Description: Machine learning algorithms fit models based on patterns identified in data and can be very complex. In this report, we describe and illustrate a range of methods for interpreting machine learning models from the growing field of Interpretable Machine Learning (IML).

Description: In this Society of Actuaries (SOA) Research Institute report, authored by consultants from Milliman, Inc. (Milliman) we aim to study the effects of hurricanes on human health: whether there is a relationship between hurricanes and the observed prevalence of healthcare utilization or certain health conditions among the affected population, whether this relationship can be observed through a healthcare utilization dataset, and whether there is an interaction between this observation and metrics of socioeconomic vulnerability.