Sstack
Bootstrap Stacking of Random Forest Models for Heterogeneous Data
Generates and predicts a set of linearly stacked Random Forest models using bootstrap sampling. Individual datasets may be heterogeneous (not all samples have full sets of features). Contains support for parallelization but the user should register their cores before running. This is an extension of the method found in Matlock (2018) <doi:10.1186/s12859-018-2060-2>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling linux/jammy R-4.5 | Sstack_1.0.1.tar.gz |
645.4 KiB |
1.0.1 |
rolling linux/noble R-4.5 | Sstack_1.0.1.tar.gz |
645.4 KiB |
1.0.1 |
rolling source/ R- | Sstack_1.0.1.tar.gz |
396.9 KiB |
1.0.1 |
latest linux/jammy R-4.5 | Sstack_1.0.1.tar.gz |
645.4 KiB |
1.0.1 |
latest linux/noble R-4.5 | Sstack_1.0.1.tar.gz |
645.4 KiB |
1.0.1 |
latest source/ R- | Sstack_1.0.1.tar.gz |
396.9 KiB |
1.0.1 |
2026-04-26 source/ R- | Sstack_1.0.1.tar.gz |
396.9 KiB |
1.0.1 |
2026-04-23 source/ R- | Sstack_1.0.1.tar.gz |
396.9 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | Sstack_1.0.1.zip |
648.7 KiB |
1.0.1 |
2025-04-20 source/ R- | Sstack_1.0.1.tar.gz |
396.9 KiB |