OutliersLearn: Educational Outlier Package with Common Outlier Detection Algorithms

Provides implementations of some of the most important outlier detection algorithms. Includes a tutorial mode option that shows a description of each algorithm and provides a step-by-step execution explanation of how it identifies outliers from the given data with the specified input parameters. References include the works of Azzedine Boukerche, Lining Zheng, and Omar Alfandi (2020) <doi:10.1145/3381028>, Abir Smiti (2020) <doi:10.1016/j.cosrev.2020.100306>, and Xiaogang Su, Chih-Ling Tsai (2011) <doi:10.1002/widm.19>.

Version: 1.0.0
Suggests: knitr, rmarkdown
Published: 2024-06-05
DOI: 10.32614/CRAN.package.OutliersLearn
Author: Andres Missiego Manjon [aut, cre], Juan Jose Cuadrado Gallego [aut]
Maintainer: Andres Missiego Manjon <andres.missiego at edu.uah.es>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: OutliersLearn results


Reference manual: OutliersLearn.pdf
Vignettes: OutliersLearnVignette


Package source: OutliersLearn_1.0.0.tar.gz
Windows binaries: r-devel: OutliersLearn_1.0.0.zip, r-release: OutliersLearn_1.0.0.zip, r-oldrel: OutliersLearn_1.0.0.zip
macOS binaries: r-release (arm64): OutliersLearn_1.0.0.tgz, r-oldrel (arm64): OutliersLearn_1.0.0.tgz, r-release (x86_64): OutliersLearn_1.0.0.tgz, r-oldrel (x86_64): OutliersLearn_1.0.0.tgz


Please use the canonical form https://CRAN.R-project.org/package=OutliersLearn to link to this page.