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CAST: Caret Applications for Spatio-Temporal models

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Supporting functionality to run ‘caret’ with spatial or spatial-temporal data. ‘caret’ is a frequently used package for model training and prediction using machine learning. CAST includes functions to improve spatial or spatial-temporal modelling tasks using ‘caret’. To decrease spatial overfitting and to improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to spatial or spatio-temporal model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models.

Note: The developer version of CAST can be found on https://github.com/HannaMeyer/CAST. The CRAN Version can be found on https://CRAN.R-project.org/package=CAST

The figure shows a very simple workflow for a spatial prediction mapping workflow, indicating which function in CAST can be used in the different steps to support the spatial prediction.

Package Website

https://hannameyer.github.io/CAST/

Tutorials

Scientific documentation of the methods

Spatial cross-validation

Spatial variable selection

Area of applicability

Applications and use cases

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.