Multiple Kernel Learning for regression.
Performs support vector regression while learning kernel weights at the same time. Makes only sense if multiple kernels are used.
Definition at line 25 of file MKLRegression.h.
Public Member Functions | |
| CMKLRegression (CSVM *s=NULL) | |
| virtual | ~CMKLRegression () |
| virtual float64_t | compute_sum_alpha () |
Protected Member Functions | |
| virtual void | init_training () |
| virtual EClassifierType | get_classifier_type () |
| virtual float64_t | compute_mkl_dual_objective () |
| CMKLRegression | ( | CSVM * | s = NULL |
) |
Constructor
| s | SVM to use as constraint generator in MKL SILP |
Definition at line 9 of file MKLRegression.cpp.
| ~CMKLRegression | ( | ) | [virtual] |
Destructor
Definition at line 22 of file MKLRegression.cpp.
| float64_t compute_mkl_dual_objective | ( | ) | [protected, virtual] |
compute mkl dual objective
Reimplemented from CMKL.
Definition at line 39 of file MKLRegression.cpp.
| float64_t compute_sum_alpha | ( | ) | [virtual] |
compute beta independent term from objective, e.g., in 2-class MKL sum_i alpha_i etc
Implements CMKL.
Definition at line 26 of file MKLRegression.cpp.
| virtual EClassifierType get_classifier_type | ( | ) | [protected, virtual] |
get classifier type
Reimplemented from CMachine.
Definition at line 53 of file MKLRegression.h.
| void init_training | ( | ) | [protected, virtual] |
check run before starting training (to e.g. check if labeling is two-class labeling in classification case
Implements CMKL.
Definition at line 45 of file MKLRegression.cpp.
