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Clustering analysis in data mining

Author(s):

Geetha P , KAAMADHENU ARTS AND SCIENCE COLLEGE; Panneerselvan P, KAAMADHENU ARTS AND SCIENCE COLLEGE

Keywords:

Data Mining, Cluster Analysis, Clustering Applications, Requirements, Various Clustering Methods

Abstract

Clustering analysis is a key point used by data processing algorithms in Data Mining. The primary aim of Clustering is to segment the data into more diminutive subsets called clusters, such that the data belonging to the same cluster are similar with some similarity metric. Clustering is imperative idea in data investigation and data mining applications. Over years, K-means has been popular clustering algorithm because of its ease of use and simplicity. This paper presents the introduction to cluster analysis in the field of data mining, where to be the discovery of useful, but non-obvious, information or patterns in large collections of data. Much of this paper is necessarily consumed with providing a general background for cluster analysis, and also discusses a number of clustering techniques that have recently been developed specifically for data mining.

Other Details

Paper ID: IJSRDV3I70331
Published in: Volume : 3, Issue : 7
Publication Date: 01/10/2015
Page(s): 766-768

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