The k-center cost function. An alternative to k-means is the k-center clustering problem, defined as follows: Input: Data points x1,...,x in some metric space (X, d); integer k > 0 Output: "Centers" 1,..., 1 , . . ., k X Goal: Minimize max min d(xi, j ). 2 1