[pymvpa] Sensitivity analysis with GNB

[Thomas Nickson]

On Fri, Dec 12, 2014 at 3:30 PM, Thomas Nickson <thomas.nickson at gmail.com>
wrote:
>
> On Fri, Dec 12, 2014 at 3:17 PM, Nick Oosterhof <
> n.n.oosterhof at googlemail.com> wrote:
>
>>
>> On 12 Dec 2014, at 16:13, Thomas Nickson <thomas.nickson at gmail.com>
>> wrote:
>>
>> >> >    # 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?
>>
>> See e.g.
>> http://www.pymvpa.org/generated/mvpa2.measures.anova.OneWayAnova.html
>>
>> Since the GNB classifier works feature-wise (does not consider any
>> covariance across voxels) the F value is a measure of how sensitive a
>> feature is in discriminating between the classes.
>>
>
>
What's the best way to use this module for this? Do I have to take the
GNB.means and then make a dataset where the targets are just [0,1] or is
there a better way?

Thanks.



>
>
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>
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