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International Workshop on Multiple Classifier Systems

MCS 2000: Multiple Classifier Systems pp 230–239Cite as

A New Evaluation Method for Expert Combination in Multi-expert System Designing

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1857))

Abstract

In this paper a new evaluation method for expert combination is presented. It takes into account the correlation among experts, their number and their recognition rate. An extended investigation on Majority Vote, Bayesian, Behaviour Knowledge Space and Dempster-Shafer method for abstract-level classifiers is presented. The two-way analysis of variance test and the Scheffè post-hoc comparison have been used to investigate on the factors that influence the recognition rate of the multi-expert system and to collect useful information for the multi-expert system designing.

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Authors and Affiliations

  1. Dipartimento di Informatica, Universitá degli Studi di Bari, Via E. Orabona 4, 70126, Bari, Italy

    S. Impedovo & A. Salzo

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  1. S. Impedovo
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  2. A. Salzo
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© 2000 Springer-Verlag Berlin Heidelberg

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Impedovo, S., Salzo, A. (2000). A New Evaluation Method for Expert Combination in Multi-expert System Designing. In: Multiple Classifier Systems. MCS 2000. Lecture Notes in Computer Science, vol 1857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45014-9_22

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  • DOI: https://doi.org/10.1007/3-540-45014-9_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67704-8

  • Online ISBN: 978-3-540-45014-6

  • eBook Packages: Springer Book Archive

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