> On 27 Jul 2021, at 11:08, Sole Galli via scikit-learn > <scikit-learn@python.org> wrote: > > Hello community, > > Do I understand correctly that Random Forests are trained as a 1 vs rest when > the target has more than 2 classes? Say the target takes values 0, 1 and 2, > then the model would train 3 estimators 1 per class under the hood?.
Each decision tree of the forest is natively supporting multi class. > > The predict_proba output is an array with 3 columns, containing the > probability of each class. If it is 1 vs rest. am I correct to assume that > the sum of the probabilities for the 3 classes should not necessarily add up > to 1? are they normalized? how is it done so that they do add up to 1? According to the above answer, the sum for each row of the array given by `predict_proba` will sum to 1. According to the documentation, the probabilities are computed as: The predicted class probabilities of an input sample are computed as the mean predicted class probabilities of the trees in the forest. The class probability of a single tree is the fraction of samples of the same class in a leaf. > > Thank you > Sole > > > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
