[pymvpa] libsvm dense arrays

[Yaroslav Halchenko]

Hi Scott,

> Been using pymvpa for a few months now and really enjoying it - thanks 
> for all the good work!
that is really great to hear, since so far we have just limited idea on
the amount and diversity of pymvpa users. So thanks for posting to the
list

> I was curious if it would be possible/useful to switch out the libsvm 
> backend to the dense version mentioned here: 
> http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#1.  They claim 
> approximately 40% increase in speed (though for much larger data sets 
> than normal for mri), and since all fmri data is dense, it seems a 
100% correct... especially taking into account that now considerate
amount of runtime is spent on just populating those 'sparse'
datastructures for libsvm, whenever they are not sparse at all.

> natural move to me.  Has anyone experimented with this?  Or is a similar 
> improvement already included in the pymvpa libsvm wrapper?  Or do you 
> think the performance increase would be negligible?
I think it would be considerable.

Have you though tried libsvm implementation which comes within shogun?
it should be more efficient (don't know from top of the head which
implementation is used there -- sparse or dense though)


But I am not sure if it is worth to rely on another part of libsvm if
shogun provides significant speed-up instead of libsvm... have you tried
SG's SVMs?

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