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Comparative Analysis of k-mean Based Algorithms


Parvesh Kumar, Siri Krishan Wasan


Vol. 10  No. 4  pp. 314-318


Clustering is important data mining techniqueto extract useful information from various high dimensional datasets. A wide range of clustering algorithms is available in literature and still an open area for researcher. K-means algorithm is one of the basic and most simple partitioning clustering given byMacQueen in 1967 and aim of this clustering algorithm is to divide the dataset into disjoint clusters. After that many variations of k-means algorithm are given by different authors. Here in this paper we make analysis of k-mean based algorithms namely global k-means, efficient k-means, k-means++ and x-means over leukemia and colon datasets.


Data Mining, Clustering, k-means