jmlr jmlr2008 jmlr2008-25 jmlr2008-25-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Gérard Biau, Luc Devroye, Gábor Lugosi
Abstract: In the last years of his life, Leo Breiman promoted random forests for use in classification. He suggested using averaging as a means of obtaining good discrimination rules. The base classifiers used for averaging are simple and randomized, often based on random samples from the data. He left a few questions unanswered regarding the consistency of such rules. In this paper, we give a number of theorems that establish the universal consistency of averaging rules. We also show that some popular classifiers, including one suggested by Breiman, are not universally consistent. Keywords: random forests, classification trees, consistency, bagging This paper is dedicated to the memory of Leo Breiman.