LightGBM
Fast gradient boosting framework by Microsoft using histogram-based algorithms.
About
LightGBM by Microsoft is a gradient boosting framework that trains decision-tree ensembles using histogram-based algorithms for speed and low memory use. It handles large tabular datasets, supports categorical features natively, offers leaf-wise tree growth, and runs on CPU, GPU, and distributed setups with Python, R, and C++ interfaces. It is a common choice for ranking, classification, and regression. Released under the MIT license.
Reviews (0)
Leave a Review
No reviews yet. Be the first to review!
Details
- Category
- AI Frameworks & Libraries
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Easy (2/5)
- License
- MIT
- Added
- Apr 3, 2026
Related Tools
Tensor library for machine learning on commodity hardware
Structured output extraction from LLMs with Pydantic
Deploy LangChain runnables as REST APIs
Unified system for large-scale distributed training and inference.
High-level deep learning library making neural nets accessible with best practices.
Open-source machine learning framework by Meta with dynamic computation graphs.