CSVMOcas Class Reference

Inheritance diagram for CSVMOcas:

Detailed Description

class SVMOcas

Definition at line 27 of file SVMOcas.h.


Public Member Functions
	CSVMOcas (E_SVM_TYPE type)
	CSVMOcas (DREAL C, CSparseFeatures< DREAL > traindat, CLabels trainlab)
virtual	~CSVMOcas ()
virtual EClassifierType	get_classifier_type ()
virtual bool	train ()
void	set_C (DREAL c1, DREAL c2)
DREAL	get_C1 ()
DREAL	get_C2 ()
void	set_epsilon (DREAL eps)
DREAL	get_epsilon ()
void	set_bias_enabled (bool enable_bias)
bool	get_bias_enabled ()
void	set_bufsize (INT sz)
INT	get_bufsize ()
virtual CLabels *	classify (CLabels *output=NULL)
virtual DREAL	classify_example (INT vec_idx)
	get output for example "vec_idx"
void	get_w (DREAL *dst_w, INT dst_dims)
void	set_w (DREAL *src_w, INT src_w_dim)
void	set_bias (DREAL b)
DREAL	get_bias ()
void	set_features (CSparseFeatures< DREAL > *feat)
CSparseFeatures< DREAL > *	get_features ()
virtual bool	load (FILE *srcfile)
virtual bool	save (FILE *dstfile)
virtual void	set_labels (CLabels *lab)
virtual CLabels *	get_labels ()
virtual DREAL	get_label (INT i)
void	set_max_train_time (DREAL t)
DREAL	get_max_train_time ()
Static Public Attributes
static CParallel	parallel
static CIO	io
static CVersion	version
Static Protected Member Functions
static void	compute_W (double sq_norm_W, double dp_WoldW, double alpha, uint32_t nSel, void ptr)
static double	update_W (double t, void *ptr)
static void	add_new_cut (double new_col_H, uint32_t new_cut, uint32_t cut_length, uint32_t nSel, void *ptr)
static void	compute_output (double output, void ptr)
static void	sort (double vals, uint32_t idx, uint32_t size)
Protected Attributes
bool	use_bias
INT	bufsize
DREAL	C1
DREAL	C2
DREAL	epsilon
E_SVM_TYPE	method
DREAL *	old_w
DREAL *	tmp_a_buf
DREAL *	lab
DREAL **	cp_value
uint32_t **	cp_index
uint32_t *	cp_nz_dims
INT	w_dim
DREAL *	w
DREAL	bias
CSparseFeatures< DREAL > *	features
DREAL	max_train_time
CLabels *	labels

Constructor & Destructor Documentation

CSVMOcas::CSVMOcas ( E_SVM_TYPE type )

constructor

Parameters:

type

a E_SVM_TYPE

Definition at line 22 of file SVMOcas.cpp.

CSVMOcas::CSVMOcas	(	DREAL	C,
		CSparseFeatures< DREAL > *	traindat,
		CLabels *	trainlab
	)

constructor

Parameters:

	C	constant C
	traindat	training features
	trainlab	labels for training features

Definition at line 30 of file SVMOcas.cpp.

CSVMOcas::~CSVMOcas ( ) [virtual]

Definition at line 42 of file SVMOcas.cpp.

Member Function Documentation

virtual EClassifierType CSVMOcas::get_classifier_type ( ) [virtual]

get classifier type

Returns:: classifier type SVMOCAS

Reimplemented from CClassifier.

Definition at line 49 of file SVMOcas.h.

bool CSVMOcas::train ( ) [virtual]

train SVM

Returns:: true if training was successful

Reimplemented from CClassifier.

Definition at line 46 of file SVMOcas.cpp.

void CSVMOcas::set_C	(	DREAL	c1,
		DREAL	c2
	)

set C

Parameters:

	c1	new C1
	c2	new C2

Definition at line 62 of file SVMOcas.h.

DREAL CSVMOcas::get_C1 ( )

get C1

Returns:: C1

Definition at line 68 of file SVMOcas.h.

DREAL CSVMOcas::get_C2 ( )

get C2

Returns:: C2

Definition at line 74 of file SVMOcas.h.

void CSVMOcas::set_epsilon ( DREAL eps )

set epsilon

Parameters:

eps

new epsilon

Definition at line 80 of file SVMOcas.h.

DREAL CSVMOcas::get_epsilon ( )

get epsilon

Returns:: epsilon

Definition at line 86 of file SVMOcas.h.

void CSVMOcas::set_bias_enabled ( bool enable_bias )

set if bias shall be enabled

Parameters:

enable_bias

if bias shall be enabled

Definition at line 92 of file SVMOcas.h.

bool CSVMOcas::get_bias_enabled ( )

check if bias is enabled

Returns:: if bias is enabled

Definition at line 98 of file SVMOcas.h.

void CSVMOcas::set_bufsize ( INT sz )

set buffer size

Parameters:

sz

buffer size

Definition at line 104 of file SVMOcas.h.

INT CSVMOcas::get_bufsize ( )

get buffer size

Returns:: buffer size

Definition at line 110 of file SVMOcas.h.

void CSVMOcas::compute_W	(	double *	sq_norm_W,
		double *	dp_WoldW,
		double *	alpha,
		uint32_t	nSel,
		void *	ptr
	)			`[static, protected]`

compute W

Parameters:

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

Definition at line 258 of file SVMOcas.cpp.

double CSVMOcas::update_W	(	double	t,
		void *	ptr
	)			`[static, protected]`

update W

Parameters:

	t	t
	ptr	ptr

Returns:: something floaty

Definition at line 134 of file SVMOcas.cpp.

void CSVMOcas::add_new_cut	(	double *	new_col_H,
		uint32_t *	new_cut,
		uint32_t	cut_length,
		uint32_t	nSel,
		void *	ptr
	)			`[static, protected]`

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 159 of file SVMOcas.cpp.

void CSVMOcas::compute_output	(	double *	output,
		void *	ptr
	)			`[static, protected]`

compute output

Parameters:

	output	output
	ptr	ptr

Definition at line 237 of file SVMOcas.cpp.

void CSVMOcas::sort	(	double *	vals,
		uint32_t *	idx,
		uint32_t	size
	)			`[static, protected]`

sort

Parameters:

	vals	vals
	idx	idx
	size	size

Definition at line 227 of file SVMOcas.cpp.

CLabels * CSparseLinearClassifier::classify ( CLabels * output = NULL ) [virtual, inherited]

classify all examples

Parameters:

output

resulting labels

Returns:: resulting labels

Reimplemented from CClassifier.

Definition at line 24 of file SparseLinearClassifier.cpp.

virtual DREAL CSparseLinearClassifier::classify_example ( INT vec_idx ) [virtual, inherited]

get output for example "vec_idx"

Reimplemented from CClassifier.

Definition at line 34 of file SparseLinearClassifier.h.

void CSparseLinearClassifier::get_w	(	DREAL **	dst_w,
		INT *	dst_dims
	)			`[inherited]`

get w

Parameters:

	dst_w	store w in this argument
	dst_dims	dimension of w

Definition at line 44 of file SparseLinearClassifier.h.

void CSparseLinearClassifier::set_w	(	DREAL *	src_w,
		INT	src_w_dim
	)			`[inherited]`

set w

Parameters:

	src_w	new w
	src_w_dim	dimension of new w

Definition at line 59 of file SparseLinearClassifier.h.

void CSparseLinearClassifier::set_bias ( DREAL b ) [inherited]

set bias

Parameters:

b

new bias

Definition at line 69 of file SparseLinearClassifier.h.

DREAL CSparseLinearClassifier::get_bias ( ) [inherited]

get bias

Returns:: bias

Definition at line 78 of file SparseLinearClassifier.h.

void CSparseLinearClassifier::set_features ( CSparseFeatures< DREAL > * feat ) [inherited]

set features

Parameters:

feat

features to set

Definition at line 87 of file SparseLinearClassifier.h.

CSparseFeatures<DREAL>* CSparseLinearClassifier::get_features ( ) [inherited]

get features

Returns:: features

Definition at line 98 of file SparseLinearClassifier.h.

virtual bool CClassifier::load ( FILE * srcfile ) [virtual, inherited]

load Classifier from file

abstract base method

Parameters:

srcfile

file to load from

Returns:: failure

Reimplemented in CKernelPerceptron, CKNN, CLinearClassifier, CSVM, CHierarchical, and CKMeans.

Definition at line 56 of file Classifier.h.

virtual bool CClassifier::save ( FILE * dstfile ) [virtual, inherited]

save Classifier to file

abstract base method

Parameters:

dstfile

file to save to

Returns:: failure

Reimplemented in CKernelPerceptron, CKNN, CLinearClassifier, CSVM, CHierarchical, and CKMeans.

Definition at line 65 of file Classifier.h.

virtual void CClassifier::set_labels ( CLabels * lab ) [virtual, inherited]

set labels

Parameters:

lab

labels

Definition at line 71 of file Classifier.h.

virtual CLabels* CClassifier::get_labels ( ) [virtual, inherited]

get labels

Returns:: labels

Definition at line 82 of file Classifier.h.

virtual DREAL CClassifier::get_label ( INT i ) [virtual, inherited]

get one specific label

Parameters:

i

index of label to get

Returns:: value of label at index i

Definition at line 89 of file Classifier.h.

void CClassifier::set_max_train_time ( DREAL t ) [inherited]

set maximum training time

Parameters:

t

maximimum training time

Definition at line 95 of file Classifier.h.

DREAL CClassifier::get_max_train_time ( ) [inherited]

get maximum training time

Returns:: maximum training time

Definition at line 101 of file Classifier.h.

Member Data Documentation

bool CSVMOcas::use_bias [protected]

if bias is used

Definition at line 159 of file SVMOcas.h.

INT CSVMOcas::bufsize [protected]

buffer size

Definition at line 161 of file SVMOcas.h.

DREAL CSVMOcas::C1 [protected]

C1

Definition at line 163 of file SVMOcas.h.

DREAL CSVMOcas::C2 [protected]

C2

Definition at line 165 of file SVMOcas.h.

DREAL CSVMOcas::epsilon [protected]

epsilon

Definition at line 167 of file SVMOcas.h.

E_SVM_TYPE CSVMOcas::method [protected]

method

Definition at line 169 of file SVMOcas.h.

DREAL* CSVMOcas::old_w [protected]

old W

Definition at line 172 of file SVMOcas.h.

DREAL* CSVMOcas::tmp_a_buf [protected]

nDim big

Definition at line 174 of file SVMOcas.h.

DREAL* CSVMOcas::lab [protected]

labels

Definition at line 176 of file SVMOcas.h.

DREAL** CSVMOcas::cp_value [protected]

sparse representation of cutting planes

Definition at line 180 of file SVMOcas.h.

uint32_t** CSVMOcas::cp_index [protected]

cutting plane index

Definition at line 182 of file SVMOcas.h.

uint32_t* CSVMOcas::cp_nz_dims [protected]

cutting plane dimensions

Definition at line 184 of file SVMOcas.h.

INT CSparseLinearClassifier::w_dim [protected, inherited]

dimension of w

Definition at line 102 of file SparseLinearClassifier.h.

DREAL* CSparseLinearClassifier::w [protected, inherited]

w

Definition at line 104 of file SparseLinearClassifier.h.

DREAL CSparseLinearClassifier::bias [protected, inherited]

bias

Definition at line 106 of file SparseLinearClassifier.h.

CSparseFeatures<DREAL>* CSparseLinearClassifier::features [protected, inherited]

features

Definition at line 108 of file SparseLinearClassifier.h.

DREAL CClassifier::max_train_time [protected, inherited]

maximum training time

Definition at line 111 of file Classifier.h.

CLabels* CClassifier::labels [protected, inherited]

labels

Definition at line 114 of file Classifier.h.

CParallel CSGObject::parallel [static, inherited]

Definition at line 105 of file SGObject.h.

CIO CSGObject::io [static, inherited]

Definition at line 106 of file SGObject.h.

CVersion CSGObject::version [static, inherited]

Definition at line 107 of file SGObject.h.

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

CSVMOcas Class Reference

Detailed Description

Public Member Functions

Static Public Attributes

Static Protected Member Functions

Protected Attributes

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation