[pymvpa] Feature selection on RSA

[Alyson Saenz]

Hey guys, I'm having problems wrapping my head around this.



I'm trying to run a representational similarity analysis RSA, on the same
data in which I run a MVPA analysis to compare both outputs. My problem is
that when I introduce the data for MVPA, I use feature selection like in
the tutorial, so I grab 5% of the ANOVA’s output and use it to train and
test the data. But in the tutorial, seems like you grab all the voxels, not
only a selection.



How can I grab only the same 5% for RSA?



This is the code I use for MVPA:



clf = LinearCSVMC()

fsel = SensitivityBasedFeatureSelection(OneWayAnova(),
FractionTailSelector(0.05, mode='select', tail='upper'))

fclf = FeatureSelectionClassifier(clf, fsel)

cvte = CrossValidation(fclf, NFoldPartitioner(), errorfx=lambda p, t:
np.mean(p == t), enable_ca=['stats'])

cv_results = cvte(ds)



This is the one I got for RSA:



dsm = rsa.PDist(square=True)

res = dsm(ds)
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