Hi Michael, my answer is more a warning than an answer.
Beyond 2 classes the "best" would be to use something like L1/L2 mixed norm with a real multinomial loss. Unfortunately we don't have it in the scikit. Also looking at the weights of a sparse logistic or L2 model (logistic or SVM) working with full brain data can be dangerous when it comes to "interpretation". Basically I wouldn't do it if it's a plain logistic regression working with voxel based features. Now it depends on what you want to say and you might find a way, eg. using permutations or bootstrap, to assess some statistical significance. Alex On Mon, Mar 5, 2012 at 4:13 AM, Michael Waskom <[email protected]> wrote: > Hi all, > > I have a LogisticRegression model I'm training in a 3-class scenario. I'd > like to examine the coefficients for the models. As the default for > LogisitcRegression is to do one-vs-all classification, my clf.coef_ array is > shape 3 x nfeat. > > My question is how to interpret the sign of the coefficients. I take each > nfeat vector to be the coefficients for the A vs all, B vs all, C vs all > models. In this case, are positive coefficients in the first nfeat vector > those weighing the classification towards "A" and the negative coefficients > those weighing the model towads "all"? Or is it the other way around? > > Cheers, > Michael > > ------------------------------------------------------------------------------ > Try before you buy = See our experts in action! > The most comprehensive online learning library for Microsoft developers > is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, > Metro Style Apps, more. Free future releases when you subscribe now! > http://p.sf.net/sfu/learndevnow-dev2 > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
