Iteration History

The iteration history shows the progress of the clustering process at each step. In early iterations, the cluster centers shift quite a lot. By the 14th iteration, they have settled down to the general area of their final location, and the last four iterations are minor adjustments.

If the algorithm stops because the maximum number of iterations is reached, you may want to increase the maximum because the solution may otherwise be unstable. For example, if you had left the maximum number of iterations at 10, the reported solution would still be in a state of flux.

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