Assisted specification of discrete choice models

نویسندگان

چکیده

Determining appropriate utility specifications for discrete choice models is time-consuming and prone to errors. With the availability of larger datasets, as number possible exponentially grows with variables under consideration, analysts need spend increasing amounts time on searching good through trial-and-error, while expert knowledge required ensure these are sound. This paper proposes an algorithm that aims at assisting modelers in their search. Our approach translates task into a multi-objective combinatorial optimization problem makes use variant variable neighborhood search generate sets promising model specifications. We apply both semi-synthetic data real mode datasets proof concept. The results demonstrate its ability provide relevant insights reasonable so effectively assist modeler developing interpretable powerful models.

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ژورنال

عنوان ژورنال: Journal of choice modelling

سال: 2021

ISSN: ['1755-5345']

DOI: https://doi.org/10.1016/j.jocm.2021.100285