The paper proposes SIG, a graph and MILP-based summary of random forest decision rules that shows global feature interactions through pruned graphs and decision-feature interaction tables.
Classification and interaction in random forests,
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Surrogate Interpretable Graph for Random Decision Forests
The paper proposes SIG, a graph and MILP-based summary of random forest decision rules that shows global feature interactions through pruned graphs and decision-feature interaction tables.