Package: RegEnRF 2.0.1

RegEnRF: Regression-Enhanced Random Forests

A novel generalized Random Forest method, that can improve on RFs by borrowing the strength of penalized parametric regression. Based on Zhang et al. (2019) <doi:10.48550/arXiv.1904.10416>.

Authors:Umberto Minora [aut, cre, cph]

RegEnRF_2.0.1.tar.gz
RegEnRF_2.0.1.zip(r-4.7-any)RegEnRF_2.0.1.zip(r-4.6-any)RegEnRF_2.0.1.zip(r-4.5-any)
RegEnRF_2.0.1.tgz(r-4.6-any)RegEnRF_2.0.1.tgz(r-4.5-any)
RegEnRF_2.0.1.tar.gz(r-4.7-any)RegEnRF_2.0.1.tar.gz(r-4.6-any)
RegEnRF_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RegEnRF/json (API)

# Install 'RegEnRF' in R:
install.packages('RegEnRF', repos = c('https://umbe1987.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/umbe1987/regenrf/issues

On CRAN:

Conda:

3.60 score 3 scripts 236 downloads 1 exports 11 dependencies

Last updated from:ff285b2c12. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK98
source / vignettesOK352
linux-releaseOK101
macos-releaseOK100
macos-oldrelOK154
windows-develOK194
windows-releaseOK64
windows-oldrelOK66
wasm-releaseOK85

Exports:RegEnRF

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixrandomForestRcppRcppEigenshapesurvival