On 01/08/2012 11:29 PM, Olivier Grisel wrote: > 2012/1/8 Andreas<[email protected]>: > >> Hey everybody. >> @larsmans (my personal hero for the day) started refactoring the SVM >> class structure here: >> https://github.com/larsmans/scikit-learn/commits/refactor-svm >> after some discussion here: >> https://github.com/scikit-learn/scikit-learn/issues/253 >> and somewhat related here: >> https://github.com/scikit-learn/scikit-learn/issues/100 >> >> The bottom line is: the SVM class structure is not as nice as one might >> hope, >> having different user interface classes for dense and sparse is a bit >> arkward >> and it's hard to give SVC and SVR different functionality with the >> current structure. >> >> I suggest putting the "nu" and "C" variants of SVC and SVR in the same >> class, >> as that might already make things somewhat easier. >> What do you think about that? >> Might hope would be to have a "BaseLibSVM" and an SVR and SVC deriving >> from that. >> These could then "under the hood" call dense or sparse implementation. >> >> Comments? >> > The NuSVC and SVC might not take the same hyperparams (`C` and > `scale_C` vs `nu`). Do you plan to keep all the hyperparam and add a > new switch and ignore the hyperparams that are not relevant? > > On the plus side: > - that would make it easier to grid search Nu-SVC vs C-SVC > > Does it ever make sense to grid search over this if you also grid search over C/nu?
> On the minus side: > - having a many constructor parameters with some of inactive depending > on one another makes it more complicated for the user to understand > the class. > > The nu-SVR takes a 'C' parameter, only the nuSVC does not. While generally I agree that having unused parameters is a bad thing, I think it wouldn't hurt so much here (as there are already quite a few with the different kernels) > I don't have any strong opinion that would favor one vs the other. > > In any case we should preserve backward compat with a deprecation > warning for NuSVC if we decide to merge it into SVC. > > Definitely Another thing is: Does any one have a reference on a paper using nuSVMs? I have never seen that and as such I think it is only of interest to people studying SVM optimization. For actual SVM users, I would guess that they never have a need for using nuSVM and that having all this duplication is more confusing than helping. ------------------------------------------------------------------------------ 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
