Description
Random forest models can be trained quickly in R through an efficient implementation. Data scientists use it for classification, regression, survival forests, and variable importance workflows.
FICHA · AUR
r-ranger
A Fast Implementation of Random Forests
- R random forest library
- LIBRARY
- R
- Dependency only
official+codex · reviewed · Jun 4, 2026 description in
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