K-means properties on six clustering benchmark datasets

This paper has two contributions. First, we introduce a clustering basic benchmark. Second, we study the performance of k-means using this benchmark. Specifically, we measure how the performance depends on four factors: (1) overlap of clusters, (2) number of clusters, (3) dimensionality, and (4) unb...

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Bibliographic Details
Published inApplied intelligence (Dordrecht, Netherlands) Vol. 48; no. 12; pp. 4743 - 4759
Main Authors Fränti, Pasi, Sieranoja, Sami
Format Journal Article
LanguageEnglish
Published New York Springer US 01.12.2018
Springer Nature B.V
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