Data points are assigned to clusters using a clustering criterion. In
distance clustering, abbreviated d–clustering, the clustering criterion is metric:
With each cluster Ck we associate a center ck, for example its centroid,
and each data point is assigned to the cluster to whose center it is the nearest.
After each such assignment, the cluster centers may change, resulting in
Probabilistic D-Clustering