The utility of clusters and a Hungarian clustering algorithm

Implicit in the k –means algorithm is a way to assign value, or utility, cluster of points. It works by taking centroid points and value sum distances from each point cluster. The aim this paper introduce an alternative Motivation provided. Moreover, whereas does not have natural determine if it unknown, we can use our method evaluating find good clusters sequential manner. idea uses optimizations over permutations are set cyclic groups; generated Hungarian algorithm.