FastKNN: Fast k-Nearest Neighbors

Compute labels for a test set according to the k-Nearest Neighbors classification. This is a fast way to do k-Nearest Neighbors classification because the distance matrix -between the features of the observations- is an input to the function rather than being calculated in the function itself every time.

AuthorGaston Besanson
Date of publication2015-02-12 22:37:24
MaintainerGaston Besanson <>

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