AINeutralarXiv – CS AI · 7h ago5/10
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Explainable AI Through a Democratic Lens: DhondtXAI for D'Hondt-Projected Feature Attribution
Researchers introduce DhondtXAI, a novel explainable AI framework for tabular data that uses proportional representation principles (the D'Hondt rule) to attribute feature importance instead of relying on SHAP values. The method demonstrates high correlation with SHAP while offering complementary capabilities for handling feature interactions and alliances, validated across synthetic tests and healthcare datasets.