Provides fast implementations of 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.
| Version: |
0.11.0.0 |
| Imports: |
Rcpp (≥ 0.12.9), parallel, methods, visNetwork, glmnet (≥
4.1), grDevices, onehot |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppThread |
| Suggests: |
testthat, knitr, rmarkdown, mvtnorm |
| Published: |
2025-03-13 |
| DOI: |
10.32614/CRAN.package.Rforestry |
| Author: |
Sören Künzel [aut],
Theo Saarinen [aut, cre],
Simon Walter [aut],
Sam Antonyan [aut],
Edward Liu [aut],
Allen Tang [aut],
Jasjeet Sekhon [aut] |
| Maintainer: |
Theo Saarinen <theo_s at berkeley.edu> |
| BugReports: |
https://github.com/forestry-labs/Rforestry/issues |
| License: |
GPL (≥ 3) | file LICENSE |
| URL: |
https://github.com/forestry-labs/Rforestry |
| NeedsCompilation: |
yes |
| Materials: |
README |
| In views: |
MissingData |
| CRAN checks: |
Rforestry results [issues need fixing before 2025-03-27] |