clustlearn: Learn Clustering Techniques Through Examples and Code

Clustering methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in Ezugwu et. al., (2022) <doi:10.1016/j.engappai.2022.104743>; and datasets to test them on, which highlight the strengths and weaknesses of each technique, as presented in the clustering section of 'scikit-learn' (Pedregosa et al., 2011) <>.

Version: 1.0.0
Depends: R (≥ 4.3.0)
Imports: proxy (≥ 0.4-27), cli (≥ 3.6.1)
Suggests: deldir (≥ 1.0-9)
Published: 2023-09-14
DOI: 10.32614/CRAN.package.clustlearn
Author: Eduardo Ruiz Sabajanes [aut, cre], Juan Jose Cuadrado Gallego ORCID iD [ctb], Universidad de Alcala [cph]
Maintainer: Eduardo Ruiz Sabajanes <eduardo.ruizs at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: clustlearn results


Reference manual: clustlearn.pdf


Package source: clustlearn_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): clustlearn_1.0.0.tgz, r-oldrel (arm64): clustlearn_1.0.0.tgz, r-release (x86_64): clustlearn_1.0.0.tgz, r-oldrel (x86_64): clustlearn_1.0.0.tgz


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