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Survey of Clustering Data Mining Techniques
Macwan Kiran

Published in: International Journal of Scientific Review and Research in Engineering and Technology
Volume- 1, Issue-4, pp.65-73, Jun 2016
DPI :-> 16.10069.IJSRRET.2016.V1I4.6573.1316



Abstract
Clustering is a division of data into groups of similar objects. Representing the data by fewer clusters necessarily loses certain fine details, but achieves simplification. It models data by its clusters. Data modeling puts clustering in a historical perspective rooted in mathematics, statistics, and numerical analysis. From a machine learning perspective clusters correspond to hidden patterns, the search for clusters is unsupervised learning, and the resulting system represents a data concept. From a practical perspective clustering plays an outstanding role in data mining applications such as scientific data exploration, information retrieval and text mining, spatial database applications, Web analysis, CRM, marketing, medical diagnostics, computational biology, and many others.

Key-Words / Index Term
Cluster, CRM

How to cite this article
Macwan Kiran , “Survey of Clustering Data Mining Techniques”, International Journal of Scientific Review and Research in Engineering and Technology, 1, Issue-4, pp.65-73, Jun 2016. DPI:16.10069.IJSRRET.V1.I4.1316