17 using namespace shogun;
59 machine->m_model_selection_parameters);
102 return best_combination;
base class for cross-validation evaluation. Given a learning machine, a splitting strategy...
T * get_element(int32_t index) const
void apply_to_modsel_parameter(Parameter *parameter) const
CrossValidationResult evaluate()
virtual CParameterCombination * select_model()
CCrossValidation * m_cross_validation
int32_t get_num_elements() const
CDynamicObjectArray< CParameterCombination > * get_combinations()
A generic learning machine interface.
Class to select parameters and their ranges for model selection. The structure is organized as a tree...
type to encapsulate the results of an evaluation run. May contain confidence interval (if conf_int_al...
static const float64_t ALMOST_NEG_INFTY
almost neg (log) infinity
Abstract base class for model selection. Takes a parameter tree which specifies parameters for model ...
CMachine * get_machine() const
CModelSelectionParameters * m_model_parameters
Template Dynamic array class that creates an array that can be used like a list or an array...
CGridSearchModelSelection()
class that holds ONE combination of parameters for a learning machine. The structure is organized as ...
EEvaluationDirection get_evaluation_direction()
static const float64_t ALMOST_INFTY
virtual ~CGridSearchModelSelection()