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: | 0.1.0 |
Depends: | R (≥ 3.1.0) |
Imports: | caret, stats, utils |
Suggests: | doParallel, GSIF, randomForest |
Published: | 2018-01-09 |
Author: | Hanna Meyer [cre, aut], Chris Reudenbach [ctb], Thomas Nauss [ctb] |
Maintainer: | Hanna Meyer <hanna.meyer at geo.uni-marburg.de> |
License: | GPL (≥ 3) | file LICENSE |
URL: | https://github.com/environmentalinformatics-marburg/CAST |
NeedsCompilation: | no |
CRAN checks: | CAST results |
Reference manual: | CAST.pdf |
Package source: | CAST_0.1.0.tar.gz |
Windows binaries: | r-devel: CAST_0.1.0.zip, r-release: CAST_0.1.0.zip, r-oldrel: CAST_0.1.0.zip |
OS X binaries: | r-release: CAST_0.1.0.tgz, r-oldrel: CAST_0.1.0.tgz |
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