Enhanced Initial Centroids for K-means Algorithm

This paper focuses on the enhanced initial centroids for the K-means algorithm. The original kmeans is using the random choice of init ial seeds which is a major limitation of the orig inal K-means algorithm because it produces less reliab le result of clustering the data. The enhanced method of the k-means algorithm includes the computation of the weighted mean to improve the centroids initializat ion. This paper shows the comparison between K-Means and the enhanced KMeans algorithm, and it proves that the new method of selecting initial seeds is better in terms of mathemat ical computation and reliability.