How much can k-means be improved by using better initialization and repeats?

•K-means clustering algorithm can be significantly improved by using a better initialization technique, and by repeating (re-starting) the algorithm.•When the data has overlapping clusters, k-means can improve the results of the initialization technique.•When the data has well separated clusters, th...

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Veröffentlicht in:	Pattern recognition Jg. 93; S. 95 - 112
Hauptverfasser:	Fränti, Pasi, Sieranoja, Sami
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.09.2019
Schlagworte:	Clustering accuracy Clustering algorithms Initialization K-means Prototype selection K-means Initialization Prototype selection Clustering algorithms Clustering accuracy
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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