Question

Which of the following can act as possible termination conditions in K-Means?

For a fixed number of iterations.

The assignment of observations to clusters does not change between iterations, except for cases with a bad local minimum.

Centroids do not change between successive iterations.

Terminate when RSS falls below a threshold.

Options:

A. 1, 3 and 4

B. 1, 2 and 3

C. 1, 2 and 4

D. All of the above

Answer 1

Answer: (D)

All four conditions can be used as possible termination conditions in K-Means clustering:

This condition limits the runtime of the clustering algorithm, but in some cases, the quality of the clustering will be poor because of an insufficient number of iterations.

Except for cases with a bad local minimum, this produces a good clustering, but runtimes may be unacceptably long.

This also ensures that the algorithm has converged at the minima.

Terminate when RSS falls below a threshold. This criterion ensures that the clustering is of the desired quality after termination. Practically, combining it with a bound on the number of iterations to guarantee termination is a good practice.