Suppose the k-means algorithm is run for an increasing sequence of values for k, and that it is run for a number of times for each k to find the assignment with a global minimum error. Is it possible that a number of values of k exist for which the error plateaus and then has a large improvement (e.g., when the errors for k = 3, k = 4, and k = 5 are about the same, but the error for k = 6 is much lower)? If so, give an example. If not, explain why.