Educational Outlier Detection Algorithms with Step-by-Step Tutorials
Overview
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.
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From NEWS.md in the release
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 15
- Examples that run
- 100%15 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- UAHDataScienceO HTML
Downloads
Dependencies
Installing UAHDataScienceO adds no packages beyond those that come with R.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.0.0Latest2025-02-20 · current release
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2025-02-20
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 79 KB
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