Clustering refers to algorithms to uncover clusters in unlabeled data. Data points belonging to the same cluster exhibit similar features, whereas data points from different clusters are dissimilar to each other. The identification of such clusters leads to segmentation of data points into a number of distinct groups. Since groups are identified from the data itself, as opposed to classification, clustering is considered as unsupervised learning.