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 an HuberRegressor as a potential best fit model.
Add HuberRegressor model into the library.
Primary File to Change: https://github.com/blobcity/autoai/blob/main/blobcity/config/regressor_config.py
Reference HuberRegressor Implementation: https://github.com/blobcity/ai-seed/blob/main/Regression/Linear%20Models/HuberRegressor.ipynb
Official API Reference for Parameter: https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.HuberRegressor.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 an HuberRegressor as a potential best fit model.