On Fri, Jan 27, 2012 at 04:58:30PM +0100, Olivier Grisel wrote:
> I would advise you to start by experimenting with your own version of
> GridSearchCV (by deriving from the version of sklearn) and passing a
> LoadBalancedView instance as argument to the constructor and use it in
> the fit method instead of calling joblib.

This does sound like a good excercice. This kind of prototypes will
enable us to have better ideas of the challenges and their solutions.

> This might be done by extending joblib to be able to deal with
> distributed infrastructure, or this could be done at sklearn level by
> refactoring the existing classes to make them more pluggable with
> IPython.parallel

I would really like to avoid having any direct import to IPython in
scikit-learn: I would like our set of dependencies to stick to scipy,
numpy, and optionally matplotlib for the examples (note that this also
means that I would like to get rid of the pyamg dependency, that has
proven a source of test failures that we don't catch early).

Gael

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