HighDimOut: Outlier Detection Algorithms for High-Dimensional Data

Three high-dimensional outlier detection algorithms and a outlier unification scheme are implemented in this package. The angle-based outlier detection (ABOD) algorithm is based on the work of Kriegel, Schubert, and Zimek [2008]. The subspace outlier detection (SOD) algorithm is based on the work of Kriegel, Kroger, Schubert, and Zimek [2009]. The feature bagging-based outlier detection (FBOD) algorithm is based on the work of Lazarevic and Kumar [2005]. The outlier unification scheme is based on the work of Kriegel, Kroger, Schubert, and Zimek [2011].

Version: 1.0.0
Depends: R (≥ 3.0.1)
Imports: foreach, DMwR, plyr, proxy, FNN, ggplot2
Suggests: knitr
Published: 2015-04-02
Author: Cheng Fan
Maintainer: Cheng Fan <raja8885 at hotmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: HighDimOut results

Downloads:

Reference manual: HighDimOut.pdf
Vignettes: Using Outlier Detection Algorithms to Analyze NBA Players
Package source: HighDimOut_1.0.0.tar.gz
Windows binaries: r-devel: HighDimOut_1.0.0.zip, r-devel-gcc8: HighDimOut_1.0.0.zip, r-release: HighDimOut_1.0.0.zip, r-oldrel: HighDimOut_1.0.0.zip
OS X binaries: r-release: HighDimOut_1.0.0.tgz, r-oldrel: HighDimOut_1.0.0.tgz

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