Fuzzy clustering based on \(K\)-nearest-neighbours rule

DOI10.1016/S0165-0114(99)00074-3zbMath0981.62057OpenAlexW1599350031MaRDI QIDQ5937026

Abderrahman Essaid, O. Abouelala, Mohammed Limouri, Nour-Eddine Zahid

Publication date: 26 March 2002

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0165-0114(99)00074-3

zbMATH Keywords

fuzzy setspattern recognitioncluster analysisfuzzy c-means algorithmk-nearest-neighbours decision rule

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Pattern recognition, speech recognition (68T10)

Related Items (5)

Approaches to the representations and logic operations of fuzzy concepts in the framework of axiomatic fuzzy set theory. II. ⋮ Categorical data fuzzy clustering: an analysis of local search heuristics ⋮ A new unsupervised approach for fuzzy clustering ⋮ A robust algorithm for solution of the fuzzy clustering problem on the basis of the fuzzy joint points method ⋮ Robustness of density-based clustering methods with various neighborhood relations

Cites Work

• Fuzzy partitions and relations; an axiomatic basis for clustering
• A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
• Fuzzy sets
• A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters

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