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[Documentation] Stopping criterion #109

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arthurmensch opened this issue Feb 20, 2017 · 2 comments
Open

[Documentation] Stopping criterion #109

arthurmensch opened this issue Feb 20, 2017 · 2 comments

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@arthurmensch
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I haven't been able to find appropriate documentation for the stopping criterion that are used in SAG(A) and coordinate descent. Is it violation of the KKT conditions ? It would be great to make this explicit in the documentation, and verify consistency of the stopping criterion across solvers.

Optionally it would also be nice to be able to monitor the loss on a validation set to do early stopping, as it is done with specific callbacks in e.g., keras -- but this is a feature that should appear in scikit-learn.

@arthurmensch arthurmensch changed the title Documentation: stopping criterion [Documentation] Stopping criterion Feb 20, 2017
@arthurmensch
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Ok so looking at the code I believe that the gradient is monitored and compared to the gradient computed at the first epoch in SAGClassifier ?

@fabianp
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fabianp commented Feb 20, 2017

yes we are looking at the residuals of the KKT conditions, "normalized" by the residuals at the first iteration if I remember correctly. Anyway, would be cool to have the stopping criteria you mention.

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