Enhanced K-Mean Clustering Algorithm to Reduce Number of Iterations and Time Complexity

Clustering technique is used to put similar data items in a same group. K-mean clustering is a common approach, which is based on initial centroids selected randomly. This paper proposes a new method of K-mean clustering in which we calculate initial centroids instead of random selection, due to which the number of iterations is reduced and elapsed time is improved.