KMeans functions through intracluster tightness. Can produce unoptimal
results if a poor seed is chosen. This is due to KMeans getting stuck
in a local minimum. A problem with KMeans is that you need to define
the number of clusters. One way to determine a sutable K, is to
compute the change in intracluster dissimilarity as K increases and
find points in which the change in dissimilarity begins to slow..
Another technique is hierarchical cluster which can be done through
division or agglomeration of clusters for each level of clustering.
-Thomas Hayden
