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Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis

Author(s): ORCID (Department of the Built Environment, College of Design and Engineering, National University of Singapore (NUS), Singapore, Singapore)
(Department of the Built Environment, College of Design and Engineering, National University of Singapore (NUS), Singapore, Singapore)
ORCID (Department of the Built Environment, College of Design and Engineering, National University of Singapore (NUS), Singapore, Singapore)
(Department of Biosystems, KU Leuven, Leuven, Belgium)
Medium: journal article
Language(s): English
Published in: Science and Technology for the Built Environment, , n. 5, v. 28
Page(s): 1-18
DOI: 10.1080/23744731.2022.2067466
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1080/23744731.2022.2067466.
  • About this
    data sheet
  • Reference-ID
    10665156
  • Published on:
    09/05/2022
  • Last updated on:
    16/06/2022
 
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