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 |
Documentation:
Downloads:
Reverse dependencies:
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