The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.