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Studies in Computational Intelligence
Multi-label classification can be applied to study empirically discrete choice problems, in which each individual chooses more than one alternative. We applied the Classifier Chain (CC) method to transform the Generalized Maximum Entropy (GME) choice model from a single-label model to a multi-label model. The contribution of our CC-GME model lies in the advantages of both the GME and CC models. Specifically, the GME model can not only predict each individual's choice, but also robustly estimatedoi:10.1007/978-3-319-13449-9_13 fatcat:3xhqdtfjpfayhgud2xwi26emii