UAHDataScienceSC: Learn Supervised Classification Methods Through Examples and Code

Supervised classification methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in PK Josephine et. al., (2021) <doi:10.59176/kjcs.v1i1.1259>; and datasets to test them on, which highlight the strengths and weaknesses of each technique.

Version:	1.0.0
Depends:	R (≥ 4.3.0)
Imports:	cli (≥ 3.6.1)
Suggests:	knitr, rmarkdown
Published:	2025-02-17
DOI:	10.32614/CRAN.package.UAHDataScienceSC
Author:	Víctor Amador Padilla [aut], Juan Jose Cuadrado Gallego [ctb], Andriy Protsak Protsak [aut, cre], Universidad de Alcala [cph]
Maintainer:	Andriy Protsak Protsak <andriy.protsak at edu.uah.es> [email to maintainer is undeliverable]
License:	MIT + file LICENSE
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	UAHDataScienceSC results

Documentation:

Reference manual:	UAHDataScienceSC.html , UAHDataScienceSC.pdf
Vignettes:	Basic Functionality of UAHDataScienceSC (source, R code)

Downloads:

Package source:	UAHDataScienceSC_1.0.0.tar.gz
Windows binaries:	r-devel: UAHDataScienceSC_1.0.0.zip, r-release: UAHDataScienceSC_1.0.0.zip, r-oldrel: UAHDataScienceSC_1.0.0.zip
macOS binaries:	r-release (arm64): UAHDataScienceSC_1.0.0.tgz, r-oldrel (arm64): UAHDataScienceSC_1.0.0.tgz, r-release (x86_64): UAHDataScienceSC_1.0.0.tgz, r-oldrel (x86_64): UAHDataScienceSC_1.0.0.tgz

Linking:

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