Detailed Description

class SVMOcas

Definition at line 32 of file SVMOcas.h.

Inheritance diagram for CSVMOcas:

Public Member Functions
	CSVMOcas ()
	CSVMOcas (E_SVM_TYPE type)
	CSVMOcas (float64_t C, CDotFeatures traindat, CLabels trainlab)
virtual	~CSVMOcas ()
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_epsilon (float64_t eps)
float64_t	get_epsilon ()
void	set_bias_enabled (bool enable_bias)
bool	get_bias_enabled ()
void	set_bufsize (int32_t sz)
int32_t	get_bufsize ()
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)
virtual const char *	get_name () const
Protected Member Functions inherited from CLinearMachine
virtual void	store_model_features ()

Static Protected Member Functions
static void	compute_W (float64_t sq_norm_W, float64_t dp_WoldW, float64_t alpha, uint32_t nSel, void ptr)
static float64_t	update_W (float64_t t, void *ptr)
static int	add_new_cut (float64_t new_col_H, uint32_t new_cut, uint32_t cut_length, uint32_t nSel, void *ptr)
static int	compute_output (float64_t output, void ptr)
static int	sort (float64_t vals, float64_t data, uint32_t size)
static void	print (ocas_return_value_T value)

Protected Attributes
bool	use_bias
int32_t	bufsize
float64_t	C1
float64_t	C2
float64_t	epsilon
E_SVM_TYPE	method
float64_t *	old_w
float64_t	old_bias
float64_t *	tmp_a_buf
SGVector< float64_t >	lab
float64_t **	cp_value
uint32_t **	cp_index
uint32_t *	cp_nz_dims
float64_t *	cp_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

CSVMOcas ( )

default constructor

Definition at line 24 of file SVMOcas.cpp.

CSVMOcas ( E_SVM_TYPE type )

constructor

Parameters

type	a E_SVM_TYPE

Definition at line 30 of file SVMOcas.cpp.

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

constructor

Parameters

C	constant C
traindat	training features
trainlab	labels for training features

Definition at line 37 of file SVMOcas.cpp.

~CSVMOcas ( )

virtual

Definition at line 50 of file SVMOcas.cpp.

Member Function Documentation

int add_new_cut	(	float64_t *	new_col_H,
		uint32_t *	new_cut,
		uint32_t	cut_length,
		uint32_t	nSel,
		void *	ptr
	)

staticprotected

add new cut

Parameters

new_col_H	new col H
new_cut	new cut
cut_length	length of cut
nSel	nSel
ptr	ptr

Definition at line 185 of file SVMOcas.cpp.

int compute_output	(	float64_t *	output,
		void *	ptr
	)

staticprotected

compute output

Parameters

output	output
ptr	ptr

Definition at line 272 of file SVMOcas.cpp.

void compute_W	(	float64_t *	sq_norm_W,
		float64_t *	dp_WoldW,
		float64_t *	alpha,
		uint32_t	nSel,
		void *	ptr
	)

staticprotected

compute W

Parameters

sq_norm_W	square normed W
dp_WoldW	dp W old W
alpha	alpha
nSel	nSel
ptr	ptr

Definition at line 298 of file SVMOcas.cpp.

bool get_bias_enabled ( )

check if bias is enabled

Returns: if bias is enabled

Definition at line 103 of file SVMOcas.h.

int32_t get_bufsize ( )

get buffer size

Returns: buffer size

Definition at line 115 of file SVMOcas.h.

float64_t get_C1 ( )

get C1

Returns: C1

Definition at line 73 of file SVMOcas.h.

float64_t get_C2 ( )

get C2

Returns: C2

Definition at line 79 of file SVMOcas.h.

virtual EClassifierType get_classifier_type ( )

virtual

get classifier type

Returns: classifier type SVMOCAS

Reimplemented from CMachine.

Definition at line 59 of file SVMOcas.h.

float64_t get_epsilon ( )

get epsilon

Returns: epsilon

Definition at line 91 of file SVMOcas.h.

virtual const char* get_name ( ) const

protectedvirtual

Returns: object name

Reimplemented from CLinearMachine.

Definition at line 183 of file SVMOcas.h.

static void print ( ocas_return_value_T value )

staticprotected

print nothing

Definition at line 166 of file SVMOcas.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 97 of file SVMOcas.h.

void set_bufsize ( int32_t sz )

set buffer size

Parameters

sz	buffer size

Definition at line 109 of file SVMOcas.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 67 of file SVMOcas.h.

void set_epsilon ( float64_t eps )

set epsilon

Parameters

eps	new epsilon

Definition at line 85 of file SVMOcas.h.

int sort	(	float64_t *	vals,
		float64_t *	data,
		uint32_t	size
	)

staticprotected

sort

Parameters

vals	vals
data	data
size	size

Definition at line 261 of file SVMOcas.cpp.

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 54 of file SVMOcas.cpp.

float64_t update_W	(	float64_t	t,
		void *	ptr
	)

staticprotected

update W

Parameters

t	t
ptr	ptr

Returns: something floaty

Definition at line 158 of file SVMOcas.cpp.

Member Data Documentation

int32_t bufsize

protected

buffer size

Definition at line 191 of file SVMOcas.h.

float64_t C1

protected

C1

Definition at line 193 of file SVMOcas.h.

float64_t C2

protected

C2

Definition at line 195 of file SVMOcas.h.

float64_t* cp_bias

protected

bias dimensions

Definition at line 218 of file SVMOcas.h.

uint32_t** cp_index

protected

cutting plane index

Definition at line 214 of file SVMOcas.h.

uint32_t* cp_nz_dims

protected

cutting plane dimensions

Definition at line 216 of file SVMOcas.h.

float64_t** cp_value

protected

sparse representation of cutting planes

Definition at line 212 of file SVMOcas.h.

float64_t epsilon

protected

epsilon

Definition at line 197 of file SVMOcas.h.

SGVector<float64_t> lab

protected

labels

Definition at line 208 of file SVMOcas.h.

E_SVM_TYPE method

protected

method

Definition at line 199 of file SVMOcas.h.

float64_t old_bias

protected

old bias

Definition at line 204 of file SVMOcas.h.

float64_t* old_w

protected

old W

Definition at line 202 of file SVMOcas.h.

float64_t* tmp_a_buf

protected

nDim big

Definition at line 206 of file SVMOcas.h.

bool use_bias

protected

if bias is used

Definition at line 189 of file SVMOcas.h.

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

Detailed Description

Public Member Functions

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Additional Inherited Members

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation