Improved SOSK-Means Automatic Clustering Algorithm with a Three-Part Mutualism Phase and Random Weighted Reflection Coefficient for High-Dimensional Datasets

Automatic clustering problems require clustering algorithms to automatically estimate the number of clusters in a dataset. However, the classical K-means requires the specification of the required number of clusters a priori. To address this problem, metaheuristic algorithms are hybridized with K-me...

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Autors principals:	Abiodun M. Ikotun, Absalom E. Ezugwu
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2022-12-01
Col·lecció:	Applied Sciences
Matèries:	symbiotic organism search K-means clustering algorithms hybrid metaheuristics automatic clustering outliers
Accés en línia:	https://www.mdpi.com/2076-3417/12/24/13019
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