Improved cluster validity index for fuzzy clustering | Zendy

Kwon Soon Hak | Zendy; Kim Jihong | Zendy; Son Seo Ho | Zendy

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Improved cluster validity index for fuzzy clustering

Author(s) -

Kwon Soon Hak,

Kim Jihong,

Son Seo Ho

Publication year - 2021

Publication title -

electronics letters

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.375

H-Index - 146

eISSN - 1350-911X

pISSN - 0013-5194

DOI - 10.1049/ell2.12249

Subject(s) - index (typography) , cluster analysis , cluster (spacecraft) , fuzzy logic , data mining , limiting , fuzzy clustering , mathematics , computer science , statistics , artificial intelligence , engineering , world wide web , programming language , mechanical engineering

An improved cluster validity index for fuzzy clustering that is able to overcome three intrinsic drawbacks in conventional cluster validity indexes is proposed. The effectiveness of the proposed index is demonstrated by the analysis of its limiting behaviour and comparison with the performance of the Xie‐Beni index, Kwon index, and Tang index on twelve data sets.

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