Advantages of Synthetic Noise and Machine Learning for Analyzing Radioecological Data Sets

r2VIM: A new variable selection method for random forests in genome-wide association studies

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Prediction of fishing effort distributions using boosted regression trees

(2014) Candan U. Soykan et al.   ECOLOGICAL APPLICATIONS

The effect of splitting on random forests

(2014) Hemant Ishwaran   MACHINE LEARNING

Random generalized linear model: a highly accurate and interpretable ensemble predictor

(2013) Lin Song et al.   BMC BIOINFORMATICS

Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

(2012) Carsten F. Dormann et al.   ECOGRAPHY

High-Dimensional Variable Selection for Survival Data

(2010) Hemant Ishwaran et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Random survival forests

(2008) Hemant Ishwaran et al.   Annals of Applied Statistics