How much does the mcl clustering differ from the clustering resulting from a perfectly computed MCL process?
For graphs with up until a few thousand nodes a perfectly computed MCL process can be achieved by abstaining from pruning and doing full-blown matrix arithmetic. Of course, this still leaves the issue of machine precision, but let us wholeheartedly ignore that. Such experiments give evidence (albeit incidental) that pruning is indeed really what it is thought to be – a small perturbation. In many cases, the ’approximated’ clustering is identical to the ’exact’ clustering. In other cases, they are very close to each other in terms of the metric split/join distance as computed by clmdist(1). Some experiments with randomly generated test graphs, clustering, and pruning are described in . On a different level of abstraction, note that perturbations of the inflation parameter will also lead to perturbations in the resulting clusterings, and surely, large changes in the inflation parameter will in general lead to large shifts in the clusterings. Node/cluster pairs that are different for t