On 01/23/2012 05:54 PM, Dimitrios Pritsos wrote: > Relate to LinearSVC() and SGDClassifier() > > I ran both with a subset of my 33k-samples by 30k-features and I am > getting a huge difference in results. Is this expected behavour! > > After 10-fold-cross-validation (using the Defaults as arguments in both > cases) I am getting: > > Accuracy = 44% for SGD > Accuracy = 89% for LinearSVC > > > This is the modules I called > csvm = svm.LinearSVC() > csvm.fit(X, y) > csvm.score(crossv_X, crossv_y) > > sgd = linear_model.SGDClassifier() > sgd.fit(X, y) > sgd.score(crossv_X, crossv_y) > > > This is somewhat expected since SGD has some tuning parameters. For example the number of iterations is set to 5 by default afaik. Having this higher would probably give you better results. Also the parameter alpha should probably be cross-validated, as SGD is more sensitive to this then LinearSVC is to the C parameter.
------------------------------------------------------------------------------ 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
