Public Member Functions | |
CLibSVR () | |
CLibSVR (float64_t C, float64_t epsilon, CKernel *k, CLabels *lab) | |
virtual | ~CLibSVR () |
virtual bool | train () |
virtual EClassifierType | get_classifier_type () |
Protected Attributes | |
svm_problem | problem |
svm_parameter | param |
struct svm_model * | model |
where and
are determined in training, i.e. using a pre-specified kernel, a given tube-epsilon for the epsilon insensitive loss, the follwoing quadratic problem is minimized (using sequential minimal decomposition (SMO))
Note that the SV regression problem is reduced to the standard SV classification problem by introducing artificial labels which leads to the epsilon insensitive loss constraints *
with and
Definition at line 48 of file LibSVR.h.
CLibSVR::CLibSVR | ( | ) |
default constructor
Definition at line 14 of file LibSVR.cpp.
constructor
C | constant C | |
epsilon | epsilon | |
k | kernel | |
lab | labels |
Definition at line 20 of file LibSVR.cpp.
CLibSVR::~CLibSVR | ( | ) | [virtual] |
Definition at line 31 of file LibSVR.cpp.
virtual EClassifierType CLibSVR::get_classifier_type | ( | ) | [virtual] |
bool CLibSVR::train | ( | ) | [virtual] |
train regression
Reimplemented from CClassifier.
Definition at line 36 of file LibSVR.cpp.
struct svm_model* CLibSVR::model [read, protected] |
svm_parameter CLibSVR::param [protected] |
svm_problem CLibSVR::problem [protected] |