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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 |
Reference manual: | clustlearn.pdf |
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 |
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These binaries (installable software) and packages are in development.
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