To prevent spam users, you can only post on this forum after registration, which is by invitation. If you want to post on the forum, please send me a mail (h DOT m DOT w DOT verbeek AT tue DOT nl) and I'll send you an invitation in return for an account.
Questions about comparing algorithms.
I'm writing my bachelor thesis on PM Algorithms. For that, I want to benchmark them on the same training/test set and compare their quality dimensions. Is there a way to get comparable values for each discovery method? E.g. is it possible to make quality assertions about fitness, when one algorithm outputs a Petri Net and another a fuzzy model? If so, any pointers how I would best go about it? Should I convert everything to a petri net, or can I use different fitness methods for each output model?
The methods I want to focus on are Fuzzy, Alpha, Heuristic, Multi-phase, Genetic, Region-based Miner. Are there any (new or old) important ones missing?
Lastly, is there a way to see who wrote which algorithm (or plugin) and when? I want to find the corresponding papers, but it has been very difficult so far. For instance, I couldn't find anything about Alpha-R, which I presume to be the latest Alpha Miner.
Thank you for your help.