I have a classifier which derives from RandomForestClassifier, in order to implement a custom "score" method. This obviously affects scoring results obtained with cross-validation, but I observed that it seems to also affect the actual predictions. In other words, the same RF classifier with two different scoring functions will produce different predictions. Perhaps I'm confused, but this doesn't seem obvious to me, as I assumed that the scoring mechanism was somewhat independent from the training one. So my question is: does a classifier's "score" method play any role in the working of its "fit" method?
------------------------------------------------------------------------------ Got visibility? Most devs has no idea what their production app looks like. Find out how fast your code is with AppDynamics Lite. http://ad.doubleclick.net/clk;262219671;13503038;y? http://info.appdynamics.com/FreeJavaPerformanceDownload.html _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
