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 Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=SHAPforxgboost to link to this page.
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