To be clear, LLE's weights are found via a linear solution involving covariances of local neighborhoods, which can be constructed from a matrix of pairwise distances in a way analogous to that of metric MDS. Jake
Matthieu Brucher wrote: > Hi, > > I think some of the algorithms already offer this (Laplacian Eigenmaps > for instance). > I'm -1 for LLE as LLE does not compute distances, but weights based on > the points directly. > > Matthieu > > 2011/9/21 Jacob VanderPlas <[email protected] > <mailto:[email protected]>> > > Hello, > I recently was contacted by someone interested in using manifold > learning methods on abstract metric spaces: that is, the training data > is a matrix of pairwise distances rather than a set of points. It > would > be fairly straightforward to implement this for basic LLE and Isomap, > and could probably be done for the other manifold methods as well. > Two > questions: > 1) does this seem like a feature worth including in scikit-learn? Are > there common use-cases people can think of? > 2) any ideas about the best interface to allow this? Because the > format > of the input is so different from the normal use-case, it may be > best to > make it a separate estimator. Perhaps `MetricLLE`, `MetricIsomap` or > something similar. Another option would be to have a keyword > similar to > the `kernel='precomputed'` option in `KernelPCA`. > Any thoughts? > Jake > > > ------------------------------------------------------------------------------ > All the data continuously generated in your IT infrastructure > contains a > definitive record of customers, application performance, security > threats, fraudulent activity and more. Splunk takes this data and > makes > sense of it. Business sense. IT sense. Common sense. > http://p.sf.net/sfu/splunk-d2dcopy1 > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > <mailto:[email protected]> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > > -- > Information System Engineer, Ph.D. > Blog: http://matt.eifelle.com > LinkedIn: http://www.linkedin.com/in/matthieubrucher > ------------------------------------------------------------------------ > > ------------------------------------------------------------------------------ > All the data continuously generated in your IT infrastructure contains a > definitive record of customers, application performance, security > threats, fraudulent activity and more. Splunk takes this data and makes > sense of it. Business sense. IT sense. Common sense. > http://p.sf.net/sfu/splunk-d2dcopy1 > ------------------------------------------------------------------------ > > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity and more. Splunk takes this data and makes sense of it. Business sense. IT sense. Common sense. http://p.sf.net/sfu/splunk-d2dcopy1 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
