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UAHDataScienceUC

1.0.1Package record

Learn Clustering Techniques Through Examples and Code

0packages depend
1.9Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

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.

Changes in 1.0.1
  • Reseting old par settings after using helper function in divisive_clustering
  • Updating DESCRIPTION file with acronyms meanings

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 1.6 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-04-18
  • ERROR13 OK, 1 ERROR2026-04-16
  • OK14 OK2026-04-12
Show 2 earlier changesHide 2 earlier changes
  • ERROR13 OK, 1 ERROR2026-04-05
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.0.1
READMENoVignettesYes · 1 · dynamicNEWSYes · 67% structured · mentions 1.0.1Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
22
Examples that run
100%7 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

1.9K
CRAN downloads in the past year
Rank #23,425 · ~5/day · ~159/mo
Daily download trend is not available in this view yet.
21630 days
55890 days
1.9K1 year
Compare downloads with other packages →
Also on69 r2u7 autocran

Dependencies

Declared dependencies
5 external dependencies (excludes base and recommended)

Installing UAHDataScienceUC adds 2 packages (2 with compiled code, 699 KB of source tarballs). Heaviest: cli 629 KB, proxy 70 KB.

Depends (1)
R >= 4.3.0
Imports (2)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (5)
Author, Maintainer since 1.0.0 (2025)
Copyright holder
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 1.0.1Latest
    record
    2025-02-17 · current release · diff ↗
  • 1.0.0
    record
    2025-02-17
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2025-02-17
Total releases
2 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.3.0
Bundled data
48 KB / 6 files
Download size
118 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("UAHDataScienceUC")
Protsak Protsak, A., Universidad de Alcala, Alcantara, R., Cuadrado Gallego, J. J., & Ruiz Sabajanes, E. (2025). UAHDataScienceUC: Learn Clustering Techniques Through Examples and Code (Version 1.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.UAHDataScienceUC

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for UAHDataScienceUC version 1.0.1 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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