Aleatoric uncertainty selects between counterfactual and feature-importance explanations, epistemic uncertainty rejects unreliable explanations, and correlation experiments support the rule.
A random forest with 100 estimators and a maximum depth of 4 is used
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Robust Explanations Through Uncertainty Decomposition: A Path to Trustworthier AI
Aleatoric uncertainty selects between counterfactual and feature-importance explanations, epistemic uncertainty rejects unreliable explanations, and correlation experiments support the rule.