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 |