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UAHDataScienceUC
View on CRAN: Click
here
Download and install UAHDataScienceUC package within the R console
Install from CRAN:
install.packages("UAHDataScienceUC")
Install from Github:
library("remotes")
install_github("cran/UAHDataScienceUC") Install by package version:
library("remotes")
install_version("UAHDataScienceUC", "1.0.1") Attach the package and use:
library("UAHDataScienceUC")
Maintained by
Andriy Protsak Protsak
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-02-17
Latest Update: 2025-02-17
Description:
A comprehensive educational package combining clustering algorithms with detailed step-by-step explanations. Provides implementations of both traditional (hierarchical, k-means) and modern (Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Gaussian Mixture Models (GMM), genetic k-means) clustering methods as described in Ezugwu et. al., (2022) <doi:10.1016/j.engappai.2022.104743>. Includes educational datasets highlighting different clustering challenges, based on 'scikit-learn' examples (Pedregosa et al., 2011) <https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html>. Features detailed algorithm explanations, visualizations, and weighted distance calculations for enhanced learning.
How to cite:
Andriy Protsak Protsak (2025). UAHDataScienceUC: Learn Clustering Techniques Through Examples and Code. R package version 1.0.1, https://cran.r-project.org/web/packages/UAHDataScienceUC. Accessed 25 Jun. 2026.
Previous versions and publish date:
1.0.0 (2025-02-17 13:20)
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