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, r-oldrel (x86_64): abodOutlier_0.1.tgz

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