How slow is the k-means method?
D Arthur, S Vassilvitskii - Proceedings of the twenty-second annual …, 2006 - dl.acm.org
D Arthur, S Vassilvitskii
Proceedings of the twenty-second annual symposium on Computational geometry, 2006•dl.acm.orgThe 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).
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).
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).
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