Conclusion The K-means is the most used clustering algorithm, due to its inherent simplicity, speed, and empirical success. However, in its basic form, it has limitations such as the sensitivity to the initial partition, sensitivity to noise, and the requierement of predeﬁned number of clusters. Thus, this algorithm needs to be improved in order to remain as popular. J.A Hartigan and M.A Wong Algorithm AS 136 : A K-Means Clustering Algorithm