How slow is the k-means method?

  • Authors:
  • David Arthur;Sergei Vassilvitskii

  • Affiliations:
  • Stanford University, Stanford, CA;Stanford University, Stanford, CA

  • Venue:
  • Proceedings of the twenty-second annual symposium on Computational geometry
  • Year:
  • 2006

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Abstract

The k-means method is an old but popular clustering algorithm known for its observed speed and its simplicity. Until recently, however, no meaningful theoretical bounds were known on its running time. In this paper, we demonstrate that the worst-case running time of k-means is superpolynomial by improving the best known lower bound from Ω(n) iterations to 2Ω(√n).