[pymvpa] Train and test on different datasets using searchlights

[Raúl Hernández]

Hi, I would like to train with a dataset and test with a different one. But
I haven’t been able to find out a straight forward way to do it. I read the
very same question from a couple of years ago (
http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/2010q4/001265.html
) On it, the answer was to use a piece of code shown there:



cv = CrossValidatedTransferError(

         TransferError(LinearCSVMC()),

         CustomSplitter([(0, 1)])) # 0 for training, 1 for testing



  sl = Searchlight(cv, radius=5)



  # assuming you have dstrain and dstest

  dstrain.chunks[:] = 0

  dstest.chunks[:] = 1



  sl_map = sl(dstrain + dstest)


I tried this, but I get the error:

NameError: name 'CrossValidatedTransferError' is not defined

I’m using a virtual machine with NeuroDebian 8.0 and supposedly pymvpa is
up to date, seems like I'm missing some libraries. How can I get them?

Thanks
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