A hybrid machine learning system and its application to insurance underwriting

This paper describes the application of evolutionary learning and classification tree techniques to the insurance underwriting domain. These machine learning techniques are used to build a knowledge base of rules for an expert system which determines when an insurance policy should be terminated. The effectiveness of each method is compared with the other and a hybrid method is proposed, which combines both approaches and seems to overshadow the performance of any other single method.<
>