abod: Angle-Based Outlier Factor

Description Usage Arguments Details Value Author(s) References Examples

Description

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

Usage

1
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

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

abodOutlier documentation built on May 2, 2019, 8:23 a.m.