TS-models from evidential clustering

R.J. Almeida, U. Kaymak

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Samenvatting

We study how to derive a fuzzy rule-based classification model using the theoretical framework of belief functions. For this purpose we use the recently proposed Evidential c-means (ECM) to derive Takagi-Sugeno (TS) models solely from data. ECM allocates, for each object, a mass of belief to any subsets of possible clusters, which allows to gain a deeper insight in the data while being robust with respect to outliers. Some classification examples are discussed, which show the advantages and disadvantages of the proposed algorithm.
Originele taal-2Engels
TitelInformation Processing and Management of Uncertainty in Knowledge-Based Systems : Theory and Methods (13th International Conference, IPMU 2010 Dortmund, Germany, June 28- July 2, 2010, Proceedings, Part I)
RedacteurenE. Hüllermeier, R. Kruse, F. Hoffmann
Plaats van productieBerlin
UitgeverijSpringer
Pagina's228-237
ISBN van geprinte versie978-3-642-14054-9
DOI's
StatusGepubliceerd - 2010
Evenement13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2010) - Dortmund, Duitsland
Duur: 28 jun 20102 jul 2010
Congresnummer: 13

Publicatie series

NaamCommunications in Computer and Information Science
Volume80
ISSN van geprinte versie1865-0929

Congres

Congres13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2010)
Verkorte titelIPMU 2010
Land/RegioDuitsland
StadDortmund
Periode28/06/102/07/10
AnderInternational Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2010)

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