Clustering techniques in data mining: A comparison

Clustering is a technique in which a given data set is divided into groups called clusters in such a manner that the data points that are similar lie together in one cluster. Clustering plays an important role in the field of data mining due to the large amount of data sets. This paper reviews the various clustering algorithms available for data mining and provides a comparative analysis of the various clustering algorithms like DBSCAN, CLARA, CURE, CLARANS, K-Means etc.