On Mon, Jan 23, 2012 at 5:34 AM, Andreas <[email protected]> wrote: > Hi everybody. > While reviewing the label propagation PR, I thought about the pairwise > rbf functions. > Would it be possible to compute an sparse, approximate RBF kernel matrix > using ball trees? > The idea would be that if the distance between two points is some > "large" multiple of gamma, the kernel can be assumed > to be zero. > Do you think this is feasible to implement and helpful for real data?
Locality Sensitive Hashing could be use for fast approximate radius search. The radius should be easy to determine: choose it such that the exponential approximately rounds to 0. Mathieu ------------------------------------------------------------------------------ Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
