[pymvpa] parallelizing for cross-subjects NFold cross-validation?

[Regina Lapate]

Hello all:

I have been trying to run an NFold cross-validation, leave-one-subject-out
scheme, and I am writing because the process has been taking quite a while.
Specifically, I am using SVM, n=2 labels/targets, n=130 subjects (which are
my 'chunks'), and I initially tried 1000 permutations--but realized that
would take weeks to run.

--Do you have any suggestions of how to go about this? Would it be
appropriate to split the job by shuffling fewer times per job, and then
aggregate across the null distribution over those jobs at the end (or are
the shuffles occurring in a systematic way that would render such an
aggregation over jobs biased)?

Thank you for any pointers!

Regina
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/attachments/20171208/0ec2acbd/attachment.html>