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The K-Means algorithm terminates when the number of clusters formed for the current iteration is identical to the number of clusters formed in the previous

The K-Means algorithm terminates when

the number of clusters formed for the current iteration is identical to the number of clusters formed in the previous iteration.

the cluster centers for the current iteration are identical to the cluster centers for the previous iteration.

a user-defined minimum value for the summation of squared error differences between instances and their corresponding cluster center is seen.

the number of instances in each cluster for the current iteration is identical to the number of instances in each cluster of the previous iteration.

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