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, Flink and DataFlow

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.

ThunderGBM: Fast GBDTs and Random Forests on GPUs

python实现GBDT的回归、二分类以及多分类，将算法流程详情进行展示解读并可视化，庖丁解牛地理解GBDT。Gradient Boosting Decision Trees regression, dichotomy and multi-classification are realized based on python, and the details of algorithm flow are displayed, interpreted and visualized to help readers better understand Gradient Boosting Decision

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).

An end-to-end machine learning and data mining framework on Hadoop

Lightweight Decision Trees Framework supporting Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

This is the official clone for the implementation of the NIPS18 paper Multi-Layered Gradient Boosting Decision Trees (mGBDT) .

A java implementation of LightGBM predicting part

A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)

Show how to perform fast retraining with LightGBM in different business cases

A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms

[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples

A memory efficient GBDT on adaptive distributions. Much faster than LightGBM with higher accuracy. Implicit merge operation.

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

GBDT (Gradient Boosted Decision Tree: 勾配ブースティング) のpythonによる実装

Run XGBoost model and make predictions in Node.js

7th in a competition organised by ICT

Programmable Decision Tree Framework

implement the machine learning algorithms by python for studying

第一届腾讯社交广告高校算法大赛Tencent_2017_contest

Stacked Gradient Boosting Machines

[NeurIPS 2019] H. Chen*, H. Zhang*, S. Si, Y. Li, D. Boning and C.-J. Hsieh, Robustness Verification of Tree-based Models (*equal contribution)

machine learning applied to NLP without deep learning

Extreme Gradient Boosting（binary classification)

A framework of python to do general machie learning using sk-learn, numpy, matplotlib and pandas

My simplest implementations of common ML algorithms