On Tue, Jan 31, 2012 at 02:08:21PM -0500, Jeff Farris wrote: > I'm currently using pickle to persist models (e.g. SVC). After upgrading > sklearn, these pickled models from a previous version of sklearn don't tend > to work and then I need to retrain. Is there some version independent way > of saving models (e.g. libsvm model format) or other recommendations on > how to go about doing this without retraining all my persisted models after > each sklearn upgrade?
You could pull out the individual learned parameters and save them as NPY files with numpy.save. Ideally, object implementations would be versioned and their __setstate__() would be able to de-persist old objects, but it's a significant maintenance burden. David ------------------------------------------------------------------------------ Keep Your Developer Skills Current with LearnDevNow! 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-d2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
