CONSISTENCY FOR A SIMPLE MODEL OF RANDOM FORESTS

A heuristic analysis is presented in this paper based on a simplified version of RF denoted RF0. The results from RF0 support the empirical results from RF. RF0 regression is consistent using a value of mtry that does not depend on the number of cases N The rate of convergence to the Bayes rule depends only on the number of strong variables and not on how many noise variables are also present.. This also implies consistency for the two class RF0 classification. The analysis also illuminates why RF is able to handle large numbers of input variables and what the role of mtry is.