AI RESEARCH
Decomposing Observational Multiplicity in Decision Trees: Leaf and Structural Regret
arXiv CS.LG
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ArXi:2603.11701v1 Announce Type: cross Many machine learning tasks admit multiple models that perform almost equally well, a phenomenon known as predictive multiplicity. A fundamental source of this multiplicity is observational multiplicity, which arises from the stochastic nature of label collection: observed