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

[J.A. Etzel]

On 1/31/2013 2:31 PM, Yaroslav Halchenko wrote:
>
> On Thu, 31 Jan 2013, J.A. Etzel wrote:
>
> There it was not only about "test set" but about the "whole-dataset"
> (i.e.  traing+test sets).

I think that's what I mean as well - permute both the training and 
testing set labels.

Why not, say, if partitioning on the runs, randomize the labels within 
each run then perform the classification? That is, the labels are 
permuted in the entire dataset (within each run, since that's a 
meaningful subdivision/source of variance), then the permuted-label 
dataset is treated (i.e. same partitioning/classification) in the same 
was as the real data?

Jo


-- 
Joset A. Etzel, Ph.D.
Research Analyst
Cognitive Control & Psychopathology Lab
Washington University in St. Louis
http://mvpa.blogspot.com/