A THEORETICAL ANALYSIS ON CLUSTERING CONCEPTS IN DATA MINING

Clustering mechanism is the unsupervised classification of patterns observations data items or feature vectors into different clusters. This type of clustering problem has been addressed in many contexts and by researchers in different domains, this makes us to understand its broad appeal and usefulness as one of the steps analyzing the whole data. As we all know that there will be huge assumptions in solving the clustering problems which makes it very complex and the clustering process became very slow. Here in this paper we are concentrating on overview of pattern clustering methods from a statistical pattern recognition perspective with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners. We also presents the study of different clustering algorithms as well as the current development in these mechanisms