smile.neighbor

Interface NearestNeighborSearch<K,V>

Type Parameters:

K - the type of keys.

V - the type of associated objects.

All Known Implementing Classes:

CoverTree, KDTree, LinearSearch, LSH, MPLSH, MutableLSH

public interface NearestNeighborSearch<K,V>

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. The problem is: given a set S of points in a metric space M and a query point q ∈ M, find the closest point in S to q.

In machine learning, we often build a nearest neighbor search data structure, and then search with object in the same dataset. The object itsef is of course the nearest one with distance 0. But this is meaningless and we therefore do the reference check during the search and excludes the query object from the results.

Method Summary

Modifier and Type	Method and Description
Neighbor<K,V>	nearest(K q) Search the nearest neighbor to the given sample.

Method Detail

nearest

Neighbor<K,V> nearest(K q)

Search the nearest neighbor to the given sample.

Parameters:

q - the query key.

Returns:

the nearest neighbor