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Title: Angle-Based Outlier Detection
Version: 0.1
Author: Jose Jimenez <jose@jimenezluna.com>
Maintainer: Jose Jimenez <jose@jimenezluna.com>
Description: 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.
Depends: cluster, R (≥ 3.1.2)
License: MIT + file LICENSE
LazyData: true
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2015-08-30 21:39:13 UTC; hawk31
Repository: CRAN
Date/Publication: 2015-08-31 14:31:42

Angle-Based Outlier Factor

Description

Computes angle-based outlier factor for each observation in the dataset

Usage

abod(data, method = "complete", n_sample_size = trunc(nrow(data)/10), k = 15)

Arguments

data

Dataframe in which to compute angle-based outlier factor.

method

Method to perform. 'complete' will use the entire dataset (cubic complexity) to compute abof. 'randomized' will use a random sample of the data of size 'n_sample_size'. 'knn' will compute abof among 'k' nearest neighbours.

n_sample_size

Number of random observations to choose in randomized method.

k

Number of nearest neighbours to choose in knn method.

Details

Please note that 'knn' has to compute an euclidean distance matrix before computing abof.

Value

Returns angle-based outlier factor for each observation. A small abof respect the others would indicate presence of an outlier.

Author(s)

Jose Jimenez <jose@jimenezluna.com>

References

[1] Angle-Based Outlier Detection in High-dimensional Data. KDD 2008. Hans-Peter Kriegel, Matthias Schubert, Arthur Zimek. (http://www.dbs.ifi.lmu.de/Publikationen/Papers/KDD2008.pdf)

Examples

abod(faithful, method = "randomized", n_sample_size = 5)
abod(faithful, method = "knn", k = 5)


Angle-based outlier detection

Description

Performs angle-based outlier detection on data. A complete, a randomized and a knn based methods are available.

Package: abodoutlier
Type: Package
Version: 0.1
Date: 2015-08-30
License: MIT License
Maintainer: Jose Jimenez <jose@jimenezluna.com>

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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