jinlow/forust

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

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

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.

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.

(ICLR 2024) GRANDE: Gradient-Based Decision Tree Ensembles

Scalable decision tree training and inference.

High performance gradient boosting for Ruby

XGBoost Julia Package

LinearBoost Classifier is a rapid and accurate classification algorithm that builds upon a very fast, linear classifier.