Feature importance: a closer look at Shapley values and LOCO
From MaRDI portal
Publication:6649135
DOI10.1214/24-sts937MaRDI QIDQ6649135
Isabella Verdinelli, Larry Alan Wasserman
Publication date: 5 December 2024
Published in: Statistical Science (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Distribution-Free Predictive Inference For Regression
- Controlling the false discovery rate via knockoffs
- Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance
- Bootstrapping and sample splitting for high-dimensional, assumption-lean inference
- Exploring Regression Structure Using Nonparametric Functional Estimation
- On Shapley Value for Measuring Importance of Dependent Inputs
- SHAPLEY EFFECTS FOR SENSITIVITY ANALYSIS WITH CORRELATED INPUTS: COMPARISONS WITH SOBOL' INDICES, NUMERICAL ESTIMATION AND APPLICATIONS
- Mean decrease accuracy for random forests: inconsistency, and a practical solution via the Sobol-MDA
- Nonparametric variable importance assessment using machine learning techniques
This page was built for publication: Feature importance: a closer look at Shapley values and LOCO