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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Published in | Applied intelligence (Dordrecht, Netherlands) Vol. 48; no. 12; pp. 4743 - 4759 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York
Springer US
01.12.2018
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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