[pymvpa] Sensitivity map with RFE?

[marco tettamanti]

Dear all,
is there any manner to obtain a sensitivity map with RFE, similar to what can be 
done with feature selection?

I am trying to use the following code:

#-------------------------------------------------
clfsvm = LinearCSVMC()

rfesvm = RFE(clfsvm.get_sensitivity_analyzer(postproc=maxofabs_sample()), 
CrossValidation(clfsvm, NFoldPartitioner(), errorfx=mean_mismatch_error, 
postproc=mean_sample()), Repeater(2), fselector=FractionTailSelector(0.30, 
mode='select', tail='upper'), 
stopping_criterion=NBackHistoryStopCrit(BestDetector(), 10), 
update_sensitivity=True)

fclfsvm = FeatureSelectionClassifier(clfsvm, rfesvm)

sensanasvm = fclfsvm.get_sensitivity_analyzer(postproc=maxofabs_sample())

cv_sensana_svm = RepeatedMeasure(sensanasvm, NFoldPartitioner())

senssvm = cv_sensana_svm(fds)
#-------------------------------------------------

However, after a while I get the following error:

RuntimeError: Cannot reverse-map data since the original data shape is unknown. 
Either set `dshape` in the constructor, or call train().


Thank you in advance for any help!
Best wishes,
Marco

-- 
Marco Tettamanti, Ph.D.
Nuclear Medicine Department & Division of Neuroscience
San Raffaele Scientific Institute
Via Olgettina 58
I-20132 Milano, Italy
Phone ++39-02-26434888
Fax ++39-02-26434892
Email: tettamanti.marco at hsr.it
Skype: mtettamanti
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