| Package | Description |
|---|---|
| smile.classification |
Classification algorithms.
|
| smile.clustering |
Clustering analysis.
|
| smile.neighbor |
Nearest neighbor search.
|
| Class and Description |
|---|
| KNNSearch
K-nearest neighbor search identifies the top k nearest neighbors to the
query.
|
| Class and Description |
|---|
| RNNSearch
A range nearest neighbor search retrieves the nearest neighbors to a query
in a range.
|
| Class and Description |
|---|
| BKTree
A BK-tree is a metric tree specifically adapted to discrete metric spaces.
|
| KDTree
A KD-tree (short for k-dimensional tree) is a space-partitioning dataset
structure for organizing points in a k-dimensional space.
|
| KNNSearch
K-nearest neighbor search identifies the top k nearest neighbors to the
query.
|
| LinearSearch
Brute force linear nearest neighbor search.
|
| LSH
Locality-Sensitive Hashing.
|
| MPLSH
Multi-Probe Locality-Sensitive Hashing.
|
| NearestNeighborSearch
Nearest neighbor search, also known as proximity search, similarity search
or closest point search, is an optimization problem for finding closest
points in metric spaces.
|
| Neighbor
The object encapsulates the results of nearest neighbor search.
|
| RNNSearch
A range nearest neighbor search retrieves the nearest neighbors to a query
in a range.
|
| SNLSH.AbstractSentence |
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