Hi, you should look into partial dependence plots [1] - they summarize the effect of certain features on the target response. Currently, our PDPs only support GradientBoostingRegressor/Classifier.
[1] http://scikit-learn.org/stable/modules/ensemble.html#partial-dependence best, Peter 2013/2/26 <[email protected]>: > Hello, > I have been looking for a way to export the boost classifiers. I know that I > could print all the trees, but if I have 100 estimators, it starts to be not > a good idea. I was thinking on a way to summarize it printing the > weaklearners and its weigth. There is an easy way to do that? > > thanks for all > > Jordi > > > ------------------------------------------------------------------------------ > 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_feb > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- Peter Prettenhofer ------------------------------------------------------------------------------ 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_feb _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
