Glossary

Understanding LightGBM Gradient boosting Framework

Written by Dr. Jagreet Kaur Gill | 08 Feb 2023

Comparing Lightgbm with other Frameworks

In a comparison of other boosting related framework, it has the following advantages -

  • Training speed faster without compromising efficiency.
  • The memory usage is also low.
  • It provides better accuracy.
  • It supports two types of learning parallel and GPU.
  • It has the capability of handling large scale data.

Best Uses of Lightgbm Framework

It is recommended to use Lightgbm with small datasets because it is considered to be prone to overfitting, which can easily overfit on small datasets also.