In our previous work (Tufiş and Ion, 2003), to approximate Z we imposed an exit condition for the clustering algorithm based on distance heuristics.
the algorithm stops when the minimal distance between the existing classes increases beyond a given threshold level: where dist(k) is the minimal distance between two clusters at the k-th iteration step and α is an empirical numerical threshold.