Andreas Mueller <amueller@...> writes: > > Am 29.11.2012 23:45, schrieb Afik Cohen: > > > > > > Hey Mathieu! > > > > Pretty much the only reason we wrap SGDClassifier in a OneVsRestClassifier is so > > we can get predict_proba results on a per class basis. This fits our use case > > better than getting prediction proabilities spread over all classes at once. > > Hmm.. is there a way to do that without the OneVsRestClassifier wrapper? > > > Does that mean that you are doing multi-label classification, i.e. there > is possibly more than one correct answer per example? > Then I think there is no way to achieve this currently without > OneVsRestClassifier, > though it would be easy enough to implement. >
No, we aren't doing multi-label classification, just multiclass. He was saying we could just use SGDClassifier directly, which is true, but AFAIK there is no way to get good prediction probability outputs on a per-class basis unless you train binary classifiers by wrapping it in a OneVsRestClassifier() call... or is there? Afik ------------------------------------------------------------------------------ Keep yourself connected to Go Parallel: BUILD Helping you discover the best ways to construct your parallel projects. http://goparallel.sourceforge.net _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
