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Performs angle-based outlier detection on a given dataframe. Three methods are available, a full but slow implementation using all the data that has cubic complexity, a fully randomized one which is way more efficient and another using k-nearest neighbours. These algorithms are specially well suited for high dimensional data outlier detection.
Package details |
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Author | Jose Jimenez <jose@jimenezluna.com> |
Maintainer | Jose Jimenez <jose@jimenezluna.com> |
License | MIT + file LICENSE |
Version | 0.1 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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