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) <https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html>.

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 [ctb], Universidad de Alcala [cph]
Maintainer:	Eduardo Ruiz Sabajanes <eduardo.ruizs at edu.uah.es>
BugReports:	https://github.com/Ediu3095/clustlearn/issues
License:	MIT + file LICENSE
URL:	https://github.com/Ediu3095/clustlearn
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	clustlearn results

Documentation:

Reference manual:

clustlearn.html , clustlearn.pdf

Downloads:

Package source:	clustlearn_1.0.0.tar.gz
Windows binaries:	r-devel: clustlearn_1.0.0.zip, r-release: clustlearn_1.0.0.zip, r-oldrel: clustlearn_1.0.0.zip
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

Linking:

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