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.
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