2011/10/4 Alexandre Gramfort <[email protected]>: > 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.
Also there is a policy of trying to stay away from adding more C++ in the scikit code base because of the maintenance cost inherent to C++. Most of the time it is possible to implement as efficient code in pure numpy + cython with much shorter source code that is understandable by any python developer. cython further gives us robustness w.r.t. most common segfaulting and memory leaks bugs one typically encounter in a C++ code base & wrappers. cython also gives use the ability to pickle the fitted models for free. So +1 for reimplementing from the paper in cython if this algorithm is proved to be more performant that those already available in the scikit. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ 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
