The global k-means clustering algorithm

Abstract : We present the global k-means algorithm which is an incremental approach to clustering that dynamically adds one cluster at a time through a deterministic global search procedure consisting of N (with N being the size of the data set) executions of the k-means algorithm from suitable initial positions. We also propose modifications of the methods to reduce the computational load without significantly affecting solution quality. The proposed clustering methods are tested on well-known data sets and they compare favorably to the k-means algorithm with random restarts.
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https://hal.inria.fr/inria-00321515
Contributor : Jakob Verbeek <>
Submitted on : Wednesday, February 16, 2011 - 5:03:46 PM
Last modification on : Monday, September 25, 2017 - 10:08:04 AM
Long-term archiving on : Tuesday, May 17, 2011 - 2:38:06 AM

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Aristidis Likas, Nikos Vlassis, Jakob Verbeek. The global k-means clustering algorithm. [Technical Report] IAS-UVA-01-02, 2001, pp.12. ⟨inria-00321515⟩

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