parameters

Parameter *	m_model_selection_parameters

Protected Attributes inherited from CMKL
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

LPX *	lp_glpk

bool	lp_initialized

Protected Attributes inherited from CSVM
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

Protected Attributes inherited from CKernelMachine
CKernel *	kernel

bool	use_batch_computation

bool	use_linadd

bool	use_bias

float64_t	m_bias

SGVector< float64_t >	m_alpha

SGVector< int32_t >	m_svs

Protected Attributes inherited from CMachine
float64_t	max_train_time

CLabels *	labels

ESolverType	solver_type

bool	m_store_model_features

Constructor & Destructor Documentation

CMKLClassification ( CSVM * s = NULL )

Constructor

Parameters

s	SVM to use as constraint generator in MKL SILP

Definition at line 7 of file MKLClassification.cpp.

~CMKLClassification ( )

virtual

Destructor

Definition at line 18 of file MKLClassification.cpp.

Member Function Documentation

float64_t compute_sum_alpha ( )

virtual

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

Implements CMKL.

Definition at line 21 of file MKLClassification.cpp.

virtual EClassifierType get_classifier_type ( )

protectedvirtual

get classifier type

Returns: classifier type MKL_CLASSIFICATION

Reimplemented from CMachine.

Definition at line 53 of file MKLClassification.h.

void init_training ( )

protectedvirtual

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

Implements CMKL.

Definition at line 31 of file MKLClassification.cpp.

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

Detailed Description

Public Member Functions

Protected Member Functions

Additional Inherited Members

Constructor & Destructor Documentation

Member Function Documentation