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.

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

interpret

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.

ydf

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

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.

mojolearn

GPU machine learning in Mojo that supports bitwise identical inference and training on Apple Metal, NVIDIA CUDA and AMD HIP.

ydf-tf

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

hessboost

Fast, deterministic gradient boosting in Rust (with Python bindings)

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

prismboost

PrismBoost: gradient boosting with SEFR oblique splits for classification and regression

mlrl-seco

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

mojolearn-nvidia

GPU machine learning in Mojo that supports bitwise identical inference and training on Apple Metal, NVIDIA CUDA and AMD HIP.

arboreto

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

mojolearn-amd

GPU machine learning in Mojo that supports bitwise identical inference and training on Apple Metal, NVIDIA CUDA and AMD HIP.

xbooster

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

auto-ml

[UNMAINTAINED] Automated machine learning for analytics & production