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MKLRegression.cpp
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3 
4 
5 using namespace shogun;
6 
8 {
9  if (!s)
10  {
11 
12  if (!s)
13  s=new CLibSVR();
14  set_svm(s);
15  }
16 }
17 
19 {
20 }
21 
23 {
25  return 0;
26 
27  // not correct needs explicit access to alpha and alpha*
28  //float64_t suma=0;
29  //int32_t nsv=svm->get_num_support_vectors();
30  //for (int32_t i=0; i<nsv; i++)
31  // suma+=CMath::abs(svm->get_alpha(i))*tube_epsilon-svm->get_alpha(i);
32  //return suma;
33 }
34 
36 {
38  return 0;
39 }
40 
42 {
44  ASSERT(svm)
47 }
virtual void init_training()
virtual int32_t get_num_labels() const =0
CLabels * m_labels
Definition: Machine.h:356
#define SG_NOTIMPLEMENTED
Definition: SGIO.h:141
CSVM * svm
Definition: MKL.h:451
virtual float64_t compute_mkl_dual_objective()
#define ASSERT(x)
Definition: SGIO.h:203
double float64_t
Definition: common.h:48
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:102
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
A generic Support Vector Machine Interface.
Definition: SVM.h:47

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