
This study proposes a new explainable artificial intelligence (XAI) framework that combines causal structure information and causal discovery to provide counterfactual explanations for black-box machine learning models, even when the causal graph is unknown.


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counterfactual-explanations-of-black-box-machine-learning-models-using-causal-discovery-with-applications-to-credit-rating


Counterfactual Explanations of Black-box Machine Learning Models using Causal Discovery with Applications to Credit Rating
