By the way, I suspect that that predict method is also sub-optimal because, since the support vectors and the coefficients are stored in numpy arrays or scipy matrices, predict has to make the conversion to liblinear's model structure at every call. This is the price that we currently pay for picklability. However, predict is very simple to implement in pure-numpy so I think we should stop using the native library altogether for prediction.
Mathieu ------------------------------------------------------------------------------ All of the data generated in your IT infrastructure is seriously valuable. Why? It contains a definitive record of application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-d2dcopy2 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
