CSVMLin Class Reference

Detailed Description

class SVMLin

Definition at line 22 of file SVMLin.h.

Inheritance diagram for CSVMLin:

Public Member Functions
	CSVMLin ()
	CSVMLin (float64_t C, CDotFeatures *traindat, CLabels *trainlab)
virtual	~CSVMLin ()
virtual EClassifierType	get_classifier_type ()
void	set_C (float64_t c_neg, float64_t c_pos)
float64_t	get_C1 ()
float64_t	get_C2 ()
void	set_bias_enabled (bool enable_bias)
bool	get_bias_enabled ()
void	set_epsilon (float64_t eps)
float64_t	get_epsilon ()
virtual const char *	get_name () const
Public Member Functions inherited from CLinearMachine
	CLinearMachine ()
virtual	~CLinearMachine ()
void	get_w (float64_t *&dst_w, int32_t &dst_dims)
SGVector< float64_t >	get_w ()
void	set_w (SGVector< float64_t > src_w)
void	set_bias (float64_t b)
float64_t	get_bias ()
virtual bool	load (FILE *srcfile)
virtual bool	save (FILE *dstfile)
virtual void	set_features (CDotFeatures *feat)
virtual CLabels *	apply ()
virtual CLabels *	apply (CFeatures *data)
virtual float64_t	apply (int32_t vec_idx)
	get output for example "vec_idx"
virtual CDotFeatures *	get_features ()
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)

Protected Member Functions
virtual bool	train_machine (CFeatures *data=NULL)
Protected Member Functions inherited from CLinearMachine
virtual void	store_model_features ()

Protected Attributes
float64_t	C1
float64_t	C2
float64_t	epsilon
bool	use_bias
Protected Attributes inherited from CLinearMachine
int32_t	w_dim
float64_t *	w
float64_t	bias
CDotFeatures *	features
Protected Attributes inherited from CMachine
float64_t	max_train_time
CLabels *	labels
ESolverType	solver_type
bool	m_store_model_features

Additional Inherited Members
Public Attributes inherited from CSGObject
SGIO *	io
Parallel *	parallel
Version *	version
Parameter *	m_parameters
Parameter *	m_model_selection_parameters

Constructor & Destructor Documentation

CSVMLin

(

)

default constructor

Definition at line 21 of file SVMLin.cpp.

CSVMLin	(	float64_t	C,
		CDotFeatures *	traindat,
		CLabels *	trainlab
	)

constructor

Parameters

C	constant C
traindat	training features
trainlab	labels for features

Definition at line 26 of file SVMLin.cpp.

~CSVMLin ( )

virtual

Definition at line 35 of file SVMLin.cpp.

Member Function Documentation

bool get_bias_enabled

(

)

get if bias is enabled

Returns

if bias is enabled

Definition at line 75 of file SVMLin.h.

float64_t get_C1

(

)

get C1

Returns

C1

Definition at line 57 of file SVMLin.h.

float64_t get_C2

(

)

get C2

Returns

C2

Definition at line 63 of file SVMLin.h.

virtual EClassifierType get_classifier_type ( )

virtual

get classifier type

Returns

classifier type SVMLIN

Reimplemented from CMachine.

Definition at line 43 of file SVMLin.h.

float64_t get_epsilon

(

)

get epsilon

Returns

epsilon

Definition at line 87 of file SVMLin.h.

virtual const char* get_name ( ) const

virtual

Returns

object name

Reimplemented from CLinearMachine.

Definition at line 90 of file SVMLin.h.

void set_bias_enabled

(

bool

enable_bias

)

set if bias shall be enabled

Parameters

enable_bias

if bias shall be enabled

Definition at line 69 of file SVMLin.h.

void set_C	(	float64_t	c_neg,
		float64_t	c_pos
	)

set C

Parameters

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

Definition at line 51 of file SVMLin.h.

void set_epsilon

(

float64_t

eps

)

set epsilon

Parameters

eps	new epsilon

Definition at line 81 of file SVMLin.h.

bool train_machine ( CFeatures *  data = NULL )

protectedvirtual

train SVM classifier

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 39 of file SVMLin.cpp.

Member Data Documentation

float64_t C1

protected

C1

Definition at line 105 of file SVMLin.h.

float64_t C2

protected

C2

Definition at line 107 of file SVMLin.h.

float64_t epsilon

protected

epsilon

Definition at line 109 of file SVMLin.h.

bool use_bias

protected

if bias is used

Definition at line 112 of file SVMLin.h.

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

• SVMLin.h
• SVMLin.cpp