A note on the consistency of the random forest algorithm

Examples are given of data-generating models for which some versions of the random forest algorithm may fail to be consistent, or at least may be extremely slow to converge to the optimal predictor. The evidence provided for these properties is based on partly intuitive and partly rigorous arguments and on numerical experiments.