bethatkinson/rpart

Scalable decision tree training and inference.

caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models

Bayesian additive regression trees (BART) for regression, classification, uncertainty quantification, and variable selection in R, with optional GPU acceleration.

an R package for deriving Prediction Rule Ensembles

Official implementation of MetaTree: Learning a Decision Tree Algorithm with Transformers

User-Friendly R Package for Supervised Machine Learning Pipelines

Advanced Machine Learning and Visualization

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

Graphical analysis of random forests with the randomForestSRC, randomForest, varPro and ggplot2 packages.