shapviz: SHAP Visualizations
Visualizations for SHAP (SHapley Additive exPlanations), such
as waterfall plots, force plots, various types of importance plots,
and dependence plots. These plots act on a 'shapviz' object created
from a matrix of SHAP values and a corresponding feature dataset.
Wrappers for the R packages 'xgboost', 'lightgbm', 'fastshap',
'shapr', 'h2o', 'treeshap', and 'kernelshap' are added for
convenience. By separating visualization and computation, it is
possible to display factor variables in graphs, even if the SHAP
values are calculated by a model that requires numerical features. The
plots are inspired by those provided by the 'shap' package in Python,
but there is no dependency on it.
| Version: |
0.2.1 |
| Depends: |
R (≥ 3.6.0) |
| Imports: |
ggbeeswarm, ggfittext (≥ 0.8.0), gggenes, ggplot2 (≥ 3.0.0), ggrepel, grid, rlang (≥ 0.3.0), stats, utils, xgboost |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Enhances: |
h2o, lightgbm |
| Published: |
2022-08-11 |
| Author: |
Michael Mayer [aut, cre] |
| Maintainer: |
Michael Mayer <mayermichael79 at gmail.com> |
| BugReports: |
https://github.com/mayer79/shapviz/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/mayer79/shapviz |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
shapviz results |
Documentation:
Downloads:
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