SHOGUN v0.10.0
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CSVM Class Reference

Detailed Description

A generic Support Vector Machine Interface.

A support vector machine is defined as

\[ f({\bf x})=\sum_{i=0}^{N-1} \alpha_i k({\bf x}, {\bf x_i})+b \]

where $N$ is the number of training examples $\alpha_i$ are the weights assigned to each training example $k(x,x')$ is the kernel and $b$ the bias.

Using an a-priori choosen kernel, the $\alpha_i$ and bias are determined by solving the following quadratic program

\begin{eqnarray*} \max_{\bf \alpha} && \sum_{i=0}^{N-1} \alpha_i - \sum_{i=0}^{N-1}\sum_{j=0}^{N-1} \alpha_i y_i \alpha_j y_j k({\bf x_i}, {\bf x_j})\\ \mbox{s.t.} && 0\leq\alpha_i\leq C\\ && \sum_{i=0}^{N-1} \alpha_i y_i=0\\ \end{eqnarray*}

here C is a pre-specified regularization parameter.

Definition at line 46 of file SVM.h.

Inheritance diagram for CSVM:
Inheritance graph
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List of all members.

Public Member Functions

 CSVM (int32_t num_sv=0)
 CSVM (float64_t C, CKernel *k, CLabels *lab)
virtual ~CSVM ()
void set_defaults (int32_t num_sv=0)
virtual float64_t * get_linear_term_ptr (index_t *len)
virtual void set_linear_term (float64_t *linear_term, index_t len)
bool load (FILE *svm_file)
bool save (FILE *svm_file)
void set_nu (float64_t nue)
void set_C (float64_t c_neg, float64_t c_pos)
void set_epsilon (float64_t eps)
void set_tube_epsilon (float64_t eps)
float64_t get_tube_epsilon ()
void set_qpsize (int32_t qps)
float64_t get_epsilon ()
float64_t get_nu ()
float64_t get_C1 ()
float64_t get_C2 ()
int32_t get_qpsize ()
void set_shrinking_enabled (bool enable)
bool get_shrinking_enabled ()
float64_t compute_svm_dual_objective ()
float64_t compute_svm_primal_objective ()
void set_objective (float64_t v)
float64_t get_objective ()
void set_callback_function (CMKL *m, bool(*cb)(CMKL *mkl, const float64_t *sumw, const float64_t suma))
virtual const char * get_name () const

Protected Member Functions

virtual float64_t * get_linear_term_array ()

Protected Attributes

float64_t * m_linear_term
index_t m_linear_term_len
bool svm_loaded
float64_t epsilon
float64_t tube_epsilon
float64_t nu
float64_t C1
float64_t C2
float64_t objective
int32_t qpsize
bool use_shrinking
bool(* callback )(CMKL *mkl, const float64_t *sumw, const float64_t suma)
CMKL * mkl

Constructor & Destructor Documentation

CSVM ( int32_t  num_sv = 0)

Create an empty Support Vector Machine Object

Parameters:
num_svwith num_sv support vectors

Definition at line 27 of file SVM.cpp.

CSVM ( float64_t  C,
CKernel *  k,
CLabels *  lab 
)

Create a Support Vector Machine Object from a trained SVM

Parameters:
Cthe C parameter
kthe Kernel object
labthe Label object

Definition at line 33 of file SVM.cpp.

~CSVM ( ) [virtual]

Definition at line 42 of file SVM.cpp.


Member Function Documentation

float64_t compute_svm_dual_objective ( )

compute svm dual objective

Returns:
computed dual objective

Definition at line 247 of file SVM.cpp.

float64_t compute_svm_primal_objective ( )

compute svm primal objective

Returns:
computed svm primal objective

Definition at line 272 of file SVM.cpp.

float64_t get_C1 ( )

get C1

Returns:
C1

Definition at line 156 of file SVM.h.

float64_t get_C2 ( )

get C2

Returns:
C2

Definition at line 162 of file SVM.h.

float64_t get_epsilon ( )

get epsilon

Returns:
epsilon

Definition at line 144 of file SVM.h.

float64_t * get_linear_term_array ( ) [protected, virtual]

get linear term copy as dynamic array

Returns:
linear term copied to a dynamic array

Definition at line 298 of file SVM.cpp.

float64_t * get_linear_term_ptr ( index_t *  len) [virtual]

get linear term

Parameters:
lenlenght of the linear term vector (returned)
Returns:
the linear term

Definition at line 331 of file SVM.cpp.

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

Reimplemented from CKernelMachine.

Reimplemented in CMKL, CGMNPSVM, CGNPPSVM, CGPBTSVM, CLaRank, CLibSVM, CLibSVMMultiClass, CLibSVMOneClass, CMPDSVM, CScatterSVM, and CLibSVR.

Definition at line 229 of file SVM.h.

float64_t get_nu ( )

get nu

Returns:
nu

Definition at line 150 of file SVM.h.

float64_t get_objective ( )

get objective

Returns:
objective

Definition at line 213 of file SVM.h.

int32_t get_qpsize ( )

get qpsize

Returns:
qpsize

Definition at line 168 of file SVM.h.

bool get_shrinking_enabled ( )

get state of shrinking

Returns:
if shrinking is enabled

Definition at line 183 of file SVM.h.

float64_t get_tube_epsilon ( )

get tube epsilon

Returns:
tube epsilon

Definition at line 132 of file SVM.h.

bool load ( FILE *  svm_file) [virtual]

load a SVM from file

Parameters:
svm_filethe file handle

Reimplemented from CClassifier.

Reimplemented in CMultiClassSVM.

Definition at line 95 of file SVM.cpp.

bool save ( FILE *  svm_file) [virtual]

write a SVM to a file

Parameters:
svm_filethe file handle

Reimplemented from CClassifier.

Reimplemented in CMultiClassSVM.

Definition at line 211 of file SVM.cpp.

void set_C ( float64_t  c_neg,
float64_t  c_pos 
)

set C

Parameters:
c_negnew C constant for negatively labeled examples
c_posnew C constant for positively labeled examples

Note that not all SVMs support this (however at least CLibSVM and CSVMLight do)

Definition at line 113 of file SVM.h.

void set_callback_function ( CMKL *  m,
bool(*)(CMKL *mkl, const float64_t *sumw, const float64_t suma)  cb 
)

set callback function svm optimizers may call when they have a new (small) set of alphas

Parameters:
mpointer to mkl object
cbcallback function

Definition at line 237 of file SVM.cpp.

void set_defaults ( int32_t  num_sv = 0)

set default values for members a SVM object

Definition at line 48 of file SVM.cpp.

void set_epsilon ( float64_t  eps)

set epsilon

Parameters:
epsnew epsilon

Definition at line 120 of file SVM.h.

void set_linear_term ( float64_t *  linear_term,
index_t  len 
) [virtual]

set linear term of the QP

Parameters:
linear_termthe linear term
lenlenght of the linear term vector

Definition at line 309 of file SVM.cpp.

void set_nu ( float64_t  nue)

set nu

Parameters:
nuenew nu

Definition at line 102 of file SVM.h.

void set_objective ( float64_t  v)

set objective

Parameters:
vobjective

Definition at line 204 of file SVM.h.

void set_qpsize ( int32_t  qps)

set qpsize

Parameters:
qpsnew qpsize

Definition at line 138 of file SVM.h.

void set_shrinking_enabled ( bool  enable)

set state of shrinking

Parameters:
enableif shrinking will be enabled

Definition at line 174 of file SVM.h.

void set_tube_epsilon ( float64_t  eps)

set tube epsilon

Parameters:
epsnew tube epsilon

Definition at line 126 of file SVM.h.


Member Data Documentation

float64_t C1 [protected]

C1 regularization const

Definition at line 253 of file SVM.h.

float64_t C2 [protected]

C2

Definition at line 255 of file SVM.h.

bool(* callback)(CMKL *mkl, const float64_t *sumw, const float64_t suma) [protected]

callback function svm optimizers may call when they have a new (small) set of alphas

Definition at line 265 of file SVM.h.

float64_t epsilon [protected]

epsilon

Definition at line 247 of file SVM.h.

float64_t* m_linear_term [protected]

linear term in qp

Definition at line 241 of file SVM.h.

Definition at line 242 of file SVM.h.

CMKL* mkl [protected]

mkl object that svm optimizers need to pass when calling the callback function

Definition at line 268 of file SVM.h.

float64_t nu [protected]

nu

Definition at line 251 of file SVM.h.

float64_t objective [protected]

objective

Definition at line 257 of file SVM.h.

int32_t qpsize [protected]

qpsize

Definition at line 259 of file SVM.h.

bool svm_loaded [protected]

if SVM is loaded

Definition at line 245 of file SVM.h.

float64_t tube_epsilon [protected]

tube epsilon for support vector regression

Definition at line 249 of file SVM.h.

bool use_shrinking [protected]

if shrinking shall be used

Definition at line 261 of file SVM.h.


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