Physical Sciences and Mathematics Commons^™

Logistic Ensemble Models, Bob Vanderheyden, Jennifer L. Priestley

Jennifer L. Priestley

Predictive models that are developed in a regulated industry or a regulated application, like determination of credit worthiness must be interpretable and “rational” (e.g., improvements in basic credit behavior must result in improved credit worthiness scores). Machine Learning technologies provide very good performance with minimal analyst intervention, so they are well suited to a high volume analytic environment but the majority are “black box” tools that provide very limited insight or interpretability into key drivers of model performance or predicted model output values. This paper presents a methodology that blends one of the most popular predictive statistical modeling methods with …