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.
| Version: | 1.0.1 |
| Depends: | R (≥ 4.3.0) |
| Imports: | proxy (≥ 0.4-27),cli (≥ 3.6.1) |
| Suggests: | deldir (≥ 1.0-9),knitr,rmarkdown |
| Published: | 2025-02-17 |
| DOI: | 10.32614/CRAN.package.UAHDataScienceUC |
| Author: | Eduardo Ruiz Sabajanes [aut], Roberto Alcantara [aut], Juan Jose Cuadrado Gallego [aut], Andriy Protsak Protsak [aut, cre], Universidad de Alcala [cph] |
| Maintainer: | Andriy Protsak Protsak <andriy.protsak at edu.uah.es> |
| License: | MIT + fileLICENSE |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | UAHDataScienceUC results |
Documentation:
| Reference manual: | UAHDataScienceUC.html ,UAHDataScienceUC.pdf |
| Vignettes: | Using the Unified Interface in clustlearn 1.1.0 (source,R code) |
Downloads:
| Package source: | UAHDataScienceUC_1.0.1.tar.gz |
| Windows binaries: | r-devel:UAHDataScienceUC_1.0.1.zip, r-release:UAHDataScienceUC_1.0.1.zip, r-oldrel:UAHDataScienceUC_1.0.1.zip |
| macOS binaries: | r-release (arm64):UAHDataScienceUC_1.0.1.tgz, r-oldrel (arm64):UAHDataScienceUC_1.0.1.tgz, r-release (x86_64):UAHDataScienceUC_1.0.1.tgz, r-oldrel (x86_64):UAHDataScienceUC_1.0.1.tgz |
| Old sources: | UAHDataScienceUC archive |
Linking:
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