| Package | Description |
|---|---|
| smile.clustering |
Clustering analysis.
|
| smile.neighbor |
Nearest neighbor search.
|
| Constructor and Description |
|---|
DBScan(T[] data,
RNNSearch<T,T> nns,
int minPts,
double radius)
Clustering the data.
|
MEC(T[] data,
RNNSearch<T,T> nns,
int k,
double radius,
int[] y)
Constructor.
|
| Modifier and Type | Class and Description |
|---|---|
class |
BKTree<E>
A BK-tree is a metric tree specifically adapted to discrete metric spaces.
|
class |
CoverTree<E>
Cover tree is a data structure for generic nearest neighbor search, which
is especially efficient in spaces with small intrinsic dimension.
|
class |
KDTree<E>
A KD-tree (short for k-dimensional tree) is a space-partitioning dataset
structure for organizing points in a k-dimensional space.
|
class |
LinearSearch<T>
Brute force linear nearest neighbor search.
|
class |
LSH<E>
Locality-Sensitive Hashing.
|
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