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.
|Author||Jaroslav Kuchar [aut, cre]|
|Maintainer||Jaroslav Kuchar <[email protected]>|
|License||Apache License (== 2.0) | file LICENSE|
|Package repository||View on CRAN|
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