CSVMOcas Class Reference


Detailed Description

class SVMOcas

Definition at line 27 of file SVMOcas.h.

Inheritance diagram for CSVMOcas:
Inheritance graph
[legend]

List of all members.

Public Member Functions

 CSVMOcas (E_SVM_TYPE type)
 CSVMOcas (float64_t C, CDotFeatures *traindat, CLabels *trainlab)
virtual ~CSVMOcas ()
virtual EClassifierType get_classifier_type ()
virtual bool train ()
void set_C (float64_t c1, float64_t c2)
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 ()

Protected Member Functions

virtual const char * get_name () const

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 (float64_t *new_col_H, uint32_t *new_cut, uint32_t cut_length, uint32_t nSel, void *ptr)
static void compute_output (float64_t *output, void *ptr)
static void sort (float64_t *vals, uint32_t *idx, uint32_t size)

Protected Attributes

bool use_bias
int32_t bufsize
float64_t C1
float64_t C2
float64_t epsilon
E_SVM_TYPE method
float64_told_w
float64_t old_bias
float64_ttmp_a_buf
float64_tlab
float64_t ** cp_value
uint32_t ** cp_index
uint32_t * cp_nz_dims
float64_tcp_bias

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 ( float64_t  C,
CDotFeatures 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 43 of file SVMOcas.cpp.


Member Function Documentation

void CSVMOcas::add_new_cut ( float64_t 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 168 of file SVMOcas.cpp.

void CSVMOcas::compute_output ( float64_t output,
void *  ptr 
) [static, protected]

compute output

Parameters:
output output
ptr ptr

Definition at line 250 of file SVMOcas.cpp.

void CSVMOcas::compute_W ( float64_t sq_norm_W,
float64_t dp_WoldW,
float64_t 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 275 of file SVMOcas.cpp.

bool CSVMOcas::get_bias_enabled (  ) 

check if bias is enabled

Returns:
if bias is enabled

Definition at line 100 of file SVMOcas.h.

int32_t CSVMOcas::get_bufsize (  ) 

get buffer size

Returns:
buffer size

Definition at line 112 of file SVMOcas.h.

float64_t CSVMOcas::get_C1 (  ) 

get C1

Returns:
C1

Definition at line 70 of file SVMOcas.h.

float64_t CSVMOcas::get_C2 (  ) 

get C2

Returns:
C2

Definition at line 76 of file SVMOcas.h.

virtual EClassifierType CSVMOcas::get_classifier_type (  )  [virtual]

get classifier type

Returns:
classifier type SVMOCAS

Reimplemented from CClassifier.

Definition at line 51 of file SVMOcas.h.

float64_t CSVMOcas::get_epsilon (  ) 

get epsilon

Returns:
epsilon

Definition at line 88 of file SVMOcas.h.

virtual const char* CSVMOcas::get_name (  )  const [protected, virtual]
Returns:
object name

Implements CSGObject.

Definition at line 163 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 94 of file SVMOcas.h.

void CSVMOcas::set_bufsize ( int32_t  sz  ) 

set buffer size

Parameters:
sz buffer size

Definition at line 106 of file SVMOcas.h.

void CSVMOcas::set_C ( float64_t  c1,
float64_t  c2 
)

set C

Parameters:
c1 new C1
c2 new C2

Definition at line 64 of file SVMOcas.h.

void CSVMOcas::set_epsilon ( float64_t  eps  ) 

set epsilon

Parameters:
eps new epsilon

Definition at line 82 of file SVMOcas.h.

void CSVMOcas::sort ( float64_t vals,
uint32_t *  idx,
uint32_t  size 
) [static, protected]

sort

Parameters:
vals vals
idx idx
size size

Definition at line 240 of file SVMOcas.cpp.

bool CSVMOcas::train (  )  [virtual]

train SVM

Returns:
true if training was successful

Reimplemented from CClassifier.

Definition at line 47 of file SVMOcas.cpp.

float64_t CSVMOcas::update_W ( float64_t  t,
void *  ptr 
) [static, protected]

update W

Parameters:
t t
ptr ptr
Returns:
something floaty

Definition at line 141 of file SVMOcas.cpp.


Member Data Documentation

int32_t CSVMOcas::bufsize [protected]

buffer size

Definition at line 169 of file SVMOcas.h.

float64_t CSVMOcas::C1 [protected]

C1

Definition at line 171 of file SVMOcas.h.

float64_t CSVMOcas::C2 [protected]

C2

Definition at line 173 of file SVMOcas.h.

bias dimensions

Definition at line 196 of file SVMOcas.h.

uint32_t** CSVMOcas::cp_index [protected]

cutting plane index

Definition at line 192 of file SVMOcas.h.

uint32_t* CSVMOcas::cp_nz_dims [protected]

cutting plane dimensions

Definition at line 194 of file SVMOcas.h.

sparse representation of cutting planes

Definition at line 190 of file SVMOcas.h.

epsilon

Definition at line 175 of file SVMOcas.h.

float64_t* CSVMOcas::lab [protected]

labels

Definition at line 186 of file SVMOcas.h.

method

Definition at line 177 of file SVMOcas.h.

old bias

Definition at line 182 of file SVMOcas.h.

float64_t* CSVMOcas::old_w [protected]

old W

Definition at line 180 of file SVMOcas.h.

nDim big

Definition at line 184 of file SVMOcas.h.

bool CSVMOcas::use_bias [protected]

if bias is used

Definition at line 167 of file SVMOcas.h.


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

SHOGUN Machine Learning Toolbox - Documentation