Abstract
Data clustering algorithms divide data into meaningful clusters so that the patterns in the same group are similar in some way, and the patterns in different clusters differ in the same way. The search for clusters involves unsupervised learning, in which it is not known in advance to which group the data belong. The partitioning group attempts to decompose the data into a set of disjoint…