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.
|Gaston Besanson <besanson at gmail.com>
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