[SciPy-dev] Google Summer of Code and scipy.learn (another trying)

Matthieu Brucher matthieu.brucher at gmail.com
Mon Mar 24 12:05:53 EDT 2008


Hi ;)

2008/3/24, Yaroslav Halchenko <lists at onerussian.com>:
>
> Hi Anton,
>
> Thank you for the positive feedback. Let me introduce myself briefly: I
> am one of the authors of PyMVPA and met Jarrod at NiPy coding sprint at
> Paris. There we met with another group (of Jean B. Poline) which
> develops analogous (yet closed source but due to our persuasion
> hopefully open-source soon) toolbox. Although we had a lot of ideas in
> common, some aspects were conceptually different (unfortunately I've
> forgotten exact name of their toolbox: mindmine, or smth like that)
>
> In the case of our PyMVPA we tried to build up a framework where it is
> possible
> to combine various ML boxes together via parametrization of the classes in
> the
> constructors. That could serve an equivalent role to those GUI-based
> frameworks
> where you build your analysis from blocks by connecting them with "lines".
> And
> the whole PyMVPA computation pipeline is initiated whenever resultant
> object
> sees some data (like within train() of a classifier). It is also somewhat
> similar to approach taken by MDP guys (http://mdp-toolkit.sourceforge.net/
> ).
> Also we have similar approach to existing scikits.learn to abstract all
> relevant data within a Dataset class. The primary user-base we target
> originally with PyMVPA is brainimaging research community, thus we had to
> provide not only simple blocks but somewhat obvious and straightforward to
> use
> software and a reasonable documentation. That could  cost us little loss
> of generality, although I don't see it happening yet ;-)



Indeed, the framework is great and is easy to use.
I have an additional question I forgot to ask during the sprint. You didn't
show an exemple of a classification training and then a single test. For
instance, train a SVM and then test one image (for SVMs, it is now needed to
be able to get the underlying cost function, more and more publications use
it to show interesting results, and it is what could be thought as a state
in your framework ?). This is expecting when testing one individual versus
two groups (it is done in anatomic brainimaging). Could you add an exemple
with this ?

I also know that Windows is not very tested for the moment, I hope the mix
with scikits.learn will help promoting your tool and fix the different bugs
that will be found (or not if there are no bugs :D) with other platforms.

Matthieu
-- 
French PhD student
Website : http://matthieu-brucher.developpez.com/
Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92
LinkedIn : http://www.linkedin.com/in/matthieubrucher
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