Thanks @Gilles for the quick answer! > > 6) As far as I can see, it is possible to set "bootstrap" to 'False' and > > still > > have max_features = n_features. > > This would build n_estimator estimators that are identical, right? > > I think this option should somehow be excluded. > >Using random forests, yes they would identical. They wouldn't for extra-trees.
I haven't looked at extra trees yet (and probably won't in the near future). Do you think in the case of random forests, the user should be alerted to this fact or do you think they should know what they are doing? On 01/02/2012 05:04 PM, Olivier Grisel wrote: > 2012/1/2 Gilles Louppe<[email protected]>: > >> >>> 5) I think an explanation of "bootstrap" should go in the docs. >>> The docstring just states "Whether bootstrap samples are used when >>> building trees." >>> I don't think this is very helpful since "bootstrap" is quite hard to >>> look up for >>> an outsider. >>> >> Okay, we should make that more explicit. I didn't realize it was obscure. >> > You can just say that it's "randomly sampling with replacement samples > for the training set" and add a link to > http://en.wikipedia.org/wiki/Bootstrapping_%28statistics%29 > > +1 that's what I had in mind. > Thanks Andy for making the effort to make the doc and default value > consistent and Gilles for answering :) > > You're welcome > Looking forward to reviewing the pull request. > > :P Maybe tonight. ------------------------------------------------------------------------------ Ridiculously easy VDI. With Citrix VDI-in-a-Box, you don't need a complex infrastructure or vast IT resources to deliver seamless, secure access to virtual desktops. With this all-in-one solution, easily deploy virtual desktops for less than the cost of PCs and save 60% on VDI infrastructure costs. Try it free! http://p.sf.net/sfu/Citrix-VDIinabox _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
