TS-models from evidential clustering

R.J. Almeida; U. Kaymak

doi:10.1007/978-3-642-14055-6_24

TS-models from evidential clustering

R.J. Almeida
, U. Kaymak

Information Systems IE&IS

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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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-2	Engels
Titel	Information 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)
Redacteuren	E. Hüllermeier, R. Kruse, F. Hoffmann
Plaats van productie	Berlin
Uitgeverij	Springer
Pagina's	228-237
ISBN van geprinte versie	978-3-642-14054-9
DOI's	https://doi.org/10.1007/978-3-642-14055-6_24
Status	Gepubliceerd - 2010
Evenement	13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2010) - Dortmund, Duitsland Duur: 28 jun. 2010 → 2 jul. 2010 Congresnummer: 13

Publicatie series

Naam	Communications in Computer and Information Science
Volume	80
ISSN van geprinte versie	1865-0929

Congres

Congres	13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2010)
Verkorte titel	IPMU 2010
Land/Regio	Duitsland
Stad	Dortmund
Periode	28/06/10 → 2/07/10
Ander	International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2010)

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10.1007/978-3-642-14055-6_24

Metis246583Definitieve gepubliceerde versie, 216 KB

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Almeida, R. J., & Kaymak, U. (2010). TS-models from evidential clustering. In E. Hüllermeier, R. Kruse, & F. Hoffmann (editors), Information 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) (blz. 228-237). (Communications in Computer and Information Science; Vol. 80). Springer. https://doi.org/10.1007/978-3-642-14055-6_24

Almeida, R.J. ; Kaymak, U. / TS-models from evidential clustering. Information 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). redacteur / E. Hüllermeier ; R. Kruse ; F. Hoffmann. Berlin : Springer, 2010. blz. 228-237 (Communications in Computer and Information Science).

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Almeida, RJ & Kaymak, U 2010, TS-models from evidential clustering. in E Hüllermeier, R Kruse & F Hoffmann (reds.), Information 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). Communications in Computer and Information Science, vol. 80, Springer, Berlin, blz. 228-237, 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2010), Dortmund, Duitsland, 28/06/10. https://doi.org/10.1007/978-3-642-14055-6_24

TS-models from evidential clustering. / Almeida, R.J.; Kaymak, U.
Information 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). reds. / E. Hüllermeier; R. Kruse; F. Hoffmann. Berlin: Springer, 2010. blz. 228-237 (Communications in Computer and Information Science; Vol. 80).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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AU - Almeida, R.J.

AU - Kaymak, U.

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PY - 2010

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N2 - 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.

AB - 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.

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DO - 10.1007/978-3-642-14055-6_24

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BT - Information 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)

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Almeida RJ, Kaymak U. TS-models from evidential clustering. In Hüllermeier E, Kruse R, Hoffmann F, redacteurs, Information 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). Berlin: Springer. 2010. blz. 228-237. (Communications in Computer and Information Science). doi: 10.1007/978-3-642-14055-6_24

TS-models from evidential clustering

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