Improved k- means clustering algorithm for two dimensional data

Authors:
Rupali Vij;Suresh Kumar
Affiliations:
Manav Rachna International University, Faridabad;Manav Rachna International University, Faridabad
Venue:
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Year:
2012

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Abstract

Clustering is a procedure of organizing the objects in groups whose member exhibits some kind of similarity. So a cluster is a collection of objects which are alike and are different from the objects belonging to other clusters. K-Means is one of clustering algorithms in which users specify the number of cluster, k, to be produced and group the input data objects into the specified number of clusters. But in k-means algorithm the initial centroid of clusters is selected randomly. So it does not result in definiteness of cluster. In our proposed method we have introduced new algorithm for grouping two dimensional data. The proposed algorithm uses a systematic way to find the initial centroids.