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SupplementaryMaterial: ModelClassReliancefor RandomForests

Neural Information Processing Systems

The packages developed as part of this work are discussed below and made available via the above notebooks. This simply calls the code fromhttps://github.com/charliemarx/ Figure 1 shows the the diagnostic graphs as considered in [4]. Note that the notebook does not haveafixedseed and this instability can beexplored by re-runningthenotebook. SHAP values are calculated on an identical RandomForestClassifier as used for the RF MCR. Thegraphs generated bytheNotebooks areperMCR estimation method, rather thanthe comparison graphs shown in the paper.



Note that the regret ofthe algorithm in [1]satisfiesR(G,T) = O (ฮด(G)logn)

Neural Information Processing Systems

The bandit problem with graph feedback, proposed in [Mannor and Shamir, NeurIPS 2011], is modeled by a directed graphG = (V,E) where V is the collection of bandit arms, and once an arm is triggered, all its incident arms are observed.