Clustering large datasets by merging \(K\)-means solutions

DOI10.1007/s00357-019-09314-8OpenAlexW2931031718WikidataQ128202764 ScholiaQ128202764MaRDI QIDQ779014

Volodymyr Melnykov, Semhar Michael

Publication date: 21 July 2020

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00357-019-09314-8

zbMATH Keywords

finite mixture models\(K\)-meansclassification EM algorithmmerging componentspairwise overlap

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

A Novel Neural Model With Lateral Interaction for Learning Tasks

Uses Software

• mclust
• mixsmsn
• flowMerge

Cites Work

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• Partitional Clustering Algorithms

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