[pymvpa] SMLR weights

[Daqiang Sun]

Hi,



----- Original Message ----
From: Yaroslav Halchenko <debian at onerussian.com>
To: pkg-exppsy-pymvpa at lists.alioth.debian.org
Sent: Friday, January 23, 2009 5:34:29 PM
Subject: Re: [pymvpa] SMLR weights

> Hi, Thanks for your quick response!
you are welcome

> The save method is a nice trick, and it makes sense to use samples only for prediction.
btw -- if not too big of a secret -- why did you want to invoke .predict
manually? most of the time it is sufficient to use
CrossValidatedTransferError or SplitClassifier...

no, not at all ;) for that case I was just curious to have a look at the values from training data themselves.
But your asking actually lead me to a question about cross-validation output esp. for leave-one-out method. 
I noticed the harvest_attribs option in CrossValidatedTransferError, and was wondering whether the sensitivities or 
other measures harvested there should always be used in place of those from full dataset without cross-validation. 
For sensitivity particularly, CrossValidatedTransferError gives a set of sens values for each run, and I'm not sure 
how could they be summed up. In SMLR for instance, I guess there might be tiny shifts of selected voxels in each 
leave-one-out run. Would a mean across runs still be a valid sensitivity? Any suggestions on that?

Thanks again for your response!

Best, Frank


> Yeah the dot_prod is not that important. I just tried to get a little more idea about how it works.
> Have a nice weekend!
U2 ;-)

> Best, Frank
-- 
Yaroslav Halchenko
Research Assistant, Psychology Department, Rutgers-Newark
Student  Ph.D. @ CS Dept. NJIT
Office: (973) 353-1412 | FWD: 82823 | Fax: (973) 353-1171
        101 Warren Str, Smith Hall, Rm 4-105, Newark NJ 07102
WWW:    http://www.linkedin.com/in/yarik        

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---------------------------
Daqiang Sun
Clinical Neuroscience Lab
Department of Psychology
UCLA
---------------------------