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Welcome to LightGBM’s documentation!

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 .

    Contents:

  • Installation Guide
  • Quick Start
  • Python Quick Start
  • Features
  • Experiments
  • Parameters
  • Parameters Tuning
  • C API
  • Python API
  • R API
  • Distributed Learning Guide
  • GPU Tutorial
  • Advanced Topics
  • Development Guide
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