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Modeling Non-deterministic Human Behaviors in Discrete Food Choices

arXiv 2301.09454 ↗First posted 23 Jan 2023stat.ML cs.LG stat.APcited by 0

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Abstract (arXiv)

We establish a non-deterministic model that predicts a user's food preferences from their demographic information. Our simulator is based on NHANES dataset and domain expert knowledge in the form of established behavioral studies. Our model can be used to generate an arbitrary amount of synthetic datapoints that are similar in distribution to the original dataset and align with behavioral science expectations. Such a simulator can be used in a variety of machine learning tasks and especially in applications requiring human behavior prediction.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 46 references that are in the map. First posted on arXiv 23 Jan 2023.

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References · 3

  1. 2020Learning from Noisy Labels with Deep Neural Networks: A Surveycited by 580
  2. 2015Inverse Optimization with Noisy Datacited by 34
  3. 2019Cognitive Model Priors for Predicting Human Decisionscited by 24

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