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for Large Data-set

By Shailendra Singh Raghuwanshi and Premnarayan Arya

Abstract

Abstract:-Clustering Performance is based iterative and analysis is a descriptive task that seeks to identify homogeneous groups of objects based on the values of the methodology is search to be near and its close to the desired cluster centers in each step attributes. This paper has been proposes a Modified approach K-Means clustering which executes K-means algorithm this Algorithm approach is better in the process in large number of clusters and its time of execution is comparisons base on K-Mean approach. If the process experimental result is using the proposed algorithm it time of computation can be reduced with a group in runtime constructed data sets are very promising.Modified Approach of K Mean Algorithm is Better then K Mean for Large Data Sets.

Topics: Data mining, K-means clustering, , cluster quality, Clustering Algorithm, Modified KMean Algorithm
Year: 2012
OAI identifier: oai:CiteSeerX.psu:10.1.1.380.8308
Provided by: CiteSeerX
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