13 CKNNSolver(k, q, num_classes, min_label, train_labels)
34 for (int32_t j=0; j<
m_k; j++)
68 dists[j] = knn_distance->
distance(NN(j,i), i);
int32_t m_k
the k parameter in KNN
Class Distance, a base class for all the distances used in the Shogun toolbox.
SGVector< int32_t > m_train_labels
SGMatrix< index_t > get_knn_indices()
static void qsort_index(T1 *output, T2 *index, uint32_t size)
int32_t choose_class(float64_t *classes, const int32_t *train_lab) const
virtual SGVector< int32_t > classify_objects_k(CDistance *d, const int32_t num_lab, SGVector< int32_t > &train_lab, SGVector< int32_t > &classes) const
void build_tree(CDenseFeatures< float64_t > *data)
bool set_label(int32_t idx, float64_t label)
Multiclass Labels for multi-class classification.
void query_knn(CDenseFeatures< float64_t > *data, int32_t k)
void choose_class_for_multiple_k(int32_t *output, int32_t *classes, const int32_t *train_lab, const int32_t step) const
This class implements KD-Tree. cf. http://www.autonlab.org/autonweb/14665/version/2/part/5/data/moore...
static bool cancel_computations()
int32_t m_min_label
smallest label, i.e. -1
virtual CMulticlassLabels * classify_objects(CDistance *d, const int32_t num_lab, SGVector< int32_t > &train_lab, SGVector< float64_t > &classes) const
virtual float64_t distance(int32_t idx_a, int32_t idx_b)
all of classes and functions are contained in the shogun namespace
The class Features is the base class of all feature objects.