Review of clustering techniques

Abstract

Clustering is the procedure of consortium a set of entities in such a manner those similar entities should in the same group. Cluster analysis is not one specific approach, but the general process to be observed. Clustering can be viewed by different algorithms that differ independently, in their view what is meant by a cluster and how to find them perfectly. Popular notions of clusters include groups with minimum distances among the cluster members. The clustering problem has been discussed by researchers in different things with respective domain. It reveals broad scope of clustering and it is very important in the process of data analysis as one step. However, it is very difficult because of the researchers may assume in different contexts. Clustering is one of best approach of data mining and a common methodology for statistical data analysis. It is used in all major domains like Banking, Health care, Robotics, and other disciplines. This paper mainly aims to discuss about limitations, scope, and purpose of different clustering algorithms in a great detail.