(Notes from: Tan, Steinbach, Kumar + Ghosh)

(C) Vipin Kumar, Parallel Issues in Data Mining, VECPAR 2002 2 K-Means Algorithm • K = # of clusters (given); one “mean” per cluster • Interval data • Initialize means (e.g. by picking k samples at random) • Iterate: (1) assign each point to nearest mean

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