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dc.contributor.authorMayer, Michael
dc.contributor.authorBourassa, Steven C.
dc.contributor.authorHoesli, Martin
dc.contributor.authorScognamiglio, Donato
dc.date.accessioned2022-04-21T10:37:01Z
dc.date.available2022-04-21T10:37:01Z
dc.date.issued2022-04-20
dc.identifier215286143
dc.identifierecad8529-ed73-46d9-a17d-12c706ecb1f0
dc.identifier85130528966
dc.identifier.citationMayer , M , Bourassa , S C , Hoesli , M & Scognamiglio , D 2022 , ' Machine Learning Applications to Land and Structure Valuation ' , Journal of Risk and Financial Management , vol. 15 , no. 5 , 193 . https://doi.org/10.3390/jrfm15050193en
dc.identifier.issn1911-8066
dc.identifier.otherSCOPUS: 85130528966
dc.identifier.otherORCID: /0000-0003-2173-1200/work/147046580
dc.identifier.urihttps://hdl.handle.net/2164/18462
dc.descriptionAcknowledgments: We thank Nicola Stalder and his IAZI team for preparing the dataset for the Swiss case study. The authors are grateful to the referees, whose feedback and comments have improved the quality of the paper.en
dc.format.extent24
dc.format.extent1633016
dc.language.isoeng
dc.relation.ispartofJournal of Risk and Financial Managementen
dc.subjectland and structure valuationen
dc.subjectmachine learningen
dc.subjectstructured additive regressionen
dc.subjectgradient boostingen
dc.subjectdeep learningen
dc.subjectinterpretabilityen
dc.subjecttransparencyen
dc.subjecthedonic modelingen
dc.subjectHF5601 Accountingen
dc.subject.lccHF5601en
dc.titleMachine Learning Applications to Land and Structure Valuationen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Accountancyen
dc.description.statusPeer revieweden
dc.identifier.doi10.3390/jrfm15050193


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