On Tue, Sep 20, 2011 at 04:25:58PM -0700, Jacob VanderPlas wrote: > 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:
Just a quick answer from someone who does too many things: - It is a general pattern that can be found with many other algorithms, therefore I think that it should be in the scikit - I don't know what interface is the right, but the problem pops up at many different places in the scikit, and we should give it some thoughts. my 2 cents, G ------------------------------------------------------------------------------ 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
