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Diet Modelling: Combining Mathematical Programming Models with Data-Driven Methods

  • Ante IvancicEmail author
  • Argyris Kanellopoulos
  • Johanna M. Geleijnse
Conference paper
  • 116 Downloads
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 554)

Abstract

Mathematical programming has been the principal workhorse behind most diet models since the 1940s. As a predominantly hypothesis-driven modelling paradigm, its structure is mostly defined by a priori information, i.e. expert knowledge. In this paper we consider two machine learning paradigms, and three instances thereof that could help leverage the readily available data and derive valuable insights for modelling healthier, and acceptable human diets.

Keywords

Machine learning Diet modelling Consumer preferences 

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Copyright information

© IFIP International Federation for Information Processing 2020

Authors and Affiliations

  • Ante Ivancic
    • 1
    Email author
  • Argyris Kanellopoulos
    • 1
  • Johanna M. Geleijnse
    • 1
  1. 1.Wageningen University and ResearchWageningenThe Netherlands

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