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binomialRF
View on CRAN: Click
here
Download and install binomialRF package within the R console
Install from CRAN:
install.packages("binomialRF")
Install from Github:
library("remotes")
install_github("cran/binomialRF")
Install by package version:
library("remotes")
install_version("binomialRF", "0.1.0")
Attach the package and use:
library("binomialRF")
Maintained by
Samir Rachid Zaim
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-01-31
Latest Update: 2020-03-26
Description:
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)) . 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.
How to cite:
Samir Rachid Zaim (2020). binomialRF: Binomial Random Forest Feature Selection. R package version 0.1.0, https://cran.r-project.org/web/packages/binomialRF
Other packages that cited binomialRF R package
View binomialRF citation profile
Other R packages that binomialRF depends,
imports, suggests or enhances
Functions, R codes and Examples using
the binomialRF R package
Some associated functions: binomialRF . calculateBinomialP . calculateBinomialP_Interaction . dot-cv_binomialRF . geneset_binomialRF . k_binomialRF . pmf_list .
Some associated R codes: binomialRF.R . calculateBinomialP.R . calculateBinomialP_Interaction.R . cv_binomialRF.R . geneset_binomialRF.R . k_binomialRF.R . Full binomialRF package functions and examples
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