This session will focus on how machine learning, and specifically a form of rule induction, can be used to enhance both the process of generalized linear modeling and the resulting models. The emphasis of this session will be on the complementary aspects of having “two tools in the toolbox” when building models. Attention will be given not only to how the use of rule induction changes the signal that can be found, but also to how it changes the context in which the modeling occurs. Case study examples will be shown.

Moderator/Panelist:
Christopher L. Cooksey, Senior Actuarial Consultant, EagleEye Analytics