Hi, I'm trying to optimize the time it takes to make a prediction with my model(s). I realized that when I perform feature selection during the model fit(), that these features are likely still computed when I go to predict() or predict_proba(). An optimization would then involve actually eliminating those features that aren't selected from my Pipeline altogether, instead of just selecting them.
Does sklearn already do this automatically? Or does this readjustment need to be done manually before serialization? thanks, Philip ------------------------------------------------------------------------------ Transform Data into Opportunity. Accelerate data analysis in your applications with Intel Data Analytics Acceleration Library. Click to learn more. http://pubads.g.doubleclick.net/gampad/clk?id=278785231&iu=/4140 _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
