> Well, it's a tradeoff: a good reimplementation that would approach the > original in terms of performance is a lot of work. For it to be > sustainable, the team would have to grow a fair amount.
It is a lot of work but the bindings have caused us lots of problems so far (memory leaks, sign switched etc). I would also like to point out that the wrapper for the cross-validation in libsvm probably doesn't work. In the long term, we should aim for a Cython port of libsvm and liblinear. Being able to work directly on the native ndarray is invaluable and with the forthcoming fused types in Cython, we would be able to use arbitrary dtype. David mentioned that it would make a good GSOC. A good programmer should be able to translate the code fairly easily, even without much SVM knowledge. liblinear and libsvm have been patched in scikit-learn and I believe it would be hard to keep the libraries up-to-date. Mathieu ------------------------------------------------------------------------------ Virtualization & Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
