AI RESEARCH
Quantifying Sensitivity for Tree Ensembles: A symbolic and compositional approach
arXiv CS.AI
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ArXi:2605.13830v1 Announce Type: new Decision tree ensembles (DTE) are a popular model for a wide range of AI classification tasks, used in multiple safety critical domains, and hence verifying properties on these models has been an active topic of study over the last decade. One such verification question is the problem of sensitivity, which asks, given a DTE, whether a small change in subset of features can lead to misclassification of the input.