On Tue, Oct 8, 2013 at 11:32 PM, Olivier Grisel <[email protected]>wrote:
> 2013/10/8 Gael Varoquaux <[email protected]>:
> > On Tue, Oct 08, 2013 at 07:47:40AM +0200, Gilles Louppe wrote:
> >> Unfortunately, algorithms for recommender systems are not planned in
> >> scikit-learn in the short or mid-term.
> >
> > Indeed in the short term, but are we sure that we want to close the door
> > to contributions implementing standard approaches for recommender
> > systems?
>
> +1 for encouraging pull requests that implement recsys building blocks
> (e.g. matrix factorization) that fit the scikit-learn API (fit and
> partial_fit + predict or transform) and work with standard input
> datastructures (e.g. input data is a scipy.sparse matrix or numpy
> array).
>
> We don't want frameworkish code that hard code recsys specific
> concepts (e.g. users and items) in the API though.
>
I'm not familiar enough with recommender systems to understand whether any
of the existing matrix factorisations apply. Is this more a matter of
presenting an example of their application to this task?
- Joel
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