[SciPy-dev] [GSoC 2008]Machine learning package in SciPy

[Matthieu Brucher]

2008/3/11, Anton Slesarev <slesarev.anton at gmail.com>:
>
> David Cournapeau is maintaining the learn scikit. This is the main place
> > where machine learning code will be put.
> > For instance, there are classifiers (SVMs with libsvm) and there will be
> > in the near future the more used manifold learning techniques.
> >
> > I didn't understand what you meant by "you want to see common which
> > features was selected by different tools".
>
>
> I mean that if we have standard format for different classifiers we can
> compare their results, we can see intersection of features that have been
> selected. If we use different tools, it is need to make exhausting
> conversions between different formats.
>


Well, a classifier gives back the class to which a point belongs to, doesn't
it ? Do you mean adding probabilities ? It would depend on the kind of the
classifier (strong or fuzzy).
For the time being, David proposed a data format, at least for inputs. The
same format could be extended to output values (when it has sense).


Sparse matrix support must be made at the C level for libsvm, you should
> > have to ask Albert who wrapped libsvm.
>
>


I see. I say that it is good idea to write parsers for different data
> formats.
>


I agree, I hope that David will be able to finish the Scons build of numpy
and scipy so that he will be able to enhance his data format proposal :)

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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