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UAHDataScienceO  

Educational Outlier Detection Algorithms with Step-by-Step Tutorials
View on CRAN: Click here


Download and install UAHDataScienceO package within the R console
Install from CRAN:
install.packages("UAHDataScienceO")

Install from Github:
library("remotes")
install_github("cran/UAHDataScienceO")

Install by package version:
library("remotes")
install_version("UAHDataScienceO", "1.0.0")



Attach the package and use:
library("UAHDataScienceO")
Maintained by
Andriy Protsak Protsak
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-02-20
Latest Update: 2025-02-20
Description:
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>.
How to cite:
Andriy Protsak Protsak (2025). UAHDataScienceO: Educational Outlier Detection Algorithms with Step-by-Step Tutorials. R package version 1.0.0, https://cran.r-project.org/web/packages/UAHDataScienceO. Accessed 05 Jun. 2026.
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Functions, R codes and Examples using the UAHDataScienceO R package
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