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In data mining functionalities, clustering analysis is the most significant tool for distribution of data. Clustering is dynamic field of research in data mining concept. It is related to unsupervised learning in machine learning. On the basis of similarity measures cluster formation process is initiated. With the help of different notations used in clustering algorithms unique clusters are formed with the same data set. In this paper several clustering methods are discussed with their particular algorithms. Clustering methods are drastically affecting the shapes of cluster, quality of cluster, scalability of clusters.
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