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Authors: Olfa Limam 1 and Fouad Ben Abdelaziz 2

Affiliations: 1 University of Tunis, Tunisia ; 2 American University of Sharjah, United Arab Emirates

ISBN: 978-989-8425-32-4

Keyword(s): Bayesian validation, Fuzzy set, Fuzzy clustering methods.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Fuzzy Systems ; Pattern Recognition: Fuzzy Clustering and Classifiers ; Soft Computing

Abstract: Clustering analysis has been used for identifying similar objects and discovering distribution of patterns in large data sets. While hard clustering assigns an object to only one cluster, fuzzy clustering assigns one object to multiple clusters at the same time based on their degrees of membership. An important issue in clustering analysis is the validation of fuzzy partitions. In this paper, we consider the Bayesian like validation along with four conventional validity measures for two clustering algorithms namely, fuzzy c-means and fuzzy c-shell based. An empirical study is conducted on five data sets to compare their performances. Results show that the Bayesian validation score outperforms the conventional ones. However, a multiple objective approach is needed.

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Paper citation in several formats:
Limam, O. and Ben Abdelaziz, F. (2010). CONVENTIONAL AND BAYESIAN VALIDATION FOR FUZZY CLUSTERING ANALYSIS.In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 135-140. DOI: 10.5220/0003110201350140

@conference{icfc10,
author={Olfa Limam. and Fouad Ben Abdelaziz.},
title={CONVENTIONAL AND BAYESIAN VALIDATION FOR FUZZY CLUSTERING ANALYSIS},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010)},
year={2010},
pages={135-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003110201350140},
isbn={978-989-8425-32-4},
}

TY - CONF

JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010)
TI - CONVENTIONAL AND BAYESIAN VALIDATION FOR FUZZY CLUSTERING ANALYSIS
SN - 978-989-8425-32-4
AU - Limam, O.
AU - Ben Abdelaziz, F.
PY - 2010
SP - 135
EP - 140
DO - 10.5220/0003110201350140

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