CAST: 'caret' Applications for Spatial-Temporal Models

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: 0.3.1
Depends: R (≥ 3.1.0)
Imports: caret, stats, utils, ggplot2, graphics
Suggests: doParallel, GSIF, randomForest, lubridate, raster, sp, knitr, mapview, rmarkdown
Published: 2018-11-19
Author: Hanna Meyer [cre, aut], Chris Reudenbach [ctb], Marvin Ludwig [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
Materials: README NEWS
CRAN checks: CAST results

Downloads:

Reference manual: CAST.pdf
Vignettes: Introduction to CAST
Package source: CAST_0.3.1.tar.gz
Windows binaries: r-devel: CAST_0.3.1.zip, r-release: CAST_0.3.1.zip, r-oldrel: CAST_0.3.1.zip
OS X binaries: r-release: CAST_0.3.1.tgz, r-oldrel: CAST_0.3.1.tgz
Old sources: CAST archive

Reverse dependencies:

Reverse suggests: uavRst

Linking:

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