Comments on: "A Random Forest Guided Tour" by G. Biau and E. Scornet

Sylvain Arlot (1, 2) , Robin Genuer (3, 4)

1 LMO - Laboratoire de Mathématiques d'Orsay
2 SELECT - Model selection in statistical learning
3 ISPED - Institut de Santé Publique, d'Epidémiologie et de Développement
4 SISTM - Statistics In System biology and Translational Medicine

This paper is a comment on the survey paper by Biau and Scornet (2016) about random forests. We focus on the problem of quantifying the impact of each ingredient of random forests on their performance. We show that such a quantification is possible for a simple pure forest , leading to conclusions that could apply more generally. Then, we consider " hold-out " random forests, which are a good middle point between " toy " pure forests and Breiman's original random forests.

Mots clés: random forests; estimation error; approximation error; subagging; bagging; hold-out random forests

Domaines: Statistiques [math.ST]; Théorie [stat.TH]; Méthodologie [stat.ME]; Machine Learning [stat.ML]

Sylvain Arlot, Robin Genuer. Comments on: "A Random Forest Guided Tour" by G. Biau and E. Scornet. Test, 2016, 25 (2), pp.228--238. ⟨10.1007/s11749-016-0484-4⟩. ⟨hal-01297557⟩