Package: rmcfs 1.3.6

Michal Draminski

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>.

Authors:Michal Draminski [aut, cre], Jacek Koronacki [aut], Julian Zubek [ctb]

rmcfs_1.3.6.tar.gz
rmcfs_1.3.6.tar.gz(r-4.5-noble)rmcfs_1.3.6.tar.gz(r-4.4-noble)
rmcfs_1.3.6.tgz(r-4.4-emscripten)rmcfs_1.3.6.tgz(r-4.3-emscripten)
rmcfs.pdf |rmcfs.html
rmcfs/json (API)
NEWS

# Install 'rmcfs' in R:
install.packages('rmcfs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.37 score 1 stars 1 packages 26 scripts 499 downloads 3 mentions 17 exports 42 dependencies

Last updated 4 months agofrom:105150ec71. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-linuxOKNov 05 2024

Exports:artificial.databuild.idgraphexport.plotsexport.resultfix.dataimport.resultmcfsplot.idgraphplot.mcfsprint.mcfsprune.dataread.adhread.adxshowmewrite.adhwrite.adxwrite.arff

Dependencies:clicolorspacecpp11data.tabledplyrfansifarvergenericsggplot2gluegridExtragtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppreshape2rJavarlangscalesstringistringrtibbletidyselectutf8vctrsviridisLitewithryaml

Draminski & Koronacki (2018): rmcfs paper (Journal of Statistical Software)

Rendered fromv85i12.pdf.asisusingR.rsp::asison Nov 05 2024.

Last update: 2018-07-27
Started: 2018-07-27