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.
在文件MKLRegression.h第25行定义。
公有成员 | |
CMKLRegression (CSVM *s=NULL) | |
virtual | ~CMKLRegression () |
virtual float64_t | compute_sum_alpha () |
保护成员 | |
virtual void | init_training () |
virtual EClassifierType | get_classifier_type () |
virtual float64_t | compute_mkl_dual_objective () |
CMKLRegression | ( | CSVM * | s = NULL |
) |
~CMKLRegression | ( | ) | [virtual] |
Destructor
在文件MKLRegression.cpp第18行定义。
float64_t compute_mkl_dual_objective | ( | ) | [protected, virtual] |
float64_t compute_sum_alpha | ( | ) | [virtual] |
compute beta independent term from objective, e.g., in 2-class MKL sum_i alpha_i etc
实现了CMKL。
在文件MKLRegression.cpp第22行定义。
virtual EClassifierType get_classifier_type | ( | ) | [protected, virtual] |
void init_training | ( | ) | [protected, virtual] |
check run before starting training (to e.g. check if labeling is two-class labeling in classification case
实现了CMKL。
在文件MKLRegression.cpp第41行定义。