CWDSVMOcas Class Reference

Detailed Description

class WDSVMOcas

Definition at line 26 of file WDSVMOcas.h.

Inheritance diagram for CWDSVMOcas:

Public Member Functions
	CWDSVMOcas ()
	CWDSVMOcas (E_SVM_TYPE type)
	CWDSVMOcas (float64_t C, int32_t d, int32_t from_d, CStringFeatures< uint8_t > *traindat, CLabels *trainlab)
virtual	~CWDSVMOcas ()
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_features (CStringFeatures< uint8_t > *feat)
CStringFeatures< uint8_t > *	get_features ()
void	set_bias_enabled (bool enable_bias)
bool	get_bias_enabled ()
void	set_bufsize (int32_t sz)
int32_t	get_bufsize ()
void	set_degree (int32_t d, int32_t from_d)
int32_t	get_degree ()
CLabels *	apply ()
virtual CLabels *	apply (CFeatures *data)
virtual float64_t	apply (int32_t num)
void	set_normalization_const ()
float64_t	get_normalization_const ()
Public Member Functions inherited from CMachine
	CMachine ()
virtual	~CMachine ()
virtual bool	train (CFeatures *data=NULL)
virtual bool	load (FILE *srcfile)
virtual bool	save (FILE *dstfile)
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
int32_t	set_wd_weights ()
virtual const char *	get_name () const
virtual bool	train_machine (CFeatures *data=NULL)
Protected Member Functions inherited from CMachine
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)

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 void *	add_new_cut_helper (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 void *	compute_output_helper (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
CStringFeatures< uint8_t > *	features
bool	use_bias
int32_t	bufsize
float64_t	C1
float64_t	C2
float64_t	epsilon
E_SVM_TYPE	method
int32_t	degree
int32_t	from_degree
float32_t *	wd_weights
int32_t	num_vec
int32_t	string_length
int32_t	alphabet_size
float64_t	normalization_const
float64_t	bias
float64_t	old_bias
int32_t *	w_offsets
int32_t	w_dim
int32_t	w_dim_single_char
float32_t *	w
float32_t *	old_w
float64_t *	lab
float32_t **	cuts
float64_t *	cp_bias
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

CWDSVMOcas

(

)

default constructor

Definition at line 48 of file WDSVMOcas.cpp.

CWDSVMOcas

(

E_SVM_TYPE

type

)

constructor

Parameters

type	type of SVM

Definition at line 64 of file WDSVMOcas.cpp.

CWDSVMOcas	(	float64_t	C,
		int32_t	d,
		int32_t	from_d,
		CStringFeatures< uint8_t > *	traindat,
		CLabels *	trainlab
	)

constructor

Parameters

C	constant C
d	degree
from_d	from degree
traindat	training features
trainlab	labels for training features

Definition at line 78 of file WDSVMOcas.cpp.

~CWDSVMOcas ( )

virtual

Definition at line 95 of file WDSVMOcas.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 346 of file WDSVMOcas.cpp.

void * add_new_cut_helper ( void *  ptr )

staticprotected

helper function for adding a new cut

Parameters

ptr

Returns

ptr

Definition at line 294 of file WDSVMOcas.cpp.

CLabels * apply ( )

virtual

classify all examples

Returns

resulting labels

Implements CMachine.

Definition at line 99 of file WDSVMOcas.cpp.

CLabels * apply ( CFeatures *  data )

virtual

classify objects

Parameters

data	(test)data to be classified

Returns

classified labels

Implements CMachine.

Definition at line 121 of file WDSVMOcas.cpp.

virtual float64_t apply ( int32_t  num )

virtual

classify one example

Parameters

num	number of example to classify

Returns

classified result

Reimplemented from CMachine.

Definition at line 169 of file WDSVMOcas.h.

int compute_output ( float64_t *  output, void *  ptr  )

staticprotected

compute output

Parameters

output	output
ptr	ptr

Definition at line 535 of file WDSVMOcas.cpp.

void * compute_output_helper ( void *  ptr )

staticprotected

helper function for computing the output

Parameters

ptr

Returns

ptr

Definition at line 443 of file WDSVMOcas.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 603 of file WDSVMOcas.cpp.

bool get_bias_enabled

(

)

check if bias is enabled

Returns

if bias is enabled

Definition at line 120 of file WDSVMOcas.h.

int32_t get_bufsize

(

)

get buffer size

Returns

buffer size

Definition at line 132 of file WDSVMOcas.h.

float64_t get_C1

(

)

get C1

Returns

C1

Definition at line 69 of file WDSVMOcas.h.

float64_t get_C2

(

)

get C2

Returns

C2

Definition at line 75 of file WDSVMOcas.h.

virtual EClassifierType get_classifier_type ( )

virtual

get classifier type

Returns

classifier type WDSVMOCAS

Reimplemented from CMachine.

Definition at line 55 of file WDSVMOcas.h.

int32_t get_degree

(

)

get degree

Returns

degree

Definition at line 149 of file WDSVMOcas.h.

float64_t get_epsilon

(

)

get epsilon

Returns

epsilon

Definition at line 87 of file WDSVMOcas.h.

CStringFeatures<uint8_t>* get_features

(

)

get features

Returns

features

Definition at line 104 of file WDSVMOcas.h.

virtual const char* get_name ( ) const

protectedvirtual

Returns

object name

Implements CSGObject.

Definition at line 292 of file WDSVMOcas.h.

float64_t get_normalization_const

(

)

get normalization const

Returns

normalization const

Definition at line 213 of file WDSVMOcas.h.

static void print ( ocas_return_value_T  value )

staticprotected

print nothing

Definition at line 285 of file WDSVMOcas.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 114 of file WDSVMOcas.h.

void set_bufsize

(

int32_t

sz

)

set buffer size

Parameters

sz	buffer size

Definition at line 126 of file WDSVMOcas.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 63 of file WDSVMOcas.h.

void set_degree	(	int32_t	d,
		int32_t	from_d
	)

set degree

Parameters

d	degree
from_d	from degree

Definition at line 139 of file WDSVMOcas.h.

void set_epsilon

(

float64_t

eps

)

set epsilon

Parameters

eps	new epsilon

Definition at line 81 of file WDSVMOcas.h.

void set_features

(

CStringFeatures< uint8_t > *

feat

)

set features

Parameters

feat	features to set

Definition at line 93 of file WDSVMOcas.h.

void set_normalization_const

(

)

set normalization const

Definition at line 198 of file WDSVMOcas.h.

int32_t set_wd_weights ( )

protected

set wd weights

Returns

w_dim_single_c

Definition at line 136 of file WDSVMOcas.cpp.

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

staticprotected

sort

Parameters

vals	vals
data	data
size	size

Definition at line 432 of file WDSVMOcas.cpp.

bool train_machine ( CFeatures *  data = NULL )

protectedvirtual

train 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 154 of file WDSVMOcas.cpp.

float64_t update_W ( float64_t  t, void *  ptr  )

staticprotected

update W

Parameters

t	t
ptr	ptr

Returns

something floaty

Definition at line 261 of file WDSVMOcas.cpp.

Member Data Documentation

int32_t alphabet_size

protected

size of alphabet

Definition at line 332 of file WDSVMOcas.h.

float64_t bias

protected

bias

Definition at line 338 of file WDSVMOcas.h.

int32_t bufsize

protected

buffer size

Definition at line 311 of file WDSVMOcas.h.

float64_t C1

protected

C1

Definition at line 313 of file WDSVMOcas.h.

float64_t C2

protected

C2

Definition at line 315 of file WDSVMOcas.h.

float64_t* cp_bias

protected

bias dimensions

Definition at line 357 of file WDSVMOcas.h.

float32_t** cuts

protected

cuts

Definition at line 355 of file WDSVMOcas.h.

int32_t degree

protected

degree

Definition at line 322 of file WDSVMOcas.h.

float64_t epsilon

protected

epsilon

Definition at line 317 of file WDSVMOcas.h.

CStringFeatures<uint8_t>* features

protected

features

Definition at line 307 of file WDSVMOcas.h.

int32_t from_degree

protected

from degree

Definition at line 324 of file WDSVMOcas.h.

float64_t* lab

protected

labels

Definition at line 352 of file WDSVMOcas.h.

E_SVM_TYPE method

protected

method

Definition at line 319 of file WDSVMOcas.h.

float64_t normalization_const

protected

normalization const

Definition at line 335 of file WDSVMOcas.h.

int32_t num_vec

protected

num vectors

Definition at line 328 of file WDSVMOcas.h.

float64_t old_bias

protected

old_bias

Definition at line 340 of file WDSVMOcas.h.

float32_t* old_w

protected

old w

Definition at line 350 of file WDSVMOcas.h.

int32_t string_length

protected

length of string in vector

Definition at line 330 of file WDSVMOcas.h.

bool use_bias

protected

if bias shall be used

Definition at line 309 of file WDSVMOcas.h.

float32_t* w

protected

w

Definition at line 348 of file WDSVMOcas.h.

int32_t w_dim

protected

w dim

Definition at line 344 of file WDSVMOcas.h.

int32_t w_dim_single_char

protected

w dim of a single char

Definition at line 346 of file WDSVMOcas.h.

int32_t* w_offsets

protected

w offsets

Definition at line 342 of file WDSVMOcas.h.

float32_t* wd_weights

protected

wd weights

Definition at line 326 of file WDSVMOcas.h.

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

• WDSVMOcas.h
• WDSVMOcas.cpp