On Hesitant Fuzzy Clustering and Clustering of Hesitant Fuzzy Data
2017 (English)In: Fuzzy sets, rough sets, multisets and clustering: Part I / [ed] Vicenç Torra, Anders Dahlbom & Yasuo Narukawa, Springer, 2017, 157-168 p.Chapter in book (Refereed)
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.
Place, publisher, year, edition, pages
Springer, 2017. 157-168 p.
Studies in Computational Intelligence, ISSN 1860-949X ; 671
Hesitant fuzzy sets, Data mining, Clustering algorithm, Fuzzy clustering
IdentifiersURN: urn:nbn:se:his:diva-13363DOI: 10.1007/978-3-319-47557-8_10ScopusID: 2-s2.0-85009957968ISBN: 978-3-319-47556-1 (print)ISBN: 978-3-319-47557-8 (electronic)OAI: oai:DiVA.org:his-13363DiVA: diva2:1071381