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blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models

Authors :
Valavi, Roozbeh
Elith, Jane
Lahoz-Monfort, José J.
Guillera-Arroita, Gurutzeta
Publication Year :
2018
Publisher :
Cold Spring Harbor Laboratory, 2018.

Abstract

SummaryWhen applied to structured data, conventional random cross-validation techniques can lead to underestimation of prediction error, and may result in inappropriate model selection.We present the R package blockCV, a new toolbox for cross-validation of species distribution modelling.The package can generate spatially or environmentally separated folds. It includes tools to measure spatial autocorrelation ranges in candidate covariates, providing the user with insights into the spatial structure in these data. It also offers interactive graphical capabilities for creating spatial blocks and exploring data folds.Package blockCV enables modellers to more easily implement a range of evaluation approaches. It will help the modelling community learn more about the impacts of evaluation approaches on our understanding of predictive performance of species distribution models.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....84e2b2004e0fe1f2d6d7f113d3ee9445
Full Text :
https://doi.org/10.1101/357798