Enhanced K Mean Algorithm for Systematic Selection of Centroids with good Accuracy and Less Clustering Time

The clustering of data set depends on the selection of initial centroids. Original k mean algorithm select the centroids randomly then the clusters get change and uniformities not carried, so the proposed algorithm is used which select the initial centroids in a systematic way from the data set. The performance of the proposed algorithm is verified by comparing with the original algorithm, as per the results accuracy of clustering increased by proposed algorithm, iterations and time taken for clustering get decreases in proposed system. The results are explained by charts.