Sorry Yaroslav,
but that surpasses my coding skills :-(
Yaroslav Halchenko debian at onerussian.com
Thu Jul 18 13:29:36 UTC 2013
>
senses = []
for i, pset in enumerate(NFoldPartitioner().generate(dataset)):
# split partitioned dataset
split = [d for d in Splitter('partitions').generate(pset)]
senses.append(senssvm(split[0]))
Do you mean, something like:
----------------------------------------------------------
clfsvm = SplitClassifier(LinearCSVMC(), NFoldPartitioner())
rfesvm = RFE(clfsvm.get_sensitivity_analyzer(postproc=maxofabs_sample()),
ConfusionBasedError(clfsvm, confusion_state='stats'), Repeater(2),
fselector=FractionTailSelector(0.30, mode='select', tail='upper'),
stopping_criterion=NBackHistoryStopCrit(BestDetector(), 10),
train_pmeasure=False, update_sensitivity=True)
fclfsvm = FeatureSelectionClassifier(clfsvm, rfesvm)
sensanasvm = fclfsvm.get_sensitivity_analyzer(postproc=maxofabs_sample())
cv_sensana_svm = RepeatedMeasure(sensanasvm, NFoldPartitioner())
senses = []
for i, pset in enumerate(NFoldPartitioner().generate(fds)):
# split partitioned dataset
split = [d for d in Splitter('partitions').generate(pset)]
senses.append(cv_sensana_svm(split[0]))
----------------------------------------------------------
This seems to run, senses incorporates 6 splits, but then I do not know how to
proceed further to get the sensitivity map, with something like:
print senses.samples # print senses[0].samples ?
ov = MapOverlap()
stabil_overlap_fraction_svm = ov(senses.samples > 0)
print stabil_overlap_fraction_svm
niftiresults = map2nifti(fds, senses)
Thank you again!
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: [email protected]
Skype: mtettamanti
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