Package: EFS 1.0.3

Ursula Neumann

EFS: Tool for Ensemble Feature Selection

Provides a function to check the importance of a feature based on a dependent classification variable. An ensemble of feature selection methods is used to determine the normalized importance value of all features. Combining these methods in one function (building the cumulative importance values) provides a stable feature selection tool. This selection can also be viewed in a barplot using the barplot_fs() function and proved using the evaluation function efs_eval().

Authors:Nikita Genze, Ursula Neumann

EFS_1.0.3.tar.gz
EFS_1.0.3.zip(r-4.5)EFS_1.0.3.zip(r-4.4)EFS_1.0.3.zip(r-4.3)
EFS_1.0.3.tgz(r-4.5-any)EFS_1.0.3.tgz(r-4.4-any)EFS_1.0.3.tgz(r-4.3-any)
EFS_1.0.3.tar.gz(r-4.5-noble)EFS_1.0.3.tar.gz(r-4.4-noble)
EFS_1.0.3.tgz(r-4.4-emscripten)EFS_1.0.3.tgz(r-4.3-emscripten)
EFS.pdf |EFS.html✨
EFS/json (API)

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

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Datasets:
  • efsdata - Meteorological data for feature selection analysis

On CRAN:

Conda:

archivedpackagesr-universe

2.70 score 5 stars 168 downloads 19 mentions 3 exports 26 dependencies

Last updated 2 days agofrom:256e45568b (on package/EFS). Checks:6 OK, 3 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 31 2025
R-4.5-winNOTEMar 31 2025
R-4.5-macNOTEMar 31 2025
R-4.5-linuxNOTEMar 31 2025
R-4.4-winOKMar 31 2025
R-4.4-macOKMar 31 2025
R-4.4-linuxOKMar 31 2025
R-4.3-winOKMar 31 2025
R-4.3-macOKMar 31 2025

Exports:barplot_fsefs_evalensemble_fs

Dependencies:bitopscaToolscodetoolscoingplotsgtoolsKernSmoothlatticelibcoinMASSMatrixmatrixStatsmodeltoolsmultcompmvtnormpartyplyrpROCrandomForestRcppROCRsandwichstrucchangesurvivalTH.datazoo