599 citations · 862 across the 35 of their papers we have counts for
4 papers · 1 filter
What's a good imputation to predict with missing values?
Marine Le Morvan, Julie Josse, Erwan Scornet +1
How to learn a good predictor on data with missing values? Most efforts focus on first imputing as well as possible and second learning on the completed data to predict the outcome…
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
Clément Bénard, Gérard Biau, Sébastien da Veiga +1
Interpretability of learning algorithms is crucial for applications involving critical decisions, and variable importance is one of the main interpretation tools. Shapley effects a…
Causal effect on a target population: a sensitivity analysis to handle missing covariates
Bénédicte Colnet, Julie Josse, Erwan Scornet +1
Randomized Controlled Trials (RCTs) are often considered the gold standard for estimating causal effect, but they may lack external validity when the population eligible to the RCT…
MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA
Clément Bénard, Sébastien da Veiga, Erwan Scornet
Variable importance measures are the main tools to analyze the black-box mechanisms of random forests. Although the mean decrease accuracy (MDA) is widely accepted as the most effi…