LightGBM

LightGBM (Light Gradient Boosting Machine) is an open-source, high-performance framework for gradient boosting developed by Microsoft. It is designed for speed and efficiency, supporting classification, regression, and ranking tasks on large datasets with both CPU and GPU acceleration.

Features of LightGBM:

• Fast training with optimized histogram-based algorithms.
• Supports classification, regression, ranking, and recommendation.
• Scales efficiently to large datasets with low memory usage.
• GPU and distributed training support for high-performance ML tasks.
• Seamless integration with Python, R, and scikit-learn API.

To check LightGBM version (testing):

$ cd /opt
$ source /opt/lgbm_env/bin/activate
$ python3 -c "import lightgbm; print('LightGBM version:', lightgbm.__version__)"

Disclaimer: LightGBM is an open-source project maintained by Microsoft and the community. It is provided "as is," without any warranty, express or implied. Users are responsible for ensuring compliance with data usage policies, regulations, and licensing terms when deploying LightGBM in production environments.