A second class of clustering evaluation techniques is based on a combinatorial approach which examines the number of pairs of data points that are clustered similarly in the target and hypothesized clustering.
each pair of points can either be 1) clustered together in both clusterings (N 11 ), 2) clustered separately in both clusterings (N 00 ), 3) clustered together in the hypothesized but not the target clustering (N 01 ) or 4) clustered together in the target but not in the hypothesized clustering (N 10 ).