hi conrad, that looks interesting however this implementation is not compatible with the scikit license ( GPLv3 ) so if we want it we'll have to reimplement it. I'll take a look at the paper to see how hard this would be.
Alex On Tue, Oct 4, 2011 at 3:28 PM, Conrad Lee <[email protected]> wrote: > I just noticed this recent paper on arXiv about faster hierarchical > clustering. The author has come up with algorithms to reduce the asymptotic > complexity of many variants from O(N^3) to O(N^2). Even better, he has come > up with a C++ implementation with a python/numpy interface that is drop-in > compatible with scipy.cluster.hierarchy. > I would take a crack at incorporating this into scikit-learn myself, but I > don't know the first thing about how to create python interfaces to C++ > code. But maybe one of you are interested. > Conrad > ------------------------------------------------------------------------------ > 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
