Abstract Functional Magnetic Resonance Imaging (fMRI) is presently one of the most
popular techniques for analysing the dynamic states in brain images using various kinds of …

The general principle of random forests is to aggregate a collection of random decision
trees. The goal is, instead of seeking to optimize a predictor “at once” as for a CART tree, to …

This paper describes the R package VSURF. Based on random forests, and for both
regression and classification problems, it returns two subsets of variables. The first is a …

This paper proposes, focusing on random forests, the increasingly used statistical method
for classification and regression problems introduced by Leo Breiman in 2001, to investigate …

Random Forests are frequently applied as they achieve a high prediction accuracy and have
the ability to identify informative variables. Several approaches for variable selection have …

Since vegetation in urban areas delivers crucial ecological services as a support to human
well-being and to the urban population in general, its monitoring is a major issue for urban …

A detailed and state-of-the-art landslide inventory map including precise landslide location
is greatly required for landslide susceptibility, hazard, and risk assessments. Traditional …

Nearly a quarter of bipolar disorder (BD) patients were misdiagnosed as major depressive
disorder (MDD) patients, which cannot be corrected until mania/hypomania develops. It is …

The discovery of cancer of unknown primary (CUP) is of great significance in designing
more effective treatments and improving the diagnostic efficiency in cancer patients. In the …

Deux des algorithmes proposés par Leo Breiman: les arbres CART (pour Classification And
Regression Trees) introduits dans la première moitié des années 80 et les forêts aléatoires …