Package: RFlocalfdr 0.9

RFlocalfdr: Significance Level for Random Forest Impurity Importance Scores

Sets a significance level for Random Forest MDI (Mean Decrease in Impurity, Gini or sum of squares) variable importance scores, using an empirical Bayes approach. See Dunne et al. (2022) <doi:10.1101/2022.04.06.487300>.

Authors:Robert Dunne [aut, cre]

RFlocalfdr_0.9.tar.gz
RFlocalfdr_0.9.zip(r-4.7-any)RFlocalfdr_0.9.zip(r-4.6-any)RFlocalfdr_0.9.zip(r-4.5-any)
RFlocalfdr_0.9.tgz(r-4.6-any)RFlocalfdr_0.9.tgz(r-4.5-any)
RFlocalfdr_0.9.tar.gz(r-4.7-any)RFlocalfdr_0.9.tar.gz(r-4.6-any)
RFlocalfdr_0.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
RFlocalfdr/json (API)

# Install 'RFlocalfdr' in R:
install.packages('RFlocalfdr', repos = c('https://parsifal9.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/parsifal9/rflocalfdr/issues

Datasets:

On CRAN:

Conda:

4.00 score 1 stars 8 scripts 223 downloads 18 exports 17 dependencies

Last updated from:04c5e1d7fa. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK124
source / vignettesOK160
linux-releaseOK137
macos-releaseOK161
macos-oldrelOK164
windows-develOK120
windows-releaseOK124
windows-oldrelOK126
wasm-releaseOK115

Exports:count_variablesdetermine_cutoffdetermine.Cdsnf.fitfit.to.data.setfit.to.data.set.wrapperlocal.fdrmy_PIMPmy_ranger_PIMPmy.dsnmy.test1funplotQpropTrueNullByLocalFDRpsnqsnrun.it.importancessignificant.genes

Dependencies:fitdistrpluslatticeMASSMatrixMatrixModelsminpack.lmmnormtnumDerivquantregrandomForestrangerRcppRcppEigenrlangsnSparseMsurvival

RFlocalfdr A Simulated Data Example
Introduction | Discussion and Conclusion | The Simulation | data setup | Random forest | parameter setting for a RF | RFlocalfdr | determine cutoff | recover variables | Boruta | Recursive Feature Elimination | AIR | PIMP | Other Methods | permutation importance | impurity corrected | cforest | sobolMDA | Shap values | SHAFF: Fast and consistent SHApley eFfect estimates via random Forests | iml: Interpretable Machine Learning | mlr3 | fastshap
Rendered fromsimulated.Rmdusingknitr::rmarkdown

Last update: 2025-01-30
Started: 2023-01-27

Smoking data
load the data | fit a ranger model | Determine a cutoff to get a unimodal density. | fit RFlocalfdr
Rendered fromSmoking.Rmdusingknitr::rmarkdown

Last update: 2025-01-30
Started: 2023-01-25