[SciPy-dev] Scikit for manifold learning techniques
Wed Dec 5 11:04:09 CST 2007
I'd like to create a new scikit (I know I didn't put much effort in the
optimizers, but it will change when I will have more time) for manifold
learning. At first, I'd like to implement some usual techniques like Isomap,
LLE (some are in neuroimaging I heard) with different levels of interaction.
I do this in my PhD thesis, so it is almost available like a scikit. It
would be a twin-like of the Dimensionality Reduction toolbox for MatLab but
with a different interaction : directly call the right global function (like
isomap, mds, nlm or gedodesicNLM ATM) or give directly to an optimizer the
cost function you want with a distance matrix (it will use my own
Eigenmaps will be available shortly (I have a referee that want it, so I
will implement it), it will use scipy.sparse, and I hope I'll be able to
propose two interfaces as well.
If everything goes smoothly, I'll propose my own dimensionality reduction
technique in the scikit as well.
French PhD student
Website : http://miles.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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