Re: [scikit-learn] impurity criterion in gradient boosted regression trees

The blog post from Matthew Drury sums it up well. The feature importance is indeed the Gini impurity. On Tue, May 9, 2017 at 8:34 AM, Olga Lyashevska wrote: > Hi all, > > I am trying to understand differences in feature importance plots obtained > with R package gbm and sklearn. Having compared

[scikit-learn] impurity criterion in gradient boosted regression trees

Hi all, I am trying to understand differences in feature importance plots obtained with R package gbm and sklearn. Having compared both implementation side by side it seems that the models are fairly similar, however feature importance plots are rather distinct. R uses empirical improvement