[SciPy-dev] Scikit for manifold learning techniques
Thu Dec 6 11:32:43 CST 2007
On Dec 5, 2007 10:04 AM, Matthieu Brucher <email@example.com> 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
> 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 ?
Another enthusiastic +1 from the peanut gallery!
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