Fool SHAP with Stealthily Biased Sampling

1 code implementation • 30 May 2022 • Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara, Mario Marchand., Foutse khomh

SHAP explanations aim at identifying which features contribute the most to the difference in model prediction at a specific input versus a background distribution.

Fairness