In addition to this, a tree, and even better an ensemble of trees, is able to approximate the XOR problem by means of a sequence of cutpoints driven by random fluctuations that are present in any real data set. In this case, the random preselection of splitting variables in random forests again increases the chance that a variable with a weak marginal effect is still selected, at least in some trees, because some of its competitors are not available.
