On Thu, Dec 29, 2011 at 12:46:36PM -0800, adnan rajper wrote: > I use LinearSVC for text classification. My problem is that I want to > generate ROC curve for LinearSVC. Since LinearSVC does not output > probabilties. Is there any other way to generate ROC curve for LinearSVC? > I have tried svm.SVC(kernel='linear', probabilities=True) but it gets too > slow.
If you really want to use LinearSVC (you could use a LogisticRegression instead), I see a couple of ways: * You could bootstrap the prediction, and thus get some decision metric. This is quickly going to get costly. * You could use the decision function, (decision_function method of the LinearSVC) although this is clearly a hack. To the other developers: is their a reason/difficulty for not having Platt's method (implemented for SVC, AFAIK) for LinearSVC? HTH, Gaël ------------------------------------------------------------------------------ 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
