Popular GitHub Repositories for Gradient Boosting

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

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.

Natural Gradient Boosting for Probabilistic Prediction

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

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

Tuning hyperparams fast with Hyperband

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

Real time eye tracking for embedded and mobile devices.

InfiniteBoost: building infinite ensembles with gradient descent

An experimental Python package that reimplements AutoGBT using LightGBM and Optuna.

Building Decision Trees From Scratch In Python

Easy Custom Losses for Tree Boosters using Pytorch

:star::rocket: Gradient boosting on steroids

Distributional Gradient Boosting Machines

Machine Learning algorithms coded from scratch

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

This repository covers h2o ai based implementations

Nested Cross-Validation for Bayesian Optimized Gradient Boosting

AutoML tools for solving Time-Varying High-Dimensional Ordinal Regression Problems