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The last decade has witnessed a growing interest in random forest models which are recognized to exhibit good practical performance, especially in high-dimensional settings.
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An empirical comparison of ensemble methods based on classification trees
M. Hamza and D. Laroque · 2005
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Gene selection and classification of microarray data using random forest
R. Díaz-Uriarte and S. Alvarez de Andrés · 2006
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Extremely randomized trees
P. Geurts, D. Ernst, and L. Wehenkel · 2006
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Quantile regression forests
N. Meinshausen · 2006
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Consistency of random forests and other averaging classifiers
G. Biau, L. Devroye, and G. Lugosi · 2008
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New insights into approximate bayesian computation
G. Biau, F. Cérou, and A. Guyader · 2012
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Ensemble Machine Learning , chapter Random forest for bioinformatics, pages 307–323
Y. Qi · 2012
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Reinforcement learning trees
R. Zhu, D. Zeng, and M.R. Kosorok · 2012
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Concentration inequalities: A nonasymptotic theory of independence
S. Boucheron, G. Lugosi, and P. Massart · 2013
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Ranking forests
S. Clémençon, M. Depecker, and N. Vayatis · 2013
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Consistency of online random forests
M. Denil, D. Matheson, and N. de Freitas · 2013
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R. Genuer, J.-M. Poggi, and C. Tuleau · 2008
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Random survival forest
H. Ishwaran, U.B. Kogalur, E.H. Blackstone, and M.S. Lauer · 2008
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Randomized trees for human pose detection
G. Rogez, J. Rihan, S. Ramalingam, C. Orrite, and P. H. Torr · 2008
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Consistency of random survival forests
H. Ishwaran and U.B. Kogalur · 2010
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Analysis of a random forests model
G. Biau · 2012
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Mondrian forests: Efficient online random forests
B. Lakshminarayanan, D. M. Roy, and Y. W. Teh · 2014
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Ensemble trees and clts: Statistical inference for supervised learning
L. Mentch and G. Hooker · 2014
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E. Scornet, G. Biau, and J.-P. Vert · 2014
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Asymptotic theory for random forests
S. Wager · 2014
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Confidence intervals for random forests: The jackknife and the infinitesimal jackknife
S. Wager, T. Hastie, and B. Efron · 2014
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