Since, however, searching for a single globally best tree is computationally infeasible (a first approach involving dynamic programming was introduced by van Os and Meulman 2005), the random restriction of the splitting variables provides an easy and efficient way to generate locally suboptimal splits that can improve the global performance of an ensemble of trees. Alternative approaches that follow this rationale by introducing even more sources of randomness are outlined below.
