CRAN/E | Rforestry

Rforestry

Random Forests, Linear Trees, and Gradient Boosting for Inference and Interpretability

Installation

About

Provides fast implementations of Honest Random Forests, Gradient Boosting, and Linear Random Forests, with an emphasis on inference and interpretability. Additionally contains methods for variable importance, out-of-bag prediction, regression monotonicity, and several methods for missing data imputation. Soren R. Kunzel, Theo F. Saarinen, Edward W. Liu, Jasjeet S. Sekhon (2019) .

github.com/forestry-labs/Rforestry
Bug report File report

Key Metrics

Version 0.10.0
Published 2023-03-25 451 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks Rforestry results

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Maintainer

Maintainer

Theo Saarinen

Authors

Sören Künzel

aut

Theo Saarinen

aut / cre

Simon Walter

aut

Sam Antonyan

aut

Edward Liu

aut

Allen Tang

aut

Jasjeet Sekhon

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

Rforestry archive

Imports

Rcpp ≥ 0.12.9
parallel
methods
visNetwork
glmnet ≥4.1
grDevices
onehot
pROC

Suggests

testthat
knitr
rmarkdown
mvtnorm

LinkingTo

Rcpp
RcppArmadillo
RcppThread

Reverse Imports

distillML