Discrete Choice Models

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Most implemented papers archive 2025-07-28

16 shown of 16 papers with code (104 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Representing Random Utility Choice Models with Neural Networks
  26 Jul 2022 2 repositories listed
  Motivated by the successes of deep learning, we propose a class of neural network-based discrete choice models, called RUMnets, inspired by the random utility maximization (RUM) framework.
• A Neural-embedded Choice Model: TasteNet-MNL Modeling Taste Heterogeneity with Flexibility and Interpretability
  3 Feb 2020 2 repositories listed
  Our formulation consists of two modules: a neural network (TasteNet) that learns taste parameters (e.
• Enhancing Discrete Choice Models with Representation Learning
  23 Dec 2018 2 repositories listed
  In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates.
• Choice-Learn: Large-scale choice modeling for operational contexts through the lens of machine learning
  10 Sep 2024 1 repository listed
  The higher-level is designed for fast and easy implementation and the lower-level enables more advanced parameterizations.
• The Mixed Aggregate Preference Logit Model: A Machine Learning Approach to Modeling Unobserved Heterogeneity in Discrete Choice Analysis
  31 Jan 2024 1 repository listed
  The traditional mixed logit model (also known as "random parameters logit'') parameterizes preference heterogeneity through assumptions about feature-specific heterogeneity distributions.
• A prediction and behavioural analysis of machine learning methods for modelling travel mode choice
  11 Jan 2023 1 repository listed
  The answer to this question goes beyond simple predictive performance, and is instead a balance of many factors, including behavioural interpretability and explainability, computational complexity, and data efficiency.
• Graph-Based Methods for Discrete Choice
  23 May 2022 1 repository listed
  We show that incorporating social network structure can improve the predictions of the standard econometric choice model, the multinomial logit.
• Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling
  31 Dec 2021 1 repository listed
  The problem of learning mixture of MNL models from partial rankings naturally arises in such applications.
• Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models
  25 Sep 2021 1 repository listed
  Although researchers increasingly adopt machine learning to model travel behavior, they predominantly focus on prediction accuracy, ignoring the ethical challenges embedded in machine learning algorithms.
• Combining Discrete Choice Models and Neural Networks through Embeddings: Formulation, Interpretability and Performance
  24 Sep 2021 1 repository listed
  The novelty of our work lies in enforcing interpretability to the embedding vectors by formally associating each of their dimensions to a choice alternative.
• Identification of Incomplete Preferences
  13 Aug 2021 1 repository listed
  We provide a sharp identification region for discrete choice models where consumers' preferences are not necessarily complete even if only aggregate choice data is available.
• Choice Set Confounding in Discrete Choice
  17 May 2021 1 repository listed
  Standard methods in preference learning involve estimating the parameters of discrete choice models from data of selections (choices) made by individuals from a discrete set of alternatives (the choice set).
• Semi-Discrete Optimal Transport: Hardness, Regularization and Numerical Solution
  10 Mar 2021 1 repository listed
  Semi-discrete optimal transport problems, which evaluate the Wasserstein distance between a discrete and a generic (possibly non-discrete) probability measure, are believed to be computationally hard.
• Robust discrete choice models with t-distributed kernel errors
  14 Sep 2020 1 repository listed
  In a case study on transport mode choice behaviour, MNR and Gen-MNR outperform MNP by substantial margins in terms of in-sample fit and out-of-sample predictive accuracy.
• Choice Set Optimization Under Discrete Choice Models of Group Decisions
  2 Feb 2020 1 repository listed
  The way that people make choices or exhibit preferences can be strongly affected by the set of available alternatives, often called the choice set.
• A branch-and-cut algorithm for the latent-class logit assortment problem
  14 Feb 2014 1 repository listed
  We study the product assortment problem of a retail operation that faces a stream of customers who are heterogeneous with respect to preferences.