#include <center_chooser.h>

Public Types | |
| typedef Distance::ResultType | DistanceType |
| typedef Distance::ElementType | ElementType |
Public Member Functions | |
| KMeansppCenterChooser (const Distance &distance, const std::vector< ElementType * > &points) | |
| void | operator() (int k, int *indices, int indices_length, int *centers, int ¢ers_length) |
Chooses the initial centers using the algorithm proposed in the KMeans++ paper: Arthur, David; Vassilvitskii, Sergei - k-means++: The Advantages of Careful Seeding
Definition at line 211 of file center_chooser.h.
| typedef Distance::ResultType rtflann::KMeansppCenterChooser< Distance >::DistanceType |
Reimplemented from rtflann::CenterChooser< Distance >.
Definition at line 215 of file center_chooser.h.
| typedef Distance::ElementType rtflann::KMeansppCenterChooser< Distance >::ElementType |
Reimplemented from rtflann::CenterChooser< Distance >.
Definition at line 214 of file center_chooser.h.
| rtflann::KMeansppCenterChooser< Distance >::KMeansppCenterChooser | ( | const Distance & | distance, |
| const std::vector< ElementType * > & | points | ||
| ) | [inline] |
Definition at line 221 of file center_chooser.h.
| void rtflann::KMeansppCenterChooser< Distance >::operator() | ( | int | k, |
| int * | indices, | ||
| int | indices_length, | ||
| int * | centers, | ||
| int & | centers_length | ||
| ) | [inline, virtual] |
Chooses cluster centers
| k | number of centers to choose |
| indices | indices of points to choose the centers from |
| indices_length | length of indices |
| centers | indices of chosen centers |
| centers_length | length of centers array |
Implements rtflann::CenterChooser< Distance >.
Definition at line 224 of file center_chooser.h.