9.6 SHAP (SHapley Additive exPlanations)

Machine learning algorithms usually operate as black boxes and it is unclear how they derived a certain decision. This book is a guide for practitioners to make machine learning decisions interpretable.

SHapley Additive exPlanations (SHAP) procedure. (A) Conceptual

Interpretable Machine Learning: A Guide For Making Black Box Models Explainable : Molnar, Christoph: : Books

Measuring feature importance, removing correlated features, by Manish Chablani

9.6 SHAP (SHapley Additive exPlanations)

Interpretation of Black Box using SHapley Additive exPlanations

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9.2 Local Surrogate (LIME) Interpretable Machine Learning

8 Shapley Additive Explanations (SHAP) for Average Attributions

SHAP : A Comprehensive Guide to SHapley Additive exPlanations

8 Shapley Additive Explanations (SHAP) for Average Attributions

The Pitfalls of Mining for QuantiFERON Gold in Severely Ill Patients With COVID-19 - ScienceDirect

Understanding SHAP for Interpretable Machine Learning