[pymvpa] Sensitivity analysis with GNB

[Thomas Nickson]

On Fri, Dec 12, 2014 at 1:42 PM, Yaroslav Halchenko <debian at onerussian.com>
wrote:

>
> On Fri, 12 Dec 2014, Thomas Nickson wrote:
>
> >    I've trained a GNB classifier on a dataset with moderate success and
> would
> >    like to look at the regions that the classifier finds most
> interesting.
>
> just use sphere_gnbsearchlight  ? ;)
>
>
I wanted to do whole brain but I'm doing both anyway.


> > I
> >    notice in the code that there is a sensitivity analyser for the GNB
> module
> >    but that it has been removed:
>
> ;) wonders of the open-source, aren't they? ;)
>
>
Truly!


> >    ## class GNBWeights(Sensitivity):
> >    ## """`SensitivityAnalyzer` that reports the weights GNB trained
> >    ## on a given `Dataset`.
> >    ## """
> >    ## _LEGAL_CLFS = [ GNB ]
> >    ## def _call(self, dataset=None):
> >    ## """Extract weights from GNB classifier.
> >    ## GNB always has weights available, so nothing has to be computed
> here.
> >    ## """
> >    ## clf = self.clf
> >    ## means = clf.means
> >    ## XXX we can do something better ;)
> >    ## return mean
>
> >    Is the use of the means considered to be poor in some sense?
>
> well -- kinda since they wouldn't be anyhow describing the 'sensitivity'
> really, just a mean of the voxel given a class  label.
>

Ok.


>
> >    Could anyone provide more information about this:
>
> >    # XXX Later come up with some
> >    # could be a simple t-test maps using distributions
> >    # per each class
>
> yeah -- something like that might prove being useful, but probably not
> too far from omnibus or ad-hoc Anovas which we have.  So that is why
> they were never implemented
>
You mean using ANOVAs to calculate the sensitivity? How do I do that?

>
> --
> Yaroslav O. Halchenko, Ph.D.
> http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org
> Research Scientist,            Psychological and Brain Sciences Dept.
> 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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