After deploying a classifier in production it is essential to support its lifecycle. This paper describes the application of an ensemble of classifiers to support two stages of the lifecycle of an on-line classifier used to underwrite life insurance applications: the monitoring of its decisions quality and the updating of the production classifier over time. All combinations of five classification methods and seven fusion methods were assessed from the perspective of accuracy and pairwise diversity of the classifiers, and accuracy, precision, and coverage of the fused classifiers. The proposed architecture consists of three offline classifiers and a fusion module.
Piero P. Bonissone, Neil Eklund, Kai Goebel