On 2015-08-18 21:37:41, Sebastian Raschka <[email protected]> 
wrote:
> I think for “simple” linear models, it would be not a bad idea 
> to save the weight coefficients in a log file or so. Here, I 
> think that your model is really not that dependent on the 
> changes in the scikit-learn code base (for example, imagine that 
> you trained a model 10 years ago and published the results in a 
> research paper, and today, someone asked you about this 
> model). I mean, you know all about how a logistic regression, 
> SVM etc. works, in the worst case you just use those weights to 
> make the prediction on new data — I think in a typical “model 
> persistence” case you don’t “update” your model anyways so 
> “efficiency” would not be that big of a deal in a typical “worst 
> case use case”.

Agreed—this is exactly the type of use case I want to support. 
Pickling won't work here, but using HDF5 like MNE does would 
probably be close to ideal (thanks to Chris Holdgraf for the 
heads-up):

https://github.com/mne-tools/mne-python/blob/master/mne/_hdf5.py

Stéfan

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