This is a simple demonstration of the k-means clustering algorithm.

Select some points, and click submit. An example with its solution is already shown.

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Number of classes:


  • Initialization

    It is initilized by randomly choosing K of the input points and using those as the cluster centers.

  • Termination

    It runs for 20 iterations, or until the labeling does not change. For these demos (small number of points in two dimensions), it often converges in 2-5 iterations.