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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) |
Published: | 2023-09-19 |
DOI: | 10.32614/CRAN.package.LearnSL |
Author: | Víctor Amador Padilla [aut, cre], Juan Jose Cuadrado Gallego [ctb], Universidad de Alcala [cph] |
Maintainer: | Víctor Amador Padilla <victor.amador at edu.uah.es> |
BugReports: | https://github.com/ComiSeng/LearnSL/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/ComiSeng/LearnSL |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | LearnSL results |
Reference manual: | LearnSL.pdf |
Package source: | LearnSL_1.0.0.tar.gz |
Windows binaries: | r-devel: LearnSL_1.0.0.zip, r-release: LearnSL_1.0.0.zip, r-oldrel: LearnSL_1.0.0.zip |
macOS binaries: | r-release (arm64): LearnSL_1.0.0.tgz, r-oldrel (arm64): LearnSL_1.0.0.tgz, r-release (x86_64): LearnSL_1.0.0.tgz, r-oldrel (x86_64): LearnSL_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.