[pymvpa] Partial least square(PLS) analysis

[Yaroslav Halchenko]

Hi Per, Hi Zhen,

actually I think things are not that hopeless ;-)

PLS has been implemented in scikits.learn, so, most probably, there is
no need to reimplement it, unless you see some obvious drawbacks in
scikits.learn implementation(s)?  on PyMVPA side we have started
implementing a basic adapter to make scikits.learn machinery
easily pluggable within PyMVPA.  So, theoretically, you could already
started playing with something like

from scikits.learn.pls import PLSRegression as sklPLSRegression
pls = SKLLearnerAdapter(sklPLSRegression())

so pls should look like a regular PyMVPA learner.

But could you please very briefly describe what kind of a task you are
looking for to tackle with PLS, e.g. what would be your "targets" and where
within processing pipeline PLS would need to be used?

On Wed, 11 May 2011, Per B. Sederberg wrote:
> Hi Zonglei:

> I started to implement PLS in PyMVPA now almost 3 years ago, but never
> finished.  I still think it would be a good addition, but I don't have
> time to finish it up.  I'd love to replicate a good bit of the PLS
> functionality from the Rotman toolbox:

> http://www.rotman-baycrest.on.ca/index.php?section=84

> So, to my knowledge, there is no way to do it now, but I'd be happy to
> chat with someone who would like to take on finishing up this
> addition.

> Best,
> Per


> On Wed, May 11, 2011 at 9:48 PM, Zhen Zonglei <zonglei.fsl at gmail.com> wrote:
> > Dear all:
> >    Is there a easy way to do PLS analysis in Pymvpa?  I exepect to
> > investigate the correlation between neural patterns and a group of behavior
> > index, so I restort to PLS.
> > If you have any info on how to do this in pymvpa, please let me know.

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