ps. a quick update, the notebook now matches the code in the branch.
On Tue, Sep 16, 2014 at 9:54 PM, <[email protected]> wrote:
> satra,
>
> thanks so much for pointing me to this. much appreciated!
>
> best,
> kc
>
> > hi kc,
> >
> > it's not in scikit learn but we use these quite routinely alongside
> > scikit-learn.
> >
> > https://github.com/scikit-learn/scikit-learn/pull/2730
> >
> > here is also a set a notebook showing manifold extraction using diffusion
> > embedding. the notebook is a little out of date with respect to the code.
> > it also contains a basic procrustean alignment as well.
> >
> >
> http://nbviewer.ipython.org/urls/dl.dropbox.com/s/qzavpq8pchbh97o/DiffusionMaps-Comparison.ipynb?dl=0
> >
> > i think the notebook is quite convincing how the diffusion embedding
> > methods are superior to the other scikit-learn manifold embedders at
> least
> > for trivial cases.
> >
> > for full inclusion, besides the powers that be being convinced that this
> > is
> > a relatively small change and that it's performance outweighs the other
> > manifold learning methods, the PR definitely needs to be cleaned up,
> > together with full support for sparse matrices. thus far i have been
> happy
> > to just keep the PR and use the code for my needs.
> >
> > cheers,
> >
> > satra
> >
> > On Tue, Sep 16, 2014 at 8:27 PM, <[email protected]> wrote:
> >
> >> Has anyone worked on the problem of manifold alignment?
> >>
> >> http://en.wikipedia.org/wiki/Manifold_alignment
> >>
> >> as described in papers like:
> >>
> >> "Manifold Alignment without Correspondence"
> >> http://ijcai.org/papers09/Papers/IJCAI09-214.pdf
> >>
> >> or
> >>
> >> "Data Fusion and Multi-Cue Data Matching by Diffusion Maps"
> >> http://people.ee.duke.edu/~lcarin/data_fusion_by_diffusion_maps.pdf
> >>
> >> or in CH. 5 of "Manifold Learning Theory and Applications"
> >>
> >> If not, is anyone interested in working on this? I would be happy to
> >> help.
> >>
> >> Best,
> >> kc
> >>
> >>
> >>
> >>
> >>
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