In many research areas it’s always found that it is very difficult to cluster the databases which come under the close region of clusters. When the database has a unique cluster then it is faster to make the cluster in lesser times but when it is coming to closer region of two or more clusters then the time taken for the clustering is high and need to be clustered very carefully by examining each attributes. In this paper clustering is done using the partitioning method and complex regions are selected which are closed to two or more cluster and this selected database is again carefully examined by each of the attribute and then finally clustered to produce more accuracy than the partitioning method.

Boundary region analysis, Precision Clusters, Share market database, Large database, Reduced Dataset, Attribute Selection, etc

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