Vantage Tree#
A Vantage Point Tree is a binary spatial tree that divides samples by their distance from the center of a cluster called the vantage point. Samples that are closer to the vantage point will be put into one branch of the tree while samples that are farther away will be put into the other branch.
Interfaces: Binary Tree, Spatial
Data Type Compatibility: Depends on distance kernel
Parameters#
| # | Param | Default | Type | Description |
|---|---|---|---|---|
| 1 | max leaf size | 30 | int | The maximum number of samples that each leaf node can contain. |
| 2 | kernel | Euclidean | Distance | The distance kernel used to compute the distance between sample points. |
Example#
use Rubix\ML\Graph\Trees\VantageTree;
use Rubix\ML\Kernels\Distance\Euclidean;
$tree = new VantageTree(30, new Euclidean());
Additional Methods#
This tree does not have any additional methods.
References#
- P. N. Yianilos. (1993). Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces.