Pattern recognition based on hierarchical description of decision rules using choquet integral

Abstract

A hierarchical approach to automatically extract subsets of soft output classifiers, assumed to decision rules, is presented in this paper. Output of classifiers are aggregated into a decision scheme using the Choquet integral. To handle this, two selection schemes are defined, aiming to discard weak or redundant decision rules so that most relevant subsets are restored. For validation, we have used two different datasets: shapes (Sharvit) and graphical symbols (handwritten, CVC - Barcelona). Our experimental study attests the interest of the proposed methods.