[pymvpa] Train and test on different classes from a dataset

[Jan Derrfuss]

Dear All,

I would like to train a classifier on classes A vs. B and test it on 
classes C vs. D from the same dataset. The dataset consists of 6 chunks 
and my aim is to perform a crossvalidation searchlight analysis (i.e., 
train A vs. B on chunks 1 to 5, predict C vs. D for chunk 6; then train 
A vs. B for chunks 1-4 and 6, predict C vs. D for chunk 5; and so on). 
When testing, a prediction of class A should be considered correct if 
the label is C and incorrect if the label is D (and vice versa for class B).

I found some e-mails in the archive that addressed this issue in the 
context of training on dataset 1 and testing on dataset 2 
(http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/2010q4/001263.html, 
http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/2012q4/002309.html), 
but I'm not quite sure what the best way to address this issue would be 
in the context of my analysis. It would be great if someone could point 
me into the right direction.

I'm using PyMVPA 2.

Any help would be greatly appreciated!

Jan