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Clustering is a technique through which the unlabeled dataset is being grouped based upon the similarity and the characteristics of the data from which a structured output is obtained [4]. The popular algorithms [5] of clustering include

 k-means (partitions the data)

 hierarchial (AGNES—agglomerative nesting)

 Density-based (DBSCAN—Density based spatial clustering with noise)

 Model-based (SOM—self-organizing maps)

 Grid-based (STING—statistical information grid)

 Soft clustering (FCM—Fuzzy Class Membership).