A binary spatial tree that partitions a dataset into successively smaller and tighter ball nodes whose boundaries are defined by a hypersphere. Ball Tree works well in higher dimensions since the partitioning schema does not rely on a finite number of 1-dimensional axis aligned splits such as with k-d tree.
Interfaces: Binary Tree, Spatial
Data Type Compatibility: Depends on distance kernel
| # | Name | Default | Type | Description |
|---|---|---|---|---|
| 1 | maxLeafSize | 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. |
use Rubix\ML\Graph\Trees\BallTree;
use Rubix\ML\Kernels\Distance\Euclidean;
$tree = new BallTree(40, new Euclidean());This tree does not have any additional methods.