LightGBM
LightGBM is a gradient boosting framework that uses tree based learning algorithms.
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LightGBM is a gradient boosting framework and is being widely-used in many winning solutions of machine learning competitions. 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.
Official Website Link : https://lightgbm.readthedocs.io/en/latest/
Links
Documentation
Documentation for LightGBM
Using LightGBM with Weights & Biases
Using LightGBM with Weights & Biases
Simple demonstration of LightGBM integration with W&B
A notebook showing easy integration of Weights and Biases with LightGBM,
wandb_callback() callback for metrics logging & log_summary() function to log a feature importance plot and enable model saving to W&B.
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