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Found 3 papers, 2 papers with code
Variable importance without impossible data
The most popular methods for measuring importance of the variables in a black box prediction algorithm make use of synthetic inputs that combine predictor variables from multiple subjects.
What makes you unique?
We use Shapley value to combine all of the reductions in log cardinality due to revealing a variable after some subset of the other variables has been revealed.
Cohort Shapley value for algorithmic fairness
Cohort Shapley value is a model-free method of variable importance grounded in game theory that does not use any unobserved and potentially impossible feature combinations.
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