Gradient Boosting Python Packages

lightgbm

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.

shap

A game theoretic approach to explain the output of any machine learning model.

catboost

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.

interpret-core

Fit interpretable models. Explain blackbox machine learning.

tensorflow-decision-forests

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

interpret

Fit interpretable models. Explain blackbox machine learning.

ydf

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

aplr

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering smoother and interpretable predictions.

ngboost

Natural Gradient Boosting for Probabilistic Prediction

catboost-dev

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.

lleaves

Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

arboreto

A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.

mlrl-common

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

mlrl-boomer

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

rfgboost

RFGBoost: Gradient Boosting with Asynchronous Random Forests

torchensemble

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

mlrl-seco

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

treeplot

Plot tree based machine learning models

auto-ml

[UNMAINTAINED] Automated machine learning for analytics & production

mqboost

[Mach. Learn. 2026] Official implementation of "Monotone Composite Quantile Regression via Second-Order Gradient Boosting Framework"

fairgbm

Train Gradient Boosting models that are both high-performance *and* Fair!

ydf-tf

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

xbooster

Explainable Boosted Scoring with Python: turning XGBoost, LightGBM, and CatBoost into explainable scorecards