PIE
A Partially Interpretable Model with Black-Box Refinement
Implements a novel predictive model, Partially Interpretable Estimators (PIE), which jointly trains an interpretable model and a black-box model to achieve high predictive performance as well as partial model. See the paper, Wang, Yang, Li, and Wang (2021) <doi:10.48550/arXiv.2105.02410>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | PIE_1.0.0.tar.gz |
139.5 KiB |
1.0.0 |
rolling linux/noble R-4.5 | PIE_1.0.0.tar.gz |
139.3 KiB |
1.0.0 |
rolling source/ R- | PIE_1.0.0.tar.gz |
118.9 KiB |
1.0.0 |
latest linux/jammy R-4.5 | PIE_1.0.0.tar.gz |
139.5 KiB |
1.0.0 |
latest linux/noble R-4.5 | PIE_1.0.0.tar.gz |
139.3 KiB |
1.0.0 |
latest source/ R- | PIE_1.0.0.tar.gz |
118.9 KiB |
1.0.0 |
2026-04-26 source/ R- | PIE_1.0.0.tar.gz |
118.9 KiB |
1.0.0 |
2026-04-23 source/ R- | PIE_1.0.0.tar.gz |
118.9 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | PIE_1.0.0.zip |
142.5 KiB |
1.0.0 |
2025-04-20 source/ R- | PIE_1.0.0.tar.gz |
118.9 KiB |