Unbiased feature selection in learning random forests for high-dimensional data.Random forests (RFs) have been widely used as a powerful classification method.  The experimental results have shown that RFs with the proposed approach outperformed the existing random forests in increasing the accuracy and the AUC measures.
Random Forests
Aiming at debiasing feature selection in RFs, we propose a new RF algorithm, called xRF, to select good features in learning RFs for high-dimensional data. 
xRF