A method that translates causal relationships into a Bipolar Argumentation Framework and applies semi-stable semantics to generate explanatory feature sets for machine learning predictions.
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A Causal Argumentation Method for Explainability of Machine Learning Models
A method that translates causal relationships into a Bipolar Argumentation Framework and applies semi-stable semantics to generate explanatory feature sets for machine learning predictions.