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Top 6 C++ gradient-boosting Projects
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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.
Project mention: 《LightGBM: 一种高效的梯度提升决策树算法》论文(A Highly Efficient Gradient Boosting Decision Tree) | dev.to | 2025-10-15代码:https://github.com/microsoft/LightGBM
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Stream
Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.
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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.
Project mention: 🚀 Why Your ML Service Needs Rust + CatBoost: A Setup Guide That Actually Works | dev.to | 2025-01-19[package] name = "MLApp" version = "0.1.0" edition = "2021" [dependencies] catboost = { git = "https://github.com/catboost/catboost", rev = "0bfdc35"}
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yggdrasil-decision-forests
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
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C++ gradient-boosting discussion
C++ gradient-boosting related posts
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Conselhos para embedded
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[D] Alternatives to the shap explainability package
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[N] Google confirms DeepMind Health Streams project has been killed off
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[Discussion] XGBoost is the way.
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[D] Generalized Additive Models… with trees?
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Machine Learning with Medical Data (unbalanced dataset)
- A note from our sponsor - SaaSHub www.saashub.com | 25 Dec 2025
Index
What are some of the best open-source gradient-boosting projects in C++? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | LightGBM | 17,946 |
| 2 | catboost | 8,719 |
| 3 | interpret | 6,744 |
| 4 | yggdrasil-decision-forests | 623 |
| 5 | fairgbm | 106 |
| 6 | decision-tree-classifier | 3 |