fpmoutliers: Frequent Pattern Mining Outliers

Algorithms for detection of outliers based on frequent pattern mining. Such algorithms follow the paradigm: if an instance contains more frequent patterns, it means that this data instance is unlikely to be an anomaly (He Zengyou, Xu Xiaofei, Huang Zhexue Joshua, Deng Shengchun (2005) <doi:10.2298/CSIS0501103H>). The package implements a list of existing state of the art algorithms as well as other published approaches: FPI, WFPI, FPOF, FPCOF, LFPOF, MFPOF, WCFPOF and WFPOF.

Version: 0.1.0
Depends: R (≥ 3.3.0)
Imports: pmml, XML, Matrix, R.utils, arules (≥ 1.5-4), foreach, doParallel, parallel, methods, pryr
Suggests: testthat
Published: 2017-11-22
Author: Jaroslav Kuchar [aut, cre]
Maintainer: Jaroslav Kuchar <jaroslav.kuchar at gmail.com>
BugReports: https://github.com/jaroslav-kuchar/fpmoutliers/issues
License: Apache License (== 2.0) | file LICENSE
URL: https://github.com/jaroslav-kuchar/fpmoutliers
NeedsCompilation: no
Materials: README NEWS
CRAN checks: fpmoutliers results


Reference manual: fpmoutliers.pdf
Package source: fpmoutliers_0.1.0.tar.gz
Windows binaries: r-devel: fpmoutliers_0.1.0.zip, r-release: fpmoutliers_0.1.0.zip, r-oldrel: fpmoutliers_0.1.0.zip
OS X El Capitan binaries: r-release: fpmoutliers_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: fpmoutliers_0.1.0.tgz


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