Re: [scikit-learn] Retracting model from the 'blackbox' SVM

2018-05-05 Thread Joel Nothman
The coef_ available from LinearSVC will be somewhat indicative of the relative importance of each feature. But you might want to look into our feature selection documentation: http://scikit-learn.org/stable/modules/feature_selection.html ___

Re: [scikit-learn] Retracting model from the 'blackbox' SVM (Sebastian Raschka)

2018-05-04 Thread David Burns
an Raschka) -- Message: 1 Date: Fri, 4 May 2018 05:51:26 -0400 From: Sebastian Raschka <m...@sebastianraschka.com> To: Scikit-learn mailing list <scikit-learn@python.org> Subject: Re: [scikit-learn] Retracting model from the 'bl

Re: [scikit-learn] Retracting model from the 'blackbox' SVM

2018-05-04 Thread Sebastian Raschka
Dear Wouter, for the SVM, scikit-learn wraps the LIBSVM and LIBLINEAR. I think the scikit-learn class SVC uses LIBSVM for every kernel. Since you are using the linear kernel, you could use the more efficient LinearSVC scikit-learn class to get similar results. I guess this in turn is easier to