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Found 2 papers, 2 papers with code
Generating Feasible and Plausible Counterfactual Explanations for Outcome Prediction of Business Processes
In recent years, various machine and deep learning architectures have been successfully introduced to the field of predictive process analytics.
Explainability in Process Outcome Prediction: Guidelines to Obtain Interpretable and Faithful Models
In this paper, we define explainability through the interpretability of the explanations and the faithfulness of the explainability model in the field of process outcome prediction.
Explainable artificial intelligence
Predictive Process Monitoring
