Re: [Scikit-learn-general] Random forests: Measuring information gain in multi-output

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 : > > I think I understand how a random forest classifier works in the > univariate > > case

[Scikit-learn-general] Random forests: Measuring information gain in multi-output

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