An empirical comparison of the validity of a neural net based multinomial logit choice model to alternative model specifications
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Cited by:
- Arkoudi, Ioanna & Krueger, Rico & Azevedo, Carlos Lima & Pereira, Francisco C., 2023. "Combining discrete choice models and neural networks through embeddings: Formulation, interpretability and performance," Transportation Research Part B: Methodological, Elsevier, vol. 175(C).
- Ioanna Arkoudi & Carlos Lima Azevedo & Francisco C. Pereira, 2021. "Combining Discrete Choice Models and Neural Networks through Embeddings: Formulation, Interpretability and Performance," Papers 2109.12042, arXiv.org, revised Sep 2021.
- Lahoz, Lorena Torres & Pereira, Francisco Camara & Sfeir, Georges & Arkoudi, Ioanna & Monteiro, Mayara Moraes & Azevedo, Carlos Lima, 2023. "Attitudes and Latent Class Choice Models using Machine Learning," Journal of choice modelling, Elsevier, vol. 49(C).
- Harald Hruschka, 2007. "Using a heterogeneous multinomial probit model with a neural net extension to model brand choice," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(2), pages 113-127.
- Yafei Han & Francisco Camara Pereira & Moshe Ben-Akiva & Christopher Zegras, 2020. "A Neural-embedded Choice Model: TasteNet-MNL Modeling Taste Heterogeneity with Flexibility and Interpretability," Papers 2002.00922, arXiv.org, revised Jul 2022.
- Lorena Torres Lahoz & Francisco Camara Pereira & Georges Sfeir & Ioanna Arkoudi & Mayara Moraes Monteiro & Carlos Lima Azevedo, 2023. "Attitudes and Latent Class Choice Models using Machine learning," Papers 2302.09871, arXiv.org.
- Lang, Stefan & Steiner, Winfried J. & Weber, Anett & Wechselberger, Peter, 2015. "Accommodating heterogeneity and nonlinearity in price effects for predicting brand sales and profits," European Journal of Operational Research, Elsevier, vol. 246(1), pages 232-241.
- Sifringer, Brian & Lurkin, Virginie & Alahi, Alexandre, 2020. "Enhancing discrete choice models with representation learning," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 236-261.
- Han, Yafei & Pereira, Francisco Camara & Ben-Akiva, Moshe & Zegras, Christopher, 2022. "A neural-embedded discrete choice model: Learning taste representation with strengthened interpretability," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 166-186.
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