27 citations · 37 across the 6 of their papers we have counts for
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stat.ML2019
Fréchet random forests for metric space valued regression with non euclidean predictors
Louis Capitaine, Jérémie Bigot, Rodolphe Thiébaut +1
Random forests are a statistical learning method widely used in many areas of scientific research because of its ability to learn complex relationships between input and output var…
stat.ME2019
Random forests for high-dimensional longitudinal data
Louis Capitaine, Robin Genuer, Rodolphe Thiébaut
Random forests is a state-of-the-art supervised machine learning method which behaves well in high-dimensional settings although some limitations may happen when , the number of…