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cs.AI2023
Feature Importance versus Feature Influence and What It Signifies for Explainable AI
Kary Främling
When used in the context of decision theory, feature importance expresses how much changing the value of a feature can change the model outcome (or the utility of the outcome), com…
cs.HC2023
Context, Utility and Influence of an Explanation
Minal Suresh Patil, Kary Främling
Contextual utility theory integrates context-sensitive factors into utility-based decision-making models. It stresses the importance of understanding individual decision-makers' pr…
cs.LG2023
Do intermediate feature coalitions aid explainability of black-box models?
Minal Suresh Patil, Kary Främling
This work introduces the notion of intermediate concepts based on levels structure to aid explainability for black-box models. The levels structure is a hierarchical structure in w…