Comparison of fusion algorithms based on logistic model of correlated classifiers

S. Y. Sohn; Y. S. Kim

Comparison of fusion algorithms based on logistic model of correlated classifiers

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This study compares the classification ability of various fusion algorithms (average, majority vote, median, max/min) when individual classifiers are potentially correlated. A logistic transformation of multivariate normal distribution (MVN) is used to generate the posterior probability estimates, assuring that the probability exists between 0 and 1. With varying parameters of MVN and number of classifiers, we measure the relative performance of the fusion algorithms to that of single classifier. Our results can be utilized for the selection of the most effective fusion method for given situation.

Original language	English
Title of host publication	Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004
Editors	P. Svensson, J. Schubert
Pages	569-575
Number of pages	7
Publication status	Published - 2004
Event	Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004 - Stockholm, Sweden Duration: 2004 Jun 28 → 2004 Jul 1

Publication series

Name	Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004
Volume	1

Other

Other	Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004
Country	Sweden
City	Stockholm
Period	04/6/28 → 04/7/1

All Science Journal Classification (ASJC) codes

Engineering(all)

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title = "Comparison of fusion algorithms based on logistic model of correlated classifiers",

abstract = "This study compares the classification ability of various fusion algorithms (average, majority vote, median, max/min) when individual classifiers are potentially correlated. A logistic transformation of multivariate normal distribution (MVN) is used to generate the posterior probability estimates, assuring that the probability exists between 0 and 1. With varying parameters of MVN and number of classifiers, we measure the relative performance of the fusion algorithms to that of single classifier. Our results can be utilized for the selection of the most effective fusion method for given situation.",

author = "Sohn, {S. Y.} and Kim, {Y. S.}",

note = "Copyright: Copyright 2008 Elsevier B.V., All rights reserved.; Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004 ; Conference date: 28-06-2004 Through 01-07-2004",

year = "2004",

language = "English",

isbn = "917056115X",

series = "Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004",

pages = "569--575",

editor = "P. Svensson and J. Schubert",

booktitle = "Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004",

}

Sohn, SY & Kim, YS 2004, Comparison of fusion algorithms based on logistic model of correlated classifiers. in P Svensson & J Schubert (eds), Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004. Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004, vol. 1, pp. 569-575, Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004, Stockholm, Sweden, 04/6/28.

Comparison of fusion algorithms based on logistic model of correlated classifiers. / Sohn, S. Y.; Kim, Y. S.

Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004. ed. / P. Svensson; J. Schubert. 2004. p. 569-575 (Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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