Hi Lukas, the impurity (in your case entropy) is simply averaged over all outputs - see [1] - the code is written in cython (a python dialect that translates to C).
best, Peter [1] https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/tree/_tree.pyx#L1482 2013/2/4 Ribonous <[email protected]>: > I think I understand how a random forest classifier works in the univariate > case. Unfortunately I haven't found much information about how to implement > random forest classifier in the multi-output case. > > How does the random forest classifier in sklearn measure the information > gain for a given split in the multi-output case ? Can anyone point me to > references on this? > > Also, is the random forest implementation written in Python or another > language? > > Thanks, > > Lukas > > > > ------------------------------------------------------------------------------ > 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_jan > _______________________________________________ > 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_jan _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
