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

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

Abstract 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 reconstruct...

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Bibliographic Details
Main Authors: J. Sakari Salonen, Mikko Korpela, John W. Williams, Miska Luoto
Format: Article
Language:English
Published: Nature Portfolio 2019-11-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-019-52293-4

Internet

https://doi.org/10.1038/s41598-019-52293-4

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