Aid in visual data investigations
using SHAP (SHapley Additive exPlanation) visualization plots for 'XGBoost' and 'LightGBM'.
It provides summary plot, dependence plot, interaction plot, and force plot and relies on
the SHAP implementation provided by 'XGBoost' and 'LightGBM'.
Please refer to 'slundberg/shap' for the original implementation of SHAP in 'Python'.
| Version: |
0.1.3 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
stats, ggplot2 (≥ 3.0.0), xgboost (≥ 0.81.0.0), data.table (≥ 1.12.0), ggforce (≥ 0.2.1.9000), ggExtra (≥ 0.8), RColorBrewer (≥ 1.1.2), ggpubr, BBmisc |
| Suggests: |
knitr, rmarkdown, gridExtra (≥ 2.3), here, parallel, lightgbm (≥ 2.1) |
| Published: |
2023-05-29 |
| DOI: |
10.32614/CRAN.package.SHAPforxgboost |
| Author: |
Yang Liu  [aut,
cre],
Allan Just [aut,
ctb],
Michael Mayer [ctb] |
| Maintainer: |
Yang Liu <lyhello at gmail.com> |
| BugReports: |
https://github.com/liuyanguu/SHAPforxgboost/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/liuyanguu/SHAPforxgboost |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
SHAPforxgboost results |