Before revision:  We show that the approximate  Shapley value of classifiers in these games is an adequate measure for selecting a subgroup of highly predictive models . In addition, we introduce the Shapley entropy a new metric to quantify the heterogeneity of machine learning ensembles when it comes to model quality. We analytically prove that our Shapley value approximation algorithm is accurate and scales to large ensembles and big data.
After revision:  We show that the approximate Shapley value of classifiers in these games is an effective decision metric for choosing a high performing subset of models from the ensemble. Our analytical findings prove that our Shapley value approximation algorithm is accurate and scales to large ensembles and big data.