2012/1/31 David Warde-Farley <[email protected]>: > 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.
Note that you can use `sklearn.externals.joblib.dump` for that. The current version can even compress the arrays. > Ideally, object implementations would be versioned and their __setstate__() > would be able to de-persist old objects, but it's a significant maintenance > burden. I am -1 for that solution. That would be a lot of boilerplate to maintain. I prefer external serializers like joblib or a PMML exporter that keep that logic out of the code. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ 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
