[Pkg-exppsy-pymvpa] model selection and other questions
emanuele at relativita.com
Mon Mar 31 13:49:57 UTC 2008
I've just installed PyMVPA after reading Yaroslav's thread
on SciPy-dev. I work in machine learning and started to work
recently on fMRI data. Since I'd like to contribute to
scikits.learn (or better, to the effort of building machine
learning tools to NumPy/SciPy) I'm wondering which will be
the main machine learning framework for that community. As
long as I've understood there is still debate among learn
and PyMVPA but the latter is getting momentum (i.e., there
are people actually working on it).
So here are some questions:
- Is this the right place to discuss of PyMVPA? According to
the mailing list archives there is more mailing on SciPy-dev
- After the Paris' sprint, is there evidence that PyMVPA
will actually substitute scikits.learn in near future?
- Is there some model selection solution currently available
in PyMVPA? I mean something to infer hyperparameters of the
classifiers (like the sigma of the RBF kernel in SVMs) from
data? Libsvm provides some extra tools for grid search; I
work with optimization techniques that can be generalized to
many classifiers etc. What about PyMVPA?
More information about the Pkg-exppsy-pymvpa