“…Choosing K too big or too small would either smooth out the important features in the data or make its structure appear too noisy. The effect of K was not found to be crucial to the performance of the clustering procedure for a many-cluster model with noise [Wiseman et al, 1998], however, the size of the neighborhood considered in that paper did not vary considerably (K ¼ 6, 12, 14, 18, and the Voronoi cell structure were studied), the contrast to noise ratio of the image, though not specified, appeared to be reasonably high, and the performance of the algorithm was measured in terms of accuracy, a measure that is less conservative than the adjusted Rand index.…”