This article addresses current methodological research on non-parametric Random Forests. It provides a brief intellectual history of Random Forests that covers CART, boosting and bagging methods. It then introduces the primary methods by which researchers can visualize results, the relationships between covariates and responses, and the out-of-bag test set error. In addition, the article considers current research on universal consistency and importance tests in Random Forests. Finally, several uses for Random Forests are discussed, and available software is identified.
- Algorithmic methods
- Ensemble and committee methods
- Random forests
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty