LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed and efficient with the following advantages:
- Faster training speed and higher efficiency.
- Lower memory usage.
- Better accuracy.
- Support of parallel, distributed, and GPU learning.
- Capable of handling large-scale data.
For more details, please refer to Features.
Installation Guide <Installation-Guide> Quick Start <Quick-Start> Python Quick Start <Python-Intro> Features <Features> Experiments <Experiments> Parameters <Parameters> Parameters Tuning <Parameters-Tuning> C API <C-API> Python API <Python-API> R API <https://lightgbm.readthedocs.io/en/latest/R/reference/> Distributed Learning Guide <Parallel-Learning-Guide> GPU Tutorial <GPU-Tutorial> Advanced Topics <Advanced-Topics> FAQ <FAQ> Development Guide <Development-Guide>
GPU-Performance GPU-Targets GPU-Windows gcc-Tips README
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