Artificial Intelligence Colloquium - Maximilian Muschalik MSc, Ludwix Maximilian University, Munich

Title: Shapley Interaction Explanations with shapiq

Abstract:

Shapley values, as computed via SHAP, are a widely used tool for computing local feature importance in machine learning models, thanks to their strong foundation in game theory and model-agnostic nature, which make them a highly flexible tool. Shapley Interactions extend the concept of Shapley values to any-order interactions allowing to disentangle higher- from lower-order effects. To compute these values, Shapley Interaction Quantification (SHAP-IQ) has been recently proposed as an extension of SHAP. This seminar will begin by introducing the game-theoretic foundations of Shapley values (SHAP), then transitioning to Shapley Interactions (SHAP-IQ), and it will conclude with a hands-on overview of the shapiq Python library.