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On Hesitant Fuzzy Clustering and Clustering of Hesitant Fuzzy Data
Faculty of Mathematics and Computer, Department of Mathematics, Shahid Bahonar University of Kerman, Kerman, Iran.
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0002-0368-8037
Faculty of Mathematics and Computer, Department of Mathematics, Shahid Bahonar University of Kerman, Kerman, Iran.
2017 (engelsk)Inngår i: Fuzzy sets, rough sets, multisets and clustering: Part I / [ed] Vicenç Torra, Anders Dahlbom & Yasuo Narukawa, Springer, 2017, s. 157-168Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

Since the notion of hesitant fuzzy set was introduced, some clustering algorithms have been proposed to cluster hesitant fuzzy data. Beside of hesitation in data, there is some hesitation in the clustering (classification) of a crisp data set. This hesitation may be arise in the selection process of a suitable clustering (classification) algorithm and initial parametrization of a clustering (classification) algorithm. Hesitant fuzzy set theory is a suitable tool to deal with this kind of problems. In this study, we introduce two different points of view to apply hesitant fuzzy sets in the data mining tasks, specially in the clustering algorithms.

sted, utgiver, år, opplag, sider
Springer, 2017. s. 157-168
Serie
Studies in Computational Intelligence, ISSN 1860-949X ; 671
Emneord [en]
Hesitant fuzzy sets, Data mining, Clustering algorithm, Fuzzy clustering
HSV kategori
Forskningsprogram
Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science
Identifikatorer
URN: urn:nbn:se:his:diva-13363DOI: 10.1007/978-3-319-47557-8_10ISI: 000413720000011Scopus ID: 2-s2.0-85009957968ISBN: 978-3-319-47556-1 (tryckt)ISBN: 978-3-319-47557-8 (digital)OAI: oai:DiVA.org:his-13363DiVA, id: diva2:1071381
Tilgjengelig fra: 2017-02-04 Laget: 2017-02-04 Sist oppdatert: 2018-06-11bibliografisk kontrollert

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