Comparative Studies of Various Clustering Techniques and Its Characteristics
Journal: International Journal of Advanced Networking and Applications (Vol.5, No. 06)Publication Date: 2014-05-05
Authors : M.Sathya Deepa; Dr.N.Sujatha;
Page : 2104-2116
Keywords : Clustering; Density-Based; Fuzzy; Grid-Based; Hierarchical; K-Means; Partitioning; STING; Wavelet;
Abstract
Discovering knowledge from the mass database is the main objective of the Data Mining. Clustering is the key technique in data mining. A cluster is made up of a number of similar objects grouped together. The clustering is an unsupervised learning. There are many methods to form clusters. The four important methods of clustering are Partitional Clustering, Hierarchical Clustering, Density-Based Clustering and Grid-Based Clustering. In this paper, we discussed these four methods in detail.
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