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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.
| Version: | 0.0.1 |
| Imports: | pdist, assertthat |
| Published: | 2015-02-12 |
| Author: | Gaston Besanson |
| Maintainer: | Gaston Besanson <besanson at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | FastKNN results |
| Reference manual: | FastKNN.pdf |
| Package source: | FastKNN_0.0.1.tar.gz |
| Windows binaries: | r-devel: FastKNN_0.0.1.zip, r-release: FastKNN_0.0.1.zip, r-oldrel: FastKNN_0.0.1.zip |
| macOS binaries: | r-release (arm64): FastKNN_0.0.1.tgz, r-oldrel (arm64): FastKNN_0.0.1.tgz, r-release (x86_64): FastKNN_0.0.1.tgz, r-oldrel (x86_64): FastKNN_0.0.1.tgz |
| Reverse imports: | GGoutlieR |
| Reverse suggests: | DRquality, ProjectionBasedClustering |
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