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On the selection of m for Fuzzy c-Means
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0002-0368-8037
2015 (engelsk)Inngår i: Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology / [ed] José M. Alonso, Humberto Bustince & Marek Reformat, Paris: Atlantis Press , 2015, s. 1571-1577Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Fuzzy c-means is a well known fuzzy clustering algorithm. It is an unsupervised clustering algorithmthat permits us to build a fuzzy partition from data. The algorithm depends on a parameter m whichcorresponds to the degree of fuzziness of the solution. Large values of m will blur the classes andall elements tend to belong to all clusters. The solutionsof the optimization problem depend on theparameter m. That is, different selections of m willtypically lead to different partitions. In this paper we study and compare the effect ofthe selection of m obtained from the fuzzy c-means.

sted, utgiver, år, opplag, sider
Paris: Atlantis Press , 2015. s. 1571-1577
Serie
Advances in Intelligent Systems Research, ISSN 1951-6851 ; 89
HSV kategori
Forskningsprogram
Skövde Artificial Intelligence Lab (SAIL)
Identifikatorer
URN: urn:nbn:se:his:diva-11632DOI: 10.2991/ifsa-eusflat-15.2015.224ISI: 000358581100223ISBN: 978-94-62520-77-6 (tryckt)OAI: oai:DiVA.org:his-11632DiVA, id: diva2:865640
Konferanse
16th World Congress of the International Fuzzy Systems Association (IFSA) / 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), Gijon, Spain, June 30-July 3, 2015
Merknad

Conference general chair: Luis Magdalena Layos

Tilgjengelig fra: 2015-10-28 Laget: 2015-10-28 Sist oppdatert: 2018-03-28bibliografisk kontrollert

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