How slow is the k-means method?

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) . Categories and Subject Descriptors: F.2.2 [Analysis of Algorithms and Problem Complexity]: Nonnumerical Algorithms and Problems General Terms: Algorithms, Theory.

• Type: Conference
• Year: 2006
• Where: COMPGEOM
• Authors: David Arthur, Sergei Vassilvitskii
• Keywords: COMPGEOM 2006, Meaningful Theoretical Bounds, Popular Clustering Algorithm, Running Time