12 #ifndef MULTICLASSONEVSRESTSTRATEGY_H__
13 #define MULTICLASSONEVSRESTSTRATEGY_H__
85 return "MulticlassOneVsRestStrategy";
void rescale_heuris_norm(SGVector< float64_t > outputs)
virtual int32_t get_num_machines()
virtual SGVector< int32_t > train_prepare_next()
virtual const char * get_name() const
virtual int32_t decide_label(SGVector< float64_t > outputs)
int32_t m_num_classes
number of classes in this problem
Multiclass Labels for multi-class classification.
int32_t m_train_iter
index of current iterations
virtual void rescale_outputs(SGVector< float64_t > outputs)
void rescale_heuris_softmax(SGVector< float64_t > outputs, const SGVector< float64_t > As, const SGVector< float64_t > Bs)
virtual SGVector< index_t > decide_label_multiple_output(SGVector< float64_t > outputs, int32_t n_outputs)
virtual bool train_has_more()
all of classes and functions are contained in the shogun namespace
CMulticlassOneVsRestStrategy()
Binary Labels for binary classification.
class MulticlassStrategy used to construct generic multiclass classifiers with ensembles of binary cl...
multiclass one vs rest strategy used to train generic multiclass machines for K-class problems with b...
virtual void train_start(CMulticlassLabels *orig_labels, CBinaryLabels *train_labels)
virtual ~CMulticlassOneVsRestStrategy()
virtual void train_start(CMulticlassLabels *orig_labels, CBinaryLabels *train_labels)