Efficient Approximation of Marginal and Coalitional Explainers using Monte Carlo Sampling

The authors design fast and accurate Monte Carlo sampling algorithms to approximate marginal game values, quotient game values, and coalitional values, which are used for interpreting the contributions of predictors in machine learning models.