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On Hesitant Fuzzy Clustering and Clustering of Hesitant Fuzzy Data

  • Laya AliahmadipourEmail author
  • Vicenç Torra
  • Esfandiar Eslami
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 671)

Abstract

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.

Keywords

Hesitant fuzzy sets Data mining Clustering algorithm Fuzzy clustering 

Notes

Acknowledgements

The first author gratefully acknowledges the support of the Ministry of Science, Research and Technology of the Islamic Republic of Iran and Shahid Bahonar University of Kerman.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Laya Aliahmadipour
    • 1
    Email author
  • Vicenç Torra
    • 2
  • Esfandiar Eslami
    • 1
  1. 1.Faculty of Mathematics and Computer, Department of MathematicsShahid Bahonar University of KermanKermanIran
  2. 2.School of InformaticsSkövde UniversitySkövdeSweden

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