Flowchart: A Representation of Traditional k-means Algorithm. Initial centroid is selected in step 1, each data point is assigned to a cluster in step 2 based on the shortest computed Euclidean distance metric. Centroid position is recomputed in step 3 and a test of convergence done in step 4, which terminates if “yes”, but control transferred to step 2 if “No”.