suiji/Arborist

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

A lightweight gradient boosted decision tree package.

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

Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Advanced Machine Learning and Visualization

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Universal model exchange and serialization format for decision tree forests