A possibilistic fuzzy Gath-Geva clustering algorithm using the exponential distance

[Display omitted] •Propose PFGG clustering algorithm.•PFGG uses the exponential distance in contrast to PFCM.•PFGG clusters the dataset containing noisy data accurately.•The clustering accuracies, cluster centers and convergence results of PFGG are significantly better than FCM, GG, PFCM. As a famou...

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Vydané v:	Expert systems with applications Ročník 184; s. 115550
Hlavní autori:	Wu, Xiaohong, Zhou, Haoxiang, Wu, Bin, Zhang, Tingfei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Elsevier Ltd 01.12.2021 Elsevier BV
Predmet:	Algorithms Clustering Covariance matrix Euclidean geometry GG clustering Hyperellipsoidal data Noise data Noise sensitivity PFCM clustering PFGG clustering PFCM clustering PFGG clustering Hyperellipsoidal data GG clustering Noise data
ISSN:	0957-4174, 1873-6793
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