  Despite their performance and widespread use, little is known about the
theory of Random Forests. A major unanswered question is whether, or when, the
Random Forest algorithm is consistent. The literature explores various variants
of the classic Random Forest algorithm to address this question and known
short-comings of the method. This paper is a contribution to this literature.
Specifically, the suitability of grafting consistent estimators onto a shallow
CART is explored. It is shown that this approach has a consistency guarantee
and performs well in empirical settings.
