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RFlocalfdr

Provides a method for setting the significance level of the MDI (mean decrease in impurity) importances from a random forest model. Based on an empirical Bayes model. See https://www.biorxiv.org/content/10.1101/2022.04.06.487300v2 Thresholding Gini Variable Importance with a single trained Random Forest: An Empirical Bayes Approach (Robert Dunne, Roc Reguant, Priya Ramarao-Milne, Piotr Szul, Letitia Sng, Mischa Lundberg, Natalie A. Twine, Denis C. Bauer) for full details.

Until I figure out how to manage the cran repository:

• the data sets are not available in the cran version
• many of the examples are enclosed in “dontrun” environments

Install devtools from CRAN

install.packages("RFlocalfdr")

Or from GitHub:

devtools::install_github("parsifal9/RFlocalfdr", build_vignettes = TRUE)

Usage

library(RFlocalfdr)
vignette("simulated",package="RFlocalfdr")
vignette("Smoking",package="RFlocalfdr")

License

GNU General Public License

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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