SPlit
Split a Dataset for Training and Testing
Procedure to optimally split a dataset for training and testing. 'SPlit' is based on the method of support points, which is independent of modeling methods. Please see Joseph and Vakayil (2021) <doi:10.1080/00401706.2021.1921037> for details. This work is supported by U.S. National Science Foundation grant DMREF-1921873.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.3 |
rolling source/ R- | SPlit_1.3.tar.gz |
97.9 KiB |
1.3 |
rolling linux/jammy R-4.5 | SPlit_1.3.tar.gz |
163.1 KiB |
1.3 |
rolling linux/noble R-4.5 | SPlit_1.3.tar.gz |
164.9 KiB |
1.3 |
latest linux/jammy R-4.5 | SPlit_1.3.tar.gz |
163.1 KiB |
1.3 |
latest linux/noble R-4.5 | SPlit_1.3.tar.gz |
164.9 KiB |
1.3 |
latest source/ R- | SPlit_1.3.tar.gz |
97.9 KiB |
1.3 |
2026-04-26 source/ R- | SPlit_1.3.tar.gz |
97.9 KiB |
1.3 |
2026-04-23 source/ R- | SPlit_1.3.tar.gz |
97.9 KiB |
1.3 |
2026-04-09 windows/windows R-4.5 | SPlit_1.3.zip |
571.0 KiB |
1.2 |
2025-04-20 source/ R- | SPlit_1.2.tar.gz |
99.1 KiB |
Dependencies (latest)
Imports
- Rcpp (>= 1.0.4)