[SciPy-dev] Scikit for manifold learning techniques
Wed Dec 5 13:41:17 CST 2007
Matthieu Brucher wrote:
> 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 optimizers).
> 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.
> Comments ?
I'd love to have them!
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
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