[pymvpa] Bad accuracy results for cross subject classification

[gal star]

Hello All,
I am wondering how to perform classification over
a cross subject nifti file i've created using FSL.

I've tried to use NFoldPartitioner with LinearCSVMC, though
the results are always 100% accuracy (which looks fishy).

I've assured there is no contamination in the data (no scan from trainset
exists also in testset).

What is the correct way to perform cross subject classification
over functional datasets?

Also attached below is confusion matrix of the described classification.

Your help would be appreciated,
Gal Star
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/attachments/20150112/964278bb/attachment.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: classification 100.png
Type: image/png
Size: 9131 bytes
Desc: not available
URL: <http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/attachments/20150112/964278bb/attachment.png>