CSVMOcas Class Reference


Detailed Description

class SVMOcas

Definition at line 29 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 (CFeatures *data=NULL)
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 ( E_SVM_TYPE  type  ) 

constructor

Parameters:
type a E_SVM_TYPE

Definition at line 24 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 32 of file SVMOcas.cpp.

~CSVMOcas (  )  [virtual]

Definition at line 45 of file SVMOcas.cpp.


Member Function Documentation

void 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 176 of file SVMOcas.cpp.

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

compute output

Parameters:
output output
ptr ptr

Definition at line 258 of file SVMOcas.cpp.

void 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 283 of file SVMOcas.cpp.

bool get_bias_enabled (  ) 

check if bias is enabled

Returns:
if bias is enabled

Definition at line 106 of file SVMOcas.h.

int32_t get_bufsize (  ) 

get buffer size

Returns:
buffer size

Definition at line 118 of file SVMOcas.h.

float64_t get_C1 (  ) 

get C1

Returns:
C1

Definition at line 76 of file SVMOcas.h.

float64_t get_C2 (  ) 

get C2

Returns:
C2

Definition at line 82 of file SVMOcas.h.

virtual EClassifierType get_classifier_type (  )  [virtual]

get classifier type

Returns:
classifier type SVMOCAS

Reimplemented from CClassifier.

Definition at line 53 of file SVMOcas.h.

float64_t get_epsilon (  ) 

get epsilon

Returns:
epsilon

Definition at line 94 of file SVMOcas.h.

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

Implements CSGObject.

Definition at line 169 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 100 of file SVMOcas.h.

void set_bufsize ( int32_t  sz  ) 

set buffer size

Parameters:
sz buffer size

Definition at line 112 of file SVMOcas.h.

void set_C ( float64_t  c1,
float64_t  c2 
)

set C

Parameters:
c1 new C1
c2 new C2

Definition at line 70 of file SVMOcas.h.

void set_epsilon ( float64_t  eps  ) 

set epsilon

Parameters:
eps new epsilon

Definition at line 88 of file SVMOcas.h.

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

sort

Parameters:
vals vals
idx idx
size size

Definition at line 248 of file SVMOcas.cpp.

bool train ( CFeatures data = NULL  )  [virtual]

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 CClassifier.

Definition at line 49 of file SVMOcas.cpp.

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

update W

Parameters:
t t
ptr ptr
Returns:
something floaty

Definition at line 149 of file SVMOcas.cpp.


Member Data Documentation

int32_t bufsize [protected]

buffer size

Definition at line 175 of file SVMOcas.h.

float64_t C1 [protected]

C1

Definition at line 177 of file SVMOcas.h.

float64_t C2 [protected]

C2

Definition at line 179 of file SVMOcas.h.

float64_t* cp_bias [protected]

bias dimensions

Definition at line 202 of file SVMOcas.h.

uint32_t** cp_index [protected]

cutting plane index

Definition at line 198 of file SVMOcas.h.

uint32_t* cp_nz_dims [protected]

cutting plane dimensions

Definition at line 200 of file SVMOcas.h.

float64_t** cp_value [protected]

sparse representation of cutting planes

Definition at line 196 of file SVMOcas.h.

float64_t epsilon [protected]

epsilon

Definition at line 181 of file SVMOcas.h.

float64_t* lab [protected]

labels

Definition at line 192 of file SVMOcas.h.

E_SVM_TYPE method [protected]

method

Definition at line 183 of file SVMOcas.h.

float64_t old_bias [protected]

old bias

Definition at line 188 of file SVMOcas.h.

float64_t* old_w [protected]

old W

Definition at line 186 of file SVMOcas.h.

float64_t* tmp_a_buf [protected]

nDim big

Definition at line 190 of file SVMOcas.h.

bool use_bias [protected]

if bias is used

Definition at line 173 of file SVMOcas.h.


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

SHOGUN Machine Learning Toolbox - Documentation