Machine learning approaches for enhancing decision-making in complex discrete choice tasks show potential for policy-based preference elicitation over traditional parametric models
Read the original at arxiv.org→arXiv:2607.28854v1 Announce Type: new Abstract: Discrete choice modeling is a common tool used for preference elicitation during policy-making, but this is typically done through parametric models. Machine learning...
Original headline: "An analysis of machine learning approaches for enhancing decision-making in complex discrete choice tasks"
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- Aug 3, 04:00 UTC arXiv cs.LG lead source An analysis of machine learning approaches for enhancing decision-making in complex discrete choice tasks