HDoutliers: Leland Wilkinson's Algorithm for Detecting Multidimensional Outliers

An implementation of an algorithm for outlier detection that can handle a) data with a mixed categorical and continuous variables, b) many columns of data, c) many rows of data, d) outliers that mask other outliers, and e) both unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, HDoutliers is based on a distributional model that uses probabilities to determine outliers. See <https://www.cs.uic.edu/~wilkinson/Publications/outliers.pdf>.

Author
Chris Fraley [aut, cre], Leland Wilkinson [ctb]
Date of publication
2016-12-24 11:23:58
Maintainer
Chris Fraley <cfraley@tableau.com>
License
MIT + file LICENSE
Version
0.15
URLs

View on CRAN

Man pages

dots
One dimensional dots dataset - outlier detection example
ex2D
Two dimensional dataset - outlier detection example
getHDmembers
Partitioning Stage of the HDoutliers Algorithm
getHDoutliers
Outlier Detection Stage of the HD Outliers Algorithm
HDoutliers
Leland Wilkinson's HDoutliers Algorithm for Outlier Detection
plotHDoutliers
Display Outlier Detection Results

Files in this package

HDoutliers
HDoutliers/inst
HDoutliers/inst/doc
HDoutliers/inst/doc/HDoutliers.pdf
HDoutliers/NAMESPACE
HDoutliers/CHANGELOG
HDoutliers/data
HDoutliers/data/dots.rda
HDoutliers/data/ex2D.rda
HDoutliers/R
HDoutliers/R/getHDmembers.R
HDoutliers/R/HDoutliers.R
HDoutliers/R/plotHDoutliers.R
HDoutliers/R/getHDoutliers.R
HDoutliers/MD5
HDoutliers/DESCRIPTION
HDoutliers/man
HDoutliers/man/getHDoutliers.Rd
HDoutliers/man/ex2D.Rd
HDoutliers/man/getHDmembers.Rd
HDoutliers/man/dots.Rd
HDoutliers/man/plotHDoutliers.Rd
HDoutliers/man/HDoutliers.Rd
HDoutliers/LICENSE