rmcfs: The MCFS-ID Algorithm for Feature Selection and Interdependency
Discovery
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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