outliertree: Explainable Outlier Detection Through Decision Tree Conditioning

Outlier detection method that flags suspicious values within observations, constrasting them against the normal values in a user-readable format, potentially describing conditions within the data that make a given outlier more rare. Full procedure is described in Cortes (2020) <doi:10.48550/arXiv.2001.00636>. Loosely based on the 'GritBot' <https://www.rulequest.com/gritbot-info.html> software.

Version:	1.10.0
Depends:	R (≥ 4.3.0)
Imports:	Rcpp (≥ 1.0.1), methods
LinkingTo:	Rcpp, Rcereal
Suggests:	knitr, rmarkdown, kableExtra, data.table
Published:	2024-09-06
DOI:	10.32614/CRAN.package.outliertree
Author:	David Cortes [aut, cre]
Maintainer:	David Cortes <david.cortes.rivera at gmail.com>
BugReports:	https://github.com/david-cortes/outliertree/issues
License:	GPL (≥ 3)
URL:	https://github.com/david-cortes/outliertree
NeedsCompilation:	yes
CRAN checks:	outliertree results

Documentation:

Reference manual:	outliertree.pdf
Vignettes:	Explainable Outlier Detection in Titanic dataset (source, R code) Introducing OutlierTree (source, R code)

Downloads:

Package source:	outliertree_1.10.0.tar.gz
Windows binaries:	r-devel: outliertree_1.10.0.zip, r-release: outliertree_1.10.0.zip, r-oldrel: outliertree_1.10.0.zip
macOS binaries:	r-release (arm64): outliertree_1.10.0.tgz, r-oldrel (arm64): outliertree_1.10.0.tgz, r-release (x86_64): outliertree_1.10.0.tgz, r-oldrel (x86_64): outliertree_1.10.0.tgz
Old sources:	outliertree archive

Reverse dependencies:

Reverse imports:	bagged.outliertrees, itsdm
Reverse suggests:	isotree

Linking:

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