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SHAPforxgboost 0.1.2

17/05/2022 Added option kind = "bar" to shap.plot.summary().

SHAPforxgboost 0.1.1

22/03/2021 Moved lightgbm from imported to suggested package.
05/02/2021 Added color_feature = "auto" in shap.plot.dependence in order to colorize the (heuristically found) strongest interaction.
06/02/2021 Added vignette.
06/02/2021 Added function shap.importance to return mean absolute SHAP values per variable.
10/02/2021 Added jitter_width, jitter_height and alpha to shap.plot.dependence.

SHAPforxgboost 0.1.0

12/12/2020 Added support for LightGBM.

SHAPforxgboost 0.0.5

Maintain documentations

SHAPforxgboost 0.0.4

05/13/2020 fixed a problem in simple scatter plot, add add_stat_cor option

SHAPforxgboost 0.0.3

01/22/2020 I fixed some issues raised, for example, y-axis goes under the data instead of on it.
02/08/2020 Added an var_cat option to shap.prep so if supply a categorical variable, the long-format data would use var_cat as a labeling variable. For example, we can make two summary plot by adding facet_wrap(~ var_cat) to the shap.plot.summary .
Added an ID variable for each observation to the dataset produced by shap.prep and shap.prep.stack.data, which might be useful under certain situation.
Revised most functions’ documentations.

SHAPforxgboost 0.0.2

Added a NEWS.md file to track changes to the package.
07/30/2019 Version 0.0.1 uploaded to cran.
08/10/2019 Version 0.0.2 released with update, fixed some bugs with dilute.
08/27/2019 Major change, merged function shap.plot.dependence.color into shap.plot.dependence.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.