The Use of Binary Choice Forests to Model and Estimate Discrete Choices

arXiv:1908.01109v5 Announce Type: replace-cross
Abstract: Problem definition. In retailing, discrete choice models (DCMs) are commonly used to capture the choice behavior of customers when offered an assortment of products. When estimating DCMs using transaction data, flexible models (such as machine learning models or nonparametric models) are typically not interpretable and hard to estimate, while tractable models (such as the multinomial logit model) tend to misspecify the complex behavior represeted in the data. Methodology/results. In this study, we use a forest …

abstract arxiv behavior binary cs.lg customers data definition econ.em forests machine machine learning machine learning models products retailing stat.ml transaction data type