[pymvpa] retraining

[Yaroslav Halchenko]

heh heh... indeed... phd defense tomorrow... computers/software does not
cooperate etc...

so... retraining -- it is only partially implemented now in pymvpa

sg.SVM
SVR

have some retraining capabilities and in sg.SVM it is somewhat messy...
in SVR it is somewhat not working (as I discovered recently while
changing kernel parameters).


but those are the codes which you can check out to start crafting your
way through 'retraining' -- it should help in many cases (lots of
features, not that many samples -- so whenever lots of time is taken to
precompute the kernels). It should be really nice to have in SMLR... but
it is not there.  Meta classifiers (split,featureselection) also do not
have it all now (iirc).

I will come back to it after this Wed ;) but you are welcome to inspect
what is already done and suggest what should be done

On Mon, 30 Mar 2009, Michael Hanke wrote:

> Hi Scott,

> On Mon, Mar 30, 2009 at 02:01:06PM -0400, Scott Gorlin wrote:
> > Hi guys,

> > What's the latest thoughts on precalculated/retrainable classifiers?  
> > I.e., it could greatly speed up cross-validated model selection... it 
> > looks like libsvm's precomputed kernel isn't implemented though, is this 
> > due to a wrapper limitation?  Or are people generally using other 
> > classifiers which have clf.retrain() implemented?

> > If I were to implement this, any tips on where to begin?

> Yarik is the expert on classifier retraining, but he is currently quite
> busy and it might take a while until he can reply...


> Michael
-- 
Yaroslav Halchenko
Research Assistant, Psychology Department, Rutgers-Newark
Student  Ph.D. @ CS Dept. NJIT
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