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. This package includes functions to improve spatial-temporal modelling tasks using 'caret'. It prepares data for Leave-Location-Out and Leave-Time-Out cross-validation which are target-oriented validation strategies for spatial-temporal models. To decrease overfitting and improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to the target-oriented performance.
Version: | 0.4.2 |
Depends: | R (≥ 3.1.0) |
Imports: | caret, stats, utils, ggplot2, graphics, reshape, FNN, plyr |
Suggests: | doParallel, GSIF, randomForest, lubridate, raster, sp, knitr, mapview, rmarkdown, sf, scales, parallel, latticeExtra, virtualspecies, gridExtra, viridis, rgeos |
Published: | 2020-07-17 |
Author: | Hanna Meyer [cre, aut], Chris Reudenbach [ctb], Marvin Ludwig [ctb], Thomas Nauss [ctb], Edzer Pebesma [ctb] |
Maintainer: | Hanna Meyer <hanna.meyer at uni-muenster.de> |
License: | GPL (≥ 3) | file LICENSE |
URL: | https://github.com/HannaMeyer/CAST |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | CAST results |
Reference manual: | CAST.pdf |
Vignettes: |
Area of applicability of spatial prediction models Introduction to CAST |
Package source: | CAST_0.4.2.tar.gz |
Windows binaries: | r-devel: CAST_0.4.2.zip, r-release: CAST_0.4.2.zip, r-oldrel: CAST_0.4.2.zip |
macOS binaries: | r-release: CAST_0.4.2.tgz, r-oldrel: CAST_0.4.2.tgz |
Old sources: | CAST archive |
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