XorSHAP: Privacy-Preserving Explainable AI for Decision Tree Models

ePrint Report: XorSHAP: Privacy-Preserving Explainable AI for Decision Tree Models

Dimitar Jetchev, Marius Vuille

Explainable AI (XAI) refers to the development of AI systems and machine learning models in a way that humans can understand, interpret and trust the predictions, decisions and outputs of these models. A common approach to explainability is feature importance, that is, determining which input features of the model have the most significant impact on the model prediction. Two major techniques for computing feature importance are …

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