The K-Means algorithm iteratively attempts to determine clusters within the test data by minimizing the distance between the mean value of cluster center vectors, and the new candidate cluster member vectors. The following equation assumes dataset members that range from X1 to Xn; it also assumes K cluster sets that range from S1 to Sk, where K <= n.