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Open Access

Peer-reviewed

Research Article

A model based on Bayesian confirmation and machine learning algorithms to aid archaeological interpretation by integrating incompatible data

Daniella Vos ,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Visualization, Writing – original draft, Writing – review & editing

* E-mail: d.vos@rug.nl

Current Address: Department of Cultural Geography, Faculty of Spatial Sciences, University of Groningen, Groningen, The Netherlands

Affiliation Department of Archaeology and Anthropology, Faculty of Science and Technology, Bournemouth University, Poole, United Kingdom

https://orcid.org/0000-0003-2938-8857

⨯
Richard Stafford,

Roles Formal analysis, Methodology, Software, Validation, Writing – review & editing

Affiliation Department of Life and Environmental Sciences, Faculty of Science and Technology, Bournemouth University, Poole, United Kingdom
⨯
Emma L. Jenkins,

Roles Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing

Affiliation Department of Archaeology and Anthropology, Faculty of Science and Technology, Bournemouth University, Poole, United Kingdom
⨯
Andrew Garrard

Roles Resources, Writing – review & editing

Affiliation Institute of Archaeology, University College London, London, United Kingdom
⨯

A model based on Bayesian confirmation and machine learning algorithms to aid archaeological interpretation by integrating incompatible data

Daniella Vos,
Richard Stafford,
Emma L. Jenkins,
Andrew Garrard

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Published: March 31, 2021
https://doi.org/10.1371/journal.pone.0248261

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