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CRAN: Package Rforestry

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

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: 0.11.1.0 Imports: Rcpp (≥ 0.12.9), parallel, methods, visNetwork, glmnet (≥ 4.1), grDevices, onehot LinkingTo: Rcpp, RcppArmadillo, RcppThread Suggests: testthat, knitr, rmarkdown, mvtnorm Published: 2025-03-15 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 Documentation: Downloads: Linking:

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