Novel approaches to optimized self-configuration in high performance multiple-expert classifiers

Abstract

Classifier combination and the design of multiple expert decision combination strategies are now considered to be very important issues in pattern recognition. This paper describes an investigation covering two important aspects of decision combination: optimization and generality.