Extends the mlr3 machine learning framework with spatio-temporal resampling methods to account for the presence of spatiotemporal autocorrelation (STAC) in predictor variables. STAC may cause highly biased performance estimates in cross-validation if ignored. A JSS article is available at <doi:10.18637/jss.v111.i07>.
Version: | 2.3.2 |
Depends: | mlr3 (≥ 0.12.0), R (≥ 3.5.0) |
Imports: | checkmate, data.table, ggplot2 (≥ 3.4.0), mlr3misc (≥ 0.11.0), paradox, R6, utils |
Suggests: | bbotk, blockCV (≥ 3.1.2), caret, CAST (≥ 0.8.0), ggsci, ggtext, here, knitr, lgr, mlr3filters (≥ 0.7.0.9000), mlr3pipelines, mlr3spatial, mlr3tuning, patchwork, plotly, rmarkdown, rpart, sf, sperrorest, terra, testthat (≥ 3.0.0), twosamples, vdiffr (≥ 1.0.0), withr |
Published: | 2024-11-29 |
DOI: | 10.32614/CRAN.package.mlr3spatiotempcv |
Author: | Patrick Schratz [aut, cre], Marc Becker [aut], Jannes Muenchow [ctb], Michel Lang [ctb] |
Maintainer: | Patrick Schratz <patrick.schratz at gmail.com> |
BugReports: | https://github.com/mlr-org/mlr3spatiotempcv/issues |
License: | LGPL-3 |
URL: | https://mlr3spatiotempcv.mlr-org.com/, https://github.com/mlr-org/mlr3spatiotempcv, https://mlr3book.mlr-org.com |
NeedsCompilation: | no |
Citation: | mlr3spatiotempcv citation info |
Materials: | README NEWS |
In views: | Spatial, SpatioTemporal |
CRAN checks: | mlr3spatiotempcv results |
Reference manual: | mlr3spatiotempcv.pdf |
Vignettes: |
Getting Started (source, R code) Spatiotemporal Visualization (source, R code) |
Package source: | mlr3spatiotempcv_2.3.2.tar.gz |
Windows binaries: | r-devel: mlr3spatiotempcv_2.3.2.zip, r-release: mlr3spatiotempcv_2.3.2.zip, r-oldrel: mlr3spatiotempcv_2.3.2.zip |
macOS binaries: | r-release (arm64): mlr3spatiotempcv_2.3.2.tgz, r-oldrel (arm64): mlr3spatiotempcv_2.3.2.tgz, r-release (x86_64): mlr3spatiotempcv_2.3.2.tgz, r-oldrel (x86_64): mlr3spatiotempcv_2.3.2.tgz |
Old sources: | mlr3spatiotempcv archive |
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