Increasing the Number of Classifiers in Multi-classifier Systems: A Complementarity-Based Analysis

Authors:
L. Bovino;Giovanni Dimauro;Sebastiano Impedovo;Giuseppe Pirlo;A. Salzo
Affiliations:
-;-;-;-;-
Venue:
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
Year:
2002

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Abstract

Complementarity among classifiers is a crucial aspect in classifier combination. A combined classifier is significantly superior to the individual classifiers only if they strongly complement each other. In this paper a complementarity-based analysis of sets of classifier is proposed for investigating the behaviour of multi-classifier systems, as new classifiers are added to the set. The experimental results confirm the theoretical evidence and allow the prediction of the performance of a multi-classifier system, as the number of classifiers increases.