The MCFS-ID Algorithm for Feature Selection and Interdependency Discovery
Overview
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.
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From NEWS.md in the release
Install
Health
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- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- WARNING12 OK, 1 WARNING2026-06-07
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- OK14 OK2026-04-06
- ERROR13 OK, 1 ERROR2026-04-04
- OK14 OK2026-03-10
Documentation
- Help pages
- 17
- Examples that run
- 12%2 run in a plain check · 15 never run
- Exported functions with examples
- 100%
- Documented parameters
- 99%
- Return-value docs
- 35%
- Help pages citing references
- 6%
Downloads
Dependencies
Installing rmcfs adds 35 packages (20 with compiled code, 41 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
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Package metadata
- First published
- 2016-03-28
- Total releases
- 24 / 10 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.70
- Download size
- 4.5 MB
Cite
Cite this package
Run in R for the authors' entry:
citation("rmcfs")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.18637/jss.v085.i12.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.