UAHDataScienceUC
Learn Clustering Techniques Through Examples and Code
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling linux/jammy R-4.5 | UAHDataScienceUC_1.0.1.tar.gz |
217.2 KiB |
1.0.1 |
rolling linux/noble R-4.5 | UAHDataScienceUC_1.0.1.tar.gz |
217.9 KiB |
1.0.1 |
rolling source/ R- | UAHDataScienceUC_1.0.1.tar.gz |
115.8 KiB |
1.0.1 |
latest linux/jammy R-4.5 | UAHDataScienceUC_1.0.1.tar.gz |
217.2 KiB |
1.0.1 |
latest linux/noble R-4.5 | UAHDataScienceUC_1.0.1.tar.gz |
217.9 KiB |
1.0.1 |
latest source/ R- | UAHDataScienceUC_1.0.1.tar.gz |
115.8 KiB |
1.0.1 |
2026-04-26 source/ R- | UAHDataScienceUC_1.0.1.tar.gz |
115.8 KiB |
1.0.1 |
2026-04-23 source/ R- | UAHDataScienceUC_1.0.1.tar.gz |
115.8 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | UAHDataScienceUC_1.0.1.zip |
222.1 KiB |
1.0.1 |
2025-04-20 source/ R- | UAHDataScienceUC_1.0.1.tar.gz |
115.8 KiB |