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Data clustering using a modified fuzzy min-max neural network

Seera, Manjeevan, Lim, Chee Peng, Loo, Chu Kiong and Jain, Lakhmi C. 2016, Data clustering using a modified fuzzy min-max neural network, in SOFA 2014 : Proceedings of the 6th International Workshop on Soft Computing Applications, Springer International Publishing, Cham, Switzerland, pp. 413-422, doi: 10.1007/978-3-319-18296-4_34.

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Title Data clustering using a modified fuzzy min-max neural network
Author(s) Seera, Manjeevan
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Loo, Chu Kiong
Jain, Lakhmi C.
Conference name Soft Computing Applications. International Workshop (6th : 2014 : Timisoara, Romania)
Conference location Timisoara, Romania
Conference dates 24-26 Jul. 2014
Title of proceedings SOFA 2014 : Proceedings of the 6th International Workshop on Soft Computing Applications
Editor(s) Kacprzyk, J.
Publication date 2016
Series Advances in intelligent systems and computing
Conference series Soft Computing Applications International Workshop
Start page 413
End page 422
Total pages 10
Publisher Springer International Publishing
Place of publication Cham, Switzerland
Keyword(s) data clustering
fuzzy man-mix neural network
hyperbox centroid
cophenetic correlation coefficient
Summary In this paper, a modified fuzzy min-max (FMM) clustering neural network is developed. Specifically, a centroid computation procedure in embedded into the FMM clustering network to establish the cluster centroid of each hyperbox in the FMM structure. Based on the hyperbox centroids, the FMM clustering performance in undertaking data clustering problems is measured using the cophenetic correlation coefficient (CCC). A series of experimental studies using benchmark datasets is conducted. The CCC scores obtained are compared with those from other clustering algorithms reported in the literature. The empirical findings indicate the effectiveness of FMM with the centroid formation procedure for tackling data clustering tasks.
ISBN 9783319182957
ISSN 2194-5357
Language eng
DOI 10.1007/978-3-319-18296-4_34
Field of Research 099999 Engineering not elsewhere classified
Socio Economic Objective 970110 Expanding Knowledge in Technology
HERDC Research category E2 Full written paper - non-refereed / Abstract reviewed
ERA Research output type E Conference publication
Copyright notice ©2016, Springer International Publishing
Persistent URL http://hdl.handle.net/10536/DRO/DU:30087682

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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