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 the notebook is a little out of date with respect to the code.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 >> >> >> >> >> ------------------------------------------------------------------------------ >> Want excitement? >> Manually upgrade your production database. >> When you want reliability, choose Perforce >> Perforce version control. Predictably reliable. >> >> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk >> _______________________________________________ >> Scikit-learn-general mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> > ------------------------------------------------------------------------------ > Want excitement? > Manually upgrade your production database. > When you want reliability, choose Perforce > Perforce version control. Predictably reliable. > http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk_______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
