Changes in version 0.2.0 (2025-12-13) - 12/12/2025 Update to support xgboost 1.7.0 and above. Changes in version 0.1.2 - 17/05/2022 Added option kind = "bar" to shap.plot.summary(). Changes in version 0.1.1 (2021-03-28) - 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. Changes in version 0.1.0 (2021-01-07) - 12/12/2020 Added support for LightGBM. Changes in version 0.0.5 - Maintain documentations Changes in version 0.0.4 (2020-05-14) - 05/13/2020 fixed a problem in simple scatter plot, add add_stat_cor option Changes in version 0.0.3 (2020-02-09) - 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. Changes in version 0.0.2 (2019-08-28) - 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.