This research project explores the intuition of building local machine learning models based on data which is a subset of the available domain dataset. The research involves evaluating whether building local models would be more performant than a single model over the entire dataset. The problems include:
- identifying the subsets that would guide model construction
- finding regions of the dataset where the model fails
- identifying metrics for the optimization problem
