Climate of the Past
Climate of the Past
CP
Articles | Volume 20, issue 10
Articles | Volume 20, issue 10
https://doi.org/10.5194/cp-20-2373-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-20-2373-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 10
Research article
 | 
24 Oct 2024
Research article |  | 24 Oct 2024

Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models?

Peng Sun, Philip B. Holden, and H. John B. Birks

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Short summary
We develop the Multi Ensemble Machine Learning Model (MEMLM) for reconstructing palaeoenvironments from microfossil assemblages. The machine-learning approaches, which include random tree and natural language processing techniques, substantially outperform classical approaches under cross-validation, but they can fail when applied to reconstruct past environments. Statistical significance testing is found sufficient to identify these unreliable reconstructions.
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