YARF—Yet Another Random Forests package—is a customizable, asynchronous, and parallelized random-forest implementation for R. It supports custom JavaScript splitting and aggregation behavior, missingness incorporated in attributes, and random-forest-based imputation.
Highlights
- Classification and regression forests with out-of-bag diagnostics
- Custom JavaScript split rules and aggregation functions
- Missingness incorporated in attributes (MIA)
- Random-forest-based missing-value imputation
- Asynchronous and parallel tree construction
- Variable-importance, interaction, proximity, and tree-inspection tools
Installation
YARF is distributed through the kapelner R-universe, not CRAN:
install.packages(
"YARF",
repos = c(
kapelner = "https://kapelner.r-universe.dev",
CRAN = "https://cloud.r-project.org"
)
)Java 8 or newer is required.
Quick start
library(YARF)
fit <- YARF(
X = iris[, 1:4],
y = iris$Species,
num_trees = 100
)
predict(fit, iris[, 1:4])See the package website for the getting-started guide and reference, and the R-universe package page for builds and binaries.
