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Cluster is a gathering of items that belongs with a similar class. At the end of the day, comparative articles are assembled in one cluster and different objects are gathered in another cluster. clustering is the way toward making a group of conceptual articles into classes of comparable items. Clustering analysis is comprehensively utilized as a part of numerous applications, for example, statistical surveying, design acknowledgment, information investigation, and picture handling. Clustering can likewise help advertisers find particular gatherings in their client base. Also, they can portray their client bunches in view of the buying designs. Clustering is a popular strategy for implementing parallel processing applications because it enables companies to leverage the investment already made in PCs and workstations. In addition, it's relatively easy to add new CPUs simply by adding a new PC to the network. In this paper we study k-mode clustering and implementing those for date classification.