rmcfs: The MCFS-ID Algorithm for Feature Selection and Interdependency Discovery (original) (raw)
MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, 'small n large p' transactional and biological data. M. Draminski, J. Koronacki (2018) <doi:10.18637/jss.v085.i12>.
| Version: | 1.3.6 |
|---|---|
| Depends: | rJava (≥ 0.5-0), R (≥ 2.70) |
| Imports: | yaml, ggplot2, gridExtra, reshape2, dplyr, stringi, igraph (≥ 2.0.0), data.table (≥ 1.0.1) |
| Suggests: | testthat, R.rsp |
| Published: | 2024-08-19 |
| DOI: | 10.32614/CRAN.package.rmcfs |
| Author: | Michal Draminski [aut, cre], Jacek Koronacki [aut], Julian Zubek [ctb] |
| Maintainer: | Michal Draminski <michal.draminski at ipipan.waw.pl> |
| License: | GPL-3 |
| URL: | https://home.ipipan.waw.pl/m.draminski/mcfs.html |
| NeedsCompilation: | no |
| SystemRequirements: | Java (>= 7) |
| Citation: | rmcfs citation info |
| Materials: | NEWS |
| CRAN checks: | rmcfs results |
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