A Unified Form of Fuzzy C-Means and K-Means algorithms and its Partitional Implementation

This paper proposes as an element of novelty the Unified Form (UF) clustering algorithm, which treats Fuzzy C-Means (FCM) and K-Means (KM) algorithms as a single configurable algorithm. UF algorithm was designed to facilitate the FCM and KM algorithms software implementation by offering a solution t...

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Vydané v:	Knowledge-based systems Ročník 214; s. 106731
Hlavní autori:	Borlea, Ioan-Daniel, Precup, Radu-Emil, Borlea, Alexandra-Bianca, Iercan, Daniel
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 28.02.2021 Elsevier Science Ltd
Predmet:	Algorithms Clustering Data processing Datasets Distributed platforms Fuzzy C-means algorithm Implementation Indexes K-means algorithm Memory Partitional Implementation Performance indices Unified form of Fuzzy C-Means algorithms and K-Means algorithms K-means algorithm Partitional Implementation Fuzzy C-means algorithm Distributed platforms Unified form of Fuzzy C-Means algorithms and K-Means algorithms
ISSN:	0950-7051, 1872-7409
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