2012/7/30 Gael Varoquaux <[email protected]>: > On Mon, Jul 30, 2012 at 11:43:01AM +0200, Olivier Grisel wrote: >> This could be worked around by chunking the data argument of the >> predict calls instead. > > Indeed. > > In addition, a voronoi tessalation computed with a KMeans during the > train could be used to avoid testing all the samples in the large n > situation.
Hum, that won't work for exact k-NN. Approximate k-NN would be useful to have but this is another story and is already very well implemented in flann: http://people.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
