Performance analysis and comparison of linear combiners for classifier fusion

Abstract

In this paper, we report a theoretical and experimental comparison between two widely used combination rules for classifier fusion: simple average and weighted average of classifiers outputs. We analyse the conditions which affect the difference between the performance of simple and weighted averaging and discuss the relation between these conditions and the concept of classifiers’ “imbalance” Experiments aimed at assessing some of the theoretical results for cases where the theoretical assumptions could not be hold are reported.