shapper
Wrapper of Python Library 'shap'
Provides SHAP explanations of machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the Interpretable Machine Learning, there are more and more new ideas for explaining black-box models. One of the best known method for local explanations is SHapley Additive exPlanations (SHAP) introduced by Lundberg, S., et al., (2016) <arXiv:1705.07874> The SHAP method is used to calculate influences of variables on the particular observation. This method is based on Shapley values, a technique used in game theory. The R package 'shapper' is a port of the Python library 'shap'.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.3 |
rolling linux/jammy R-4.5 | shapper_0.1.3.tar.gz |
66.6 KiB |
0.1.3 |
rolling linux/noble R-4.5 | shapper_0.1.3.tar.gz |
66.4 KiB |
0.1.3 |
rolling source/ R- | shapper_0.1.3.tar.gz |
38.9 KiB |
0.1.3 |
latest linux/jammy R-4.5 | shapper_0.1.3.tar.gz |
66.6 KiB |
0.1.3 |
latest linux/noble R-4.5 | shapper_0.1.3.tar.gz |
66.4 KiB |
0.1.3 |
latest source/ R- | shapper_0.1.3.tar.gz |
38.9 KiB |
0.1.3 |
2026-04-26 source/ R- | shapper_0.1.3.tar.gz |
38.9 KiB |
0.1.3 |
2026-04-23 source/ R- | shapper_0.1.3.tar.gz |
38.9 KiB |
0.1.3 |
2026-04-09 windows/windows R-4.5 | shapper_0.1.3.zip |
77.6 KiB |
0.1.3 |
2025-04-20 source/ R- | shapper_0.1.3.tar.gz |
38.9 KiB |