IBLM
Interpretable Boosted Linear Models
Implements Interpretable Boosted Linear Models (IBLMs). These combine a conventional generalized linear model (GLM) with a machine learning component, such as XGBoost. The package also provides tools within for explaining and analyzing these models. For more details see Gawlowski and Wang (2025) <https://ifoa-adswp.github.io/IBLM/reference/figures/iblm_paper.pdf>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.2 |
rolling source/ R- | IBLM_1.0.2.tar.gz |
1.2 MiB |
1.0.2 |
rolling linux/jammy R-4.5 | IBLM_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
rolling linux/noble R-4.5 | IBLM_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
latest source/ R- | IBLM_1.0.2.tar.gz |
1.2 MiB |
1.0.2 |
latest linux/jammy R-4.5 | IBLM_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
latest linux/noble R-4.5 | IBLM_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
2026-04-26 source/ R- | IBLM_1.0.2.tar.gz |
1.2 MiB |
1.0.2 |
2026-04-23 source/ R- | IBLM_1.0.2.tar.gz |
1.2 MiB |
1.0.2 |
2026-04-09 windows/windows R-4.5 | IBLM_1.0.2.zip |
1.3 MiB |