Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions

@article{Wang2019DeepNN,
  title={Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions},
  author={Shenhao Wang and J. Zhao},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.07481}
}
  • Shenhao Wang, J. Zhao
  • Published 2019
  • Mathematics, Engineering, Computer Science, Economics
  • ArXiv
  • Whereas deep neural network (DNN) is increasingly applied to choice analysis, it is challenging to reconcile domain-specific behavioral knowledge with generic-purpose DNN, to improve DNN's interpretability and predictive power, and to identify effective regularization methods for specific tasks. This study designs a particular DNN architecture with alternative-specific utility functions (ASU-DNN) by using prior behavioral knowledge. Unlike a fully connected DNN (F-DNN), which computes the… CONTINUE READING

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