2012/1/31 Jeff Farris <[email protected]>:
> 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?

Indeed this is an issue we will need to address at some point. I don't
think python pickles are the solution for this.

For some models it might be possible to write PRML importer and exporters:

http://en.wikipedia.org/wiki/Predictive_Model_Markup_Language
http://www.dmg.org/

That would give us the additional benefit to be interoperable with the
Google Prediction API and other tools from the analytics industry:

https://code.google.com/apis/predict/docs/pmml-schema.html
http://en.wikipedia.org/wiki/Predictive_Model_Markup_Language#PMML_Products

-- 
Olivier
http://twitter.com/ogrisel - http://github.com/ogrisel

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