2013/3/15 Conrad Lee <conrad...@gmail.com>: > The server will handle requests in parallel. Most requests will include a > feature vector, and for these I will return a prediction by calling the > 'predict' or 'predict_proba' method on the classifier. If the server has > several threads running concurrently, can they all simultaneously make calls > to the classifier's predict method without causing problems?
That should be no problem. In recent versions, predict is just a few NumPy operations. > What if one of these threads calls the fit() method, while others are still > calling predict? I suspect that will cause problems... That's undefined behavior. We don't atomically set the intercept_ and coef_, and I don't think we should try to do that. If memory permits, just fit a new model and atomically replace your old one. -- Lars Buitinck Scientific programmer, ILPS University of Amsterdam ------------------------------------------------------------------------------ Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://p.sf.net/sfu/appdyn_d2d_mar _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
