On Combining Multiple Classifiers Using an Evidential Approach

Combining multiple classifiers via combining schemes or meta-learners has led to substantial improvements in many classification problems. One of the challenging tasks is to choose appropriate combining schemes and classifiers involved in an ensemble of classifiers. In this paper we propose a novel evidential approach to combining decisions given by multiple classifiers. We develop a novel evidence structure

• Type: Conference
• Year: 2006
• Where: AAAI
• Authors: Yaxin Bi, Sally I. McClean, Terry J. Anderson
• Keywords: AAAI 2006, Appropriate Combining Schemes, Intelligent Agents, Multiple Classifiers, Substantial Improvements