Package: binomialRF 0.1.0

Samir Rachid Zaim

binomialRF: Binomial Random Forest Feature Selection

The 'binomialRF' is a new feature selection technique for decision trees that aims at providing an alternative approach to identify significant feature subsets using binomial distributional assumptions (Rachid Zaim, S., et al. (2019)) <doi:10.1101/681973>. Treating each splitting variable selection as a set of exchangeable correlated Bernoulli trials, 'binomialRF' then tests whether a feature is selected more often than by random chance.

Authors:Samir Rachid Zaim [aut, cre]

binomialRF_0.1.0.tar.gz
binomialRF_0.1.0.tar.gz(r-4.5-noble)binomialRF_0.1.0.tar.gz(r-4.4-noble)
binomialRF_0.1.0.tgz(r-4.4-emscripten)binomialRF_0.1.0.tgz(r-4.3-emscripten)
binomialRF.pdf |binomialRF.html✨
binomialRF/json (API)
NEWS

# Install 'binomialRF' in R:
install.packages('binomialRF', repos = 'https://cloud.r-project.org')
Datasets:
  • pmf_list - A prebuilt distribution for correlated binary data

On CRAN:

Conda:

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

softwaregenepredictionstatisticalmethoddecisiontreedimensionreductionexperimentaldesign

2.70 score 334 downloads 1 mentions 5 exports 6 dependencies

Last updated 5 years agofrom:f29cabf788. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 13 2025
R-4.5-linuxOKMar 13 2025
R-4.4-linuxOKMar 13 2025

Exports:binomialRFcalculateBinomialPcalculateBinomialP_Interactiongeneset_binomialRFk_binomialRF

Dependencies:data.tablejsonliterandomForestrlistXMLyaml

binomialRF Feature Selection Vignette

Samir Rachid Zaim

Rendered frommy-vignette.Rmdusingknitr::rmarkdownon Mar 13 2025.

Last update: 2020-03-26
Started: 2020-01-31

Citation

To cite package ‘binomialRF’ in publications use:

Rachid Zaim S (2020). binomialRF: Binomial Random Forest Feature Selection. R package version 0.1.0, https://CRAN.R-project.org/package=binomialRF.

Corresponding BibTeX entry: 

  @Manual{,
    title = {binomialRF: Binomial Random Forest Feature Selection},
    author = {Samir {Rachid Zaim}},
    year = {2020},
    note = {R package version 0.1.0},
    url = {https://CRAN.R-project.org/package=binomialRF},
  }

Readme and manuals

binomialRF R Package

The binomialRF package is an R package that provides a feature selection algorithm to be used in randomForest classifiers. Treating each tree as a quasi binomial stochastic process in a random forest, binomialRF determines a feature’s importance by how often they are selected in practice vs. as expected by random chance. Given that trees are co-dependent as they subsample the same data, a theoretical adjustment is made using a generalization of the binomial distribution that adds a parameter to model correlation/association between trials.

Installing from CRAN

The binomialRF R package is on CRAN, and you can install as follows:

install.packages('binomialRF')

The CRAN version will always be the most stable release.

Installing from GitHub

To install experimental updates from the binomialRF , install it from GitHub directly, follow the code instructions below!

install.packages("devtools")


# The following dependencies might need to be installed
# manually if they're not installed by devtools. 

install.packages(c("ggplot2", "randomForest", "data.table","rlist", "correlbinom"))
devtools::install_github("SamirRachidZaim/binomialRF")
library(binomialRF)

These GitHub updates and features are experimental and will not be available in the CRAN version until the next, stable release is pushed.

References:

The main manuscript is included as a preprint in bioRxiv: https://doi.org/10.1101/681973, and has also been submitted for consideration at Frontiers in Genetics.