Strengths of K-means clustering Relatively scalable in processing large data sets a Relatively efficient: O(tkn), where n is #f objects, k is clusters, and t is iterations. Normally, k, t<< n a Often terminates at a local optimum; the global optimum may be found using techniques such as genetic algorithmsStrengths of K-means clustering ◼ Relatively scalable in processing large data sets ◼ Relatively efficient: O(tkn), where n is # objects, k is # clusters, and t is # iterations. Normally, k, t << n. ◼ Often terminates at a local optimum; the global optimum may be found using techniques such as genetic algorithms