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Fast, lightweight toolkit for data splitting. Data sets can be partitioned into disjoint groups (e.g. into training, validation, and test) or into (repeated) k-folds for subsequent cross-validation. Besides basic splits, the package supports stratified, grouped as well as blocked splitting. Furthermore, cross-validation folds for time series data can be created. See e.g. Hastie et al. (2001) <doi:10.1007/978-0-387-84858-7> for the basic background on data partitioning and cross-validation.
Version: | 1.0.1 |
Imports: | stats |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2023-06-06 |
DOI: | 10.32614/CRAN.package.splitTools |
Author: | Michael Mayer [aut, cre] |
Maintainer: | Michael Mayer <mayermichael79 at gmail.com> |
BugReports: | https://github.com/mayer79/splitTools/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/mayer79/splitTools |
NeedsCompilation: | no |
Materials: | README NEWS |
In views: | MachineLearning |
CRAN checks: | splitTools results |
Reference manual: | splitTools.pdf |
Vignettes: |
Using 'splitTools' |
Package source: | splitTools_1.0.1.tar.gz |
Windows binaries: | r-devel: splitTools_1.0.1.zip, r-release: splitTools_1.0.1.zip, r-oldrel: splitTools_1.0.1.zip |
macOS binaries: | r-release (arm64): splitTools_1.0.1.tgz, r-oldrel (arm64): splitTools_1.0.1.tgz, r-release (x86_64): splitTools_1.0.1.tgz, r-oldrel (x86_64): splitTools_1.0.1.tgz |
Old sources: | splitTools archive |
Reverse imports: | mlexperiments |
Reverse suggests: | mllrnrs, mlsurvlrnrs |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.