Machine-learning based reconstructions of primary and secondary climate variables from North American and European fossil pollen data

We test several quantitative algorithms as palaeoclimate reconstruction tools for North American and European fossil pollen data, using both classical methods and newer machine-learning approaches based on regression tree ensembles and artificial neural networks. We focus on the reconstruction of se...

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Detalles Bibliográficos
Autores principales: Salonen, J. Sakari, Korpela, Mikko, Williams, John W., Luoto, Miska
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825136/
https://www.ncbi.nlm.nih.gov/pubmed/31676769
http://dx.doi.org/10.1038/s41598-019-52293-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825136/
https://www.ncbi.nlm.nih.gov/pubmed/31676769
http://dx.doi.org/10.1038/s41598-019-52293-4

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