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    Calibrating aquatic microfossil proxies with regression-tree ensembles: Cross-validation with modern chironomid and diatom data

    Salonen, S.J. and Verster, A.J. and Engels, Stefan and Soininen, J. and Trachsel, M. and Luoto, M. (2016) Calibrating aquatic microfossil proxies with regression-tree ensembles: Cross-validation with modern chironomid and diatom data. The Holocene 26 (7), pp. 1040-1048. ISSN 0959-6836.

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    Abstract

    We examine the ability of four different regression-tree ensemble techniques (bagging, random forest, rotation forest and boosted tree) in calibration of aquatic microfossil proxies. The methods are tested with six chironomid and diatom datasets, using a variety of cross-validation schemes. We find random forest, rotation forest and the boosted tree to have a similar performance, while bagging performs less well and in several cases has trouble producing continuous predictions. In comparison with commonly used parametric transfer-function approaches (PLS, WA, WA-PLS), we find that in some cases tree-ensemble methods outperform the best-performing transfer-function technique, especially with large datasets characterized by complex taxon responses and abundant noise. However, parametric transfer functions remain competitive with datasets characterized by low number of samples or linear taxon responses. We present an implementation of the rotation forest algorithm in R.

    Metadata

    Item Type: Article
    School: Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Social Sciences
    Depositing User: Stefan Engels
    Date Deposited: 14 Jan 2021 14:44
    Last Modified: 02 Aug 2023 18:05
    URI: https://eprints.bbk.ac.uk/id/eprint/41773

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