Package: UAHDataScienceUC
Title: Learn Clustering Techniques Through Examples and Code
Version: 1.0.1
Authors@R: c(
       person(
            "Eduardo",
            "Ruiz Sabajanes",
            email = "eduardo.ruizs@edu.uah.es",
            role = c("aut")
        ),
        person(
            "Roberto", 
            "Alcantara",
            email = "roberto.alcantara@edu.uah.es",
            role = c("aut")
        ),
        person(
            "Juan Jose",
            "Cuadrado Gallego",
            email = "jjcg@uah.es",
            role = c("aut"),
            comment = c(ORCID = "0000-0001-8178-5556")
        ),
        person(
            "Andriy",
            "Protsak Protsak",
            email = "andriy.protsak@edu.uah.es",
            role = c("aut", "cre")
        ),
        person(
            "Universidad de Alcala",
            role = c("cph")
        )
    )
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.
License: MIT + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Depends: R (>= 4.3.0)
Imports: proxy (>= 0.4-27), cli (>= 3.6.1)
Suggests: deldir (>= 1.0-9), knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
Repository: https://andriyprotsak5.r-universe.dev
Date/Publication: 2025-02-17 15:30:35 UTC
RemoteUrl: https://github.com/andriyprotsak5/UAHDataScienceUC
RemoteRef: HEAD
RemoteSha: a4c1398e730627b6e0b9fcd927dff526c5c35eb7
NeedsCompilation: no
Packaged: 2026-06-23 10:26:17 UTC; root
Author: Eduardo Ruiz Sabajanes [aut],
  Roberto Alcantara [aut],
  Juan Jose Cuadrado Gallego [aut] (ORCID:
    <https://orcid.org/0000-0001-8178-5556>),
  Andriy Protsak Protsak [aut, cre],
  Universidad de Alcala [cph]
Maintainer: Andriy Protsak Protsak <andriy.protsak@edu.uah.es>