2023
Stability of Random Forests and Coverage of Random-Forest Prediction Intervals
NeurIPS 2023poster
We establish stability of random forests under the mild condition that the squared response ($Y^2$) does not have a heavy tail. In particular, our analysis holds for the practical version of random forests that is implemented in popular packages like \texttt{randomForest} in \texttt{R}. Empirical re…