For calculating global feature importance using Shapley values.
Project description
SAGE (Shapley Additive Global importancE) is a game theoretic approach for understanding black-box machine learning models. It summarizes the importance of each feature based on the predictive power it contributes, accounting for complex interactions by using the Shapley value from cooperative game theory. See the GitHub page for examples, and see the paper for more details.
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