Detailed Description

Class LibSVR, performs support vector regression using LibSVM.

The SVR solution can be expressed as

$f({\bf x})=\sum_{i=1}^{N} \alpha_i k({\bf x}, {\bf x_i})+b$

where $\alpha$ and $b$ are determined in training, i.e. using a pre-specified kernel, a given tube-epsilon for the epsilon insensitive loss, the follwoing quadratic problem is minimized (using sequential minimal decomposition (SMO))

$\begin{eqnarray*} \max_{{\bf \alpha},{\bf \alpha}^*} &-\frac{1}{2}\sum_{i,j=1}^N(\alpha_i-\alpha_i^*)(\alpha_j-\alpha_j^*){\bf x}_i^T {\bf x}_j -\sum_{i=1}^N(\alpha_i+\alpha_i^*)\epsilon - \sum_{i=1}^N(\alpha_i-\alpha_i^*)y_i\\ \mbox{wrt}:& {\bf \alpha},{\bf \alpha}^*\in{\bf R}^N\\ \mbox{s.t.}:& 0\leq \alpha_i,\alpha_i^*\leq C,\, \forall i=1\dots N\\ &\sum_{i=1}^N(\alpha_i-\alpha_i^*)y_i=0 \end{eqnarray*}$

Note that the SV regression problem is reduced to the standard SV classification problem by introducing artificial labels $-y_i$ which leads to the epsilon insensitive loss constraints *

$\begin{eqnarray*} {\bf w}^T{\bf x}_i+b-c_i-\xi_i\leq 0,&\, \forall i=1\dots N\\ -{\bf w}^T{\bf x}_i-b-c_i^*-\xi_i^*\leq 0,&\, \forall i=1\dots N \end{eqnarray*}$

with $c_i=y_i+ \epsilon$ and $c_i^*=-y_i+ \epsilon$

Definition at line 51 of file LibSVR.h.

Inheritance diagram for CLibSVR:

[legend]

Public Member Functions
	CLibSVR ()

	CLibSVR (float64_t C, float64_t epsilon, CKernel k, CLabels lab)

virtual	~CLibSVR ()

virtual EClassifierType	get_classifier_type ()

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 bool	train_machine (CFeatures *data=NULL)

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)

Protected Attributes
svm_problem	problem

svm_parameter	param

struct svm_model *	model

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

Additional Inherited Members
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

Constructor & Destructor Documentation

CLibSVR ( )

default constructor

Definition at line 16 of file LibSVR.cpp.

CLibSVR	(	float64_t	C,
		float64_t	epsilon,
		CKernel *	k,
		CLabels *	lab
	)

constructor

Parameters

C	constant C
epsilon	tube epsilon
k	kernel
lab	labels

Definition at line 22 of file LibSVR.cpp.

~CLibSVR ( )

virtual

Definition at line 33 of file LibSVR.cpp.

Member Function Documentation

EClassifierType get_classifier_type ( )

virtual

get classifier type

Returns: classifie type LIBSVR

Reimplemented from CMachine.

Definition at line 38 of file LibSVR.cpp.

virtual const char* get_name ( ) const

virtual

Returns: object name

Reimplemented from CSVM.

Definition at line 74 of file LibSVR.h.

bool train_machine ( CFeatures * data = NULL )

protectedvirtual

train regression

Parameters

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

Returns: whether training was successful

Reimplemented from CMachine.

Definition at line 43 of file LibSVR.cpp.

Member Data Documentation

struct svm_model* model

protected

SVM model

Definition at line 93 of file LibSVR.h.

svm_parameter param

protected

SVM parameter

Definition at line 90 of file LibSVR.h.

svm_problem problem

protected

SVM problem

Definition at line 88 of file LibSVR.h.

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

Detailed Description

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation