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Feature subset selection algorithms modularized in search algorithms and measure utilities. Full list and more information available at <https://dicits.ugr.es/software/FSinR/>.
| Version: | 2.0.5 |
| Imports: | rpart, neuralnet, class, digest, caret, mlbench, Rdpack, GA, dplyr, tidyr, prodlim, rlang, purrr, e1071 |
| Suggests: | testthat, knitr, rmarkdown, RSNNS |
| Published: | 2020-11-23 |
| Author: | Alfonso Jiménez-Vílchez [aut, cre], Francisco Aragón-Royón [aut], Adan M. Rodriguez [aut], Antonio Arauzo-Azofra [aut], José Manuel Benítez [aut] |
| Maintainer: | Alfonso Jiménez-Vílchez <i52jivia at uco.es> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | FSinR citation info |
| CRAN checks: | FSinR results |
| Reference manual: | FSinR.pdf |
| Vignettes: |
A Short Introduction to the FSinR Package Evaluation and algorithms combination |
| Package source: | FSinR_2.0.5.tar.gz |
| Windows binaries: | r-devel: FSinR_2.0.5.zip, r-release: FSinR_2.0.5.zip, r-oldrel: FSinR_2.0.5.zip |
| macOS binaries: | r-release (arm64): FSinR_2.0.5.tgz, r-oldrel (arm64): FSinR_2.0.5.tgz, r-release (x86_64): FSinR_2.0.5.tgz, r-oldrel (x86_64): FSinR_2.0.5.tgz |
| Old sources: | FSinR archive |
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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.
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