SHOGUN  4.1.0
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MKLRegression.cpp
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3 #ifdef USE_SVMLIGHT
5 #endif //USE_SVMLIGHT
6 
7 using namespace shogun;
8 
10 {
11  if (!s)
12  {
13 #ifdef USE_SVMLIGHT
14  s=new CSVRLight();
15 #endif //USE_SVMLIGHT
16  if (!s)
17  s=new CLibSVR();
18  set_svm(s);
19  }
20 }
21 
23 {
24 }
25 
27 {
29  return 0;
30 
31  // not correct needs explicit access to alpha and alpha*
32  //float64_t suma=0;
33  //int32_t nsv=svm->get_num_support_vectors();
34  //for (int32_t i=0; i<nsv; i++)
35  // suma+=CMath::abs(svm->get_alpha(i))*tube_epsilon-svm->get_alpha(i);
36  //return suma;
37 }
38 
40 {
42  return 0;
43 }
44 
46 {
48  ASSERT(svm)
51 }
virtual void init_training()
virtual int32_t get_num_labels() const =0
CLabels * m_labels
Definition: Machine.h:361
#define SG_NOTIMPLEMENTED
Definition: SGIO.h:139
CSVM * svm
Definition: MKL.h:451
virtual float64_t compute_mkl_dual_objective()
Class SVRLight, performs support vector regression using SVMLight.
Definition: SVRLight.h:62
#define ASSERT(x)
Definition: SGIO.h:201
double float64_t
Definition: common.h:50
CMKLRegression(CSVM *s=NULL)
virtual float64_t compute_sum_alpha()
Multiple Kernel Learning.
Definition: MKL.h:95
virtual EMachineType get_classifier_type()
Definition: Machine.cpp:100
bool interleaved_optimization
Definition: MKL.h:474
void set_svm(CSVM *s)
Definition: MKL.h:121
Class LibSVR, performs support vector regression using LibSVM.
Definition: LibSVR.h:70
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
A generic Support Vector Machine Interface.
Definition: SVM.h:49

SHOGUN Machine Learning Toolbox - Documentation