Erwan Scornet

Trees, forests, and impurity-based variable importance

2020 · INRIA a CCSD electronic archive server

Tree ensemble methods such as random forests [Breiman, 2001] are very popular to handle high-dimensional tabular data sets, notably because of their good predictive accuracy. However, when machine learning is used for decision-making problems, settling …

A primer on linear classification with missing data

2024 · arXiv (Cornell University)

Supervised learning with missing data aims at building the best prediction of a target output based on partially-observed inputs. Major approaches to address this problem can be decomposed into $(i)$ impute-then-predict strategies, which first fill …