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DSAM: Data Splitting Algorithms for Model Developments

Providing six different algorithms that can be used to split the available data into training, test and validation subsets with similar distribution for hydrological model developments. The dataSplit() function will help you divide the data according to specific requirements, and you can refer to the par.default() function to set the parameters for data splitting. The getAUC() function will help you measure the similarity of distribution features between the data subsets. For more information about the data splitting algorithms, please refer to: Chen et al. (2022) <doi:10.1016/j.jhydrol.2022.128340>, Zheng et al. (2022) <doi:10.1029/2021WR031818>.

Version: 1.0.2
Depends: R (≥ 2.10)
Imports: caret, kohonen, Matrix, pROC, stats, utils, xgboost
Published: 2024-01-29
DOI: 10.32614/CRAN.package.DSAM
Author: Feifei Zheng [aut, ths], Junyi Chen ORCID iD [aut, cre]
Maintainer: Junyi Chen <jun1chen at zju.edu.cn>
BugReports: https://github.com/lark-max/DSAM/issues
License: MIT + file LICENSE
URL: https://github.com/lark-max/DSAM
NeedsCompilation: no
Materials: README NEWS
CRAN checks: DSAM results

Documentation:

Reference manual: DSAM.pdf

Downloads:

Package source: DSAM_1.0.2.tar.gz
Windows binaries: r-devel: DSAM_1.0.2.zip, r-release: DSAM_1.0.2.zip, r-oldrel: DSAM_1.0.2.zip
macOS binaries: r-release (arm64): DSAM_1.0.2.tgz, r-oldrel (arm64): DSAM_1.0.2.tgz, r-release (x86_64): DSAM_1.0.2.tgz, r-oldrel (x86_64): DSAM_1.0.2.tgz
Old sources: DSAM archive

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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.