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Authors: László Felföld 1 and András Kocsor 2

Affiliations: 1 University of Szeged, Hungary ; 2 Research Group on Artificial Intelligence of the Hungarian Academy of Sciences and University of Szeged, Hungary

Abstract: Classifier combinations are effective techniques for difficult pattern recognition problems such as speech recognition where the combination of differently trained classifiers can produce a more robust phoneme classification on noisy datasets. In this paper we investigate traditional linear combination schemes (e.g. arithmetic mean and least squares methods), and propose a new combiner based on the Analytic Hierarchy Process (AHP), a method frequently applied in mathematical psychology and multi-criteria decision making. In addition, we experimentally compare the applicability of these linear combination schemes using neural network classifiers on a speech recognition framework and two test sets from the UCI repository.

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Paper citation in several formats:
Felföld, L. and Kocsor, A. (2004). AHP-Based Classifier Combination. In Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems (ICEIS 2004) - PRIS; ISBN 972-8865-01-5, SciTePress, pages 45-58. DOI: 10.5220/0002680200450058

@conference{pris04,
author={László Felföld. and András Kocsor.},
title={AHP-Based Classifier Combination},
booktitle={Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems (ICEIS 2004) - PRIS},
year={2004},
pages={45-58},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002680200450058},
isbn={972-8865-01-5},
}

TY - CONF

JO - Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems (ICEIS 2004) - PRIS
TI - AHP-Based Classifier Combination
SN - 972-8865-01-5
AU - Felföld, L.
AU - Kocsor, A.
PY - 2004
SP - 45
EP - 58
DO - 10.5220/0002680200450058
PB - SciTePress