abodOutlier: Angle-Based Outlier Detection

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.

Version: 0.1
Depends: cluster, R (≥ 3.1.2)
Published: 2015-08-31
Author: Jose Jimenez
Maintainer: Jose Jimenez <jose at jimenezluna.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: abodOutlier results

Documentation:

Reference manual: abodOutlier.pdf

Downloads:

Package source: abodOutlier_0.1.tar.gz
Windows binaries: r-devel: abodOutlier_0.1.zip, r-release: abodOutlier_0.1.zip, r-oldrel: abodOutlier_0.1.zip
macOS binaries: r-release (arm64): abodOutlier_0.1.tgz, r-oldrel (arm64): abodOutlier_0.1.tgz, r-release (x86_64): abodOutlier_0.1.tgz

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