Interpretable Artificial Intelligence: A Perspective of Granular Computing

Chapter 1 Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring

Chapter 2 Use of Visual Analytics (VA) in Explainable Artificial Intelligence (XAI): A Framework of Information Granules

Chapter 3 Visualizing the Behavior of Convolutional Neural Networks for Time Series Forecasting

Chapter 4 Beyond Deep Event Prediction: Deep Event Understanding Based on Explainable Artificial Intelligence

Chapter 6 Factual and Counterfactual Explanation of Fuzzy Information Granules

Chapter 7 Transparency and Granularity in the SP Theory of Intelligence and Its Realisation in the SP Computer Model

Chapter 8 Survey of Explainable Machine Learning with Visual and Granular Methods Beyond Quasi-Explanations

Chapter 10 Designing Explainable Text Classification Pipelines: Insights from IT Ticket Complexity Prediction Case Study

Chapter 11 A Granular Computing Approach to Provide Transparency of Intelligent Systems for Criminal Investigations

Chapter 12 RYEL System: A Novel Method for Capturing and Represent Knowledge in a Legal Domain Using Explainable Artificial Intelligence (XAI) and Granular Computing (GrC)