Survey on Various Clustering Techniques in Data Mining
Abstract: Clustering is the run through of grouping the data into classes, so that objects within a cluster are similar to one another but these objects are different to the objects that are in other clusters. Differences and likeness are refereed on the attribute values telling the objects and often involves in measuring distance. This paper provides an review about few clustering methods Partitioning method, hierarchical method, Density based method, Grid based method, and Model based method in data mining.
Keywords: Clustering, Partitioning, Hierarchical, Density Based, Grid based, Model based
How to Cite?: Lavanya.N, N. Deepika, "Survey on Various Clustering Techniques in Data Mining", Volume 5 Issue 12, December 2016, International Journal of Science and Research (IJSR), Pages: 962-966, https://www.ijsr.net/getabstract.php?paperid=ART20163563, DOI: https://dx.doi.org/10.21275/ART20163563