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.

Author | Gaston Besanson |

Date of publication | 2015-02-12 22:37:24 |

Maintainer | Gaston Besanson <besanson@gmail.com> |

License | GPL-3 |

Version | 0.0.1 |

**Distance_for_KNN_test:** Distance for KNN Test The Distance_for_KNN_test returns the...

**k.nearest.neighbors:** k-Nearest Neighbors the 'k.nearest.neigbors' gives the list...

**knn_test_function:** KNN Test The knn_test_function returns the labels for a test...

**knn_training_function:** KNN Training The knn_training_function returns the labels for...

FastKNN

FastKNN/NAMESPACE

FastKNN/R

FastKNN/R/FastKNN.R
FastKNN/MD5

FastKNN/DESCRIPTION

FastKNN/man

FastKNN/man/knn_test_function.Rd
FastKNN/man/k.nearest.neighbors.Rd
FastKNN/man/knn_training_function.Rd
FastKNN/man/Distance_for_KNN_test.Rd
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