CedricL <[email protected]> wrote: > > Hello all, > > last update of OTB 5.2 seems to remove SVM learning (I am not sure). > > Whatever, even if I am a fan of SVM in particular with parameter > optimization, I now that Random Forest is also powerfull (may be a little bit > less than svm) but strongly faster. > > However, because I don't know to much Random Forest I don(t know how to chose > best settings in comparison to SVM optimization parameters. > > So have you any tricks or paper to read about that ? >
Hi Cédric, I would suggest to have a look at this paper for RF parameter tuning: http://dx.doi.org/10.1016/j.isprsjprs.2011.11.002 An this one for a comparison of SVM and RF: http://dx.doi.org/10.3390/rs70912356 As a rule of thumb, start with -classifier.rf.nbtrees 100 -classifier.rf.max 25 -classifier.rf.min 25 And eventually tune from there, but in my experience, performances are not very sensitive to these parameters. Jordi > Best > > > -- -- -- Check the OTB FAQ at http://www.orfeo-toolbox.org/FAQ.html You received this message because you are subscribed to the Google Groups "otb-users" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/otb-users?hl=en --- You received this message because you are subscribed to the Google Groups "otb-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
