Hi Yanir, thanks for raising this issue. I've implemented this feature without much though; furthermore, I haven't used OOB estimates in my work yet. I need to think more deeply about the issue - will come back to you.
You propose to update ``y_pred`` only for the in-bag samples, correct? best, Peter 2013/3/22 Andreas Mueller <amuel...@ais.uni-bonn.de>: > Hi Yanir. > I was not aware that GradientBoosting had oob scores. > Is that even possible / sensible? It definitely does not do what it promises > :-/ > > Peter, any thoughts? > > Cheers, > Andy > > > On 03/22/2013 11:39 AM, Yanir Seroussi wrote: > > Hi, > > I'm new to the mailing list, so I apologise if this has been asked before. > > I want to use the oob_score_ in GradientBoostingRegressor to determine the > optimal number of iterations without relying on an external validation set, > so I set the subsample parameter to 0.5 and trained the model. However, I've > noticed that oob_score_ improves in a similar manner to the in-bag scores > (train_score_). That is, it goes down very fast, and keeps improving > regardless of the number of iterations. > > Digging through the code in ensemble/gradient_boosting.py, it seems like the > cause is that oob_score_[i] includes previous trees that were trained on the > OOB instances of the i-th sample. Isn't the OOB score supposed to be > calculated for each OOB instance using only trees that where this instance > wasn't used for training (as done for random forests)? > > Cheers, > Yanir > > > ------------------------------------------------------------------------------ > Everyone hates slow websites. So do we. > Make your web apps faster with AppDynamics > Download AppDynamics Lite for free today: > http://p.sf.net/sfu/appdyn_d2d_mar > > > > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > ------------------------------------------------------------------------------ > Everyone hates slow websites. So do we. > Make your web apps faster with AppDynamics > Download AppDynamics Lite for free today: > http://p.sf.net/sfu/appdyn_d2d_mar > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > -- Peter Prettenhofer ------------------------------------------------------------------------------ Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://p.sf.net/sfu/appdyn_d2d_mar _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
