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Optimal Spatial Prediction Using Ensemble Machine Learning

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  • Davies Molly Margaret
  • van der Laan Mark J.

    (Group in Biostatistics, University of California, Berkeley, Berkeley, CA, USA)

Abstract

Spatial prediction is an important problem in many scientific disciplines. Super Learner is an ensemble prediction approach related to stacked generalization that uses cross-validation to search for the optimal predictor amongst all convex combinations of a heterogeneous candidate set. It has been applied to non-spatial data, where theoretical results demonstrate it will perform asymptotically at least as well as the best candidate under consideration. We review these optimality properties and discuss the assumptions required in order for them to hold for spatial prediction problems. We present results of a simulation study confirming Super Learner works well in practice under a variety of sample sizes, sampling designs, and data-generating functions. We also apply Super Learner to a real world dataset.

Suggested Citation

  • Davies Molly Margaret & van der Laan Mark J., 2016. "Optimal Spatial Prediction Using Ensemble Machine Learning," The International Journal of Biostatistics, De Gruyter, vol. 12(1), pages 179-201, May.
    • Handle: RePEc:bpj:ijbist:v:12:y:2016:i:1:p:179-201:n:1
    DOI: 10.1515/ijb-2014-0060
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    References listed on IDEAS

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    1. Huang, Hsin-Cheng & Chen, Chun-Shu, 2007. "Optimal Geostatistical Model Selection," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1009-1024, September.
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    Cited by:

    1. Xiangyuan Wu & Kening Wu & Huafu Zhao & Shiheng Hao & Zhenyu Zhou, 2023. "Impact of Land Cover Changes on Soil Type Mapping in Plain Areas: Evidence from Tongzhou District of Beijing, China," Land, MDPI, vol. 12(9), pages 1-14, August.
    2. Odunayo David Adeniyi & Alexander Brenning & Alice Bernini & Stefano Brenna & Michael Maerker, 2023. "Digital Mapping of Soil Properties Using Ensemble Machine Learning Approaches in an Agricultural Lowland Area of Lombardy, Italy," Land, MDPI, vol. 12(2), pages 1-17, February.

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