(in quantifying building energy efficiency savings)
Testing predictive models and quantifying their errors on datasets beyond the training dataset is a well-known practice in data-heavy domains. Here, I demonstrate its importance in the energy efficiency industry where model accuracy directly impacts project incentive payments and influences customer behavior, nudging them to opt-in or out of the energy efficiency programs.
