Explainable AI using expressive Boolean formulas

Understand

We propose and implement an interpretable machine learning classification model for Explainable AI (XAI) based on expressive Boolean formulas.

• Potential applications include credit scoring and diagnosis of medical conditions.
• The Boolean formula defines a rule with tunable complexity (or interpretability), according to which input data are classified.
• Such a formula can include any operator that can be applied to one or more Boolean variables, thus providing higher expressivity compared to more rigid rule-based and tree-based approaches.