19 const int32_t N_splits = 2;
29 for (int32_t i=0; i < N_splits; ++i)
53 conf_mat(j, k) += tmp_mat(j, k);
69 conf_mat(j, k) /= N_splits;
85 conf_mat(i, j) = conf_mat_int(i, j);
SGMatrix< float64_t > estimate_confusion_matrix(CBaseMulticlassMachine *machine, CFeatures *X, CMulticlassLabels *Y, int32_t num_classes)
void split(v_array< ds_node< P > > &point_set, v_array< ds_node< P > > &far_set, int max_scale)
Multiclass Labels for multi-class classification.
virtual void build_subsets()
virtual void set_store_model_features(bool store_model)
void get_confusion_matrix(SGMatrix< float64_t > &conf_mat, CMulticlassLabels *gt, CMulticlassLabels *pred)
static SGMatrix< int32_t > get_confusion_matrix(CLabels *predicted, CLabels *ground_truth)
virtual void remove_subset()
virtual void add_subset(SGVector< index_t > subset)
SGVector< index_t > generate_subset_inverse(index_t subset_idx)
all of classes and functions are contained in the shogun namespace
SGVector< index_t > generate_subset_indices(index_t subset_idx)
virtual void remove_subset()
The class Features is the base class of all feature objects.
virtual bool train(CFeatures *data=NULL)
Implementation of normal cross-validation on the base of CSplittingStrategy. Produces subset index se...
virtual CMulticlassLabels * apply_multiclass(CFeatures *data=NULL)
virtual void set_labels(CLabels *lab)
virtual void add_subset(SGVector< index_t > subset)