Clustering is the technique which used to group data from a set of unlabeled data, in a way that data containing similar properties contains in a same group. There are many cluster techniques are used to cluster data thus there is no suitable definition for cluster is available. Techniques like link based clustering, centroid based clustering, distribution based clustering, density based clustering are used. A survey over centroid based K-mean clustering techniques is presented which is widely used for clustering purpose. K-mean clustering technique suffers drawbacks like sensitive to initialization centroid, sensitive to noise, and there is no. of clusters also not defined. Thus an enhanced k-mean technique is presented to reduce such drawbacks and provide an enhanced functionality for clustering.

K-Means, Clustering, Centroid, Centroid based clustering, partition based clustering, point based, convex, euclidian

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