[pymvpa] Can't access an enabled classifier attribute.

[Roberto Guidotti]

Thank you very much Yaroslav, you're always thoroughly exhaustive!

Now it works very well!!

Thank you
Roberto

On 27 November 2012 16:19, Yaroslav Halchenko <debian at onerussian.com> wrote:

>
> On Tue, 27 Nov 2012, Roberto Guidotti wrote:
> >    Well the snippet probabilities = clf.ca.probabilities is only an
> example
> >    that I've build to reveal the exception (I didn't think is a version
> >    problem, I had 2.0.1 mvpa)!!�
>
> 2.0.1 ... hm... I do not remember how life was back then ;)
>
> >    BTW I was quite sure that the problem relied on the cross validation
> :)!
> >    �I would like to gather all the predictions/probabilities for each cv
> >    fold.
>
> then provide callback to the CrossValidation and there you can collect
> anything you like from your classifier upon completion of every split.
> e.g. look at
> https://github.com/PyMVPA/PyMVPA/blob/HEAD/mvpa2/tests/test_rfe.py#L403
>
>
> >    This why using the ca 'training_stats' during the definition of the
> >    classifier, I had the probabilities of the samples during training?
>
> I guess ;)
>
> >    So I can't have access to every cv fold probabilities/predictions
> using
> >    CrossValidation object?
>
> you can with above mentioned callback
>
> > Or I need a manual CrossValidation (and sometimes
> >    a Feature Selection)?
>
> if you decide to gather probabilities on both training and testing
> samples, then you might need indeed manual loop with explicit .train
> .predict so you get needed probabilities at the right moment.  Otherwise
> -- callback should be sufficient
> --
> Yaroslav O. Halchenko
> Postdoctoral Fellow,   Department of Psychological and Brain Sciences
> Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
> Phone: +1 (603) 646-9834                       Fax: +1 (603) 646-1419
> WWW:   http://www.linkedin.com/in/yarik
>
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