Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
Dependencies if any, must be appropriately added. Test run of the train function on a regression problem must pass, and the function must attempt to train a LightGBMRegressor as a potential best fit model.
Add LightGBMRegressor model into the library.
Primary File to Change: https://github.com/blobcity/autoai/blob/main/blobcity/config/regressor_config.py
Reference LightGBMRegressor Implementation: https://github.com/blobcity/ai-seed/blob/main/Regression/LightGBM/LGBMRegressor.ipynb
Also Refer offical documentation to select appropriate parameters: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html
Dependencies if any, must be appropriately added. Test run of the train function on a regression problem must pass, and the function must attempt to train a LightGBMRegressor as a potential best fit model.