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Changelog

Source: NEWS.md

SHAPforxgboost 0.2.0

  • 12/12/2025 Update to support xgboost 1.7.0 and above.

SHAPforxgboost 0.1.2

SHAPforxgboost 0.1.1

CRAN release: 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.

SHAPforxgboost 0.1.0

CRAN release: 2021-01-07

  • 12/12/2020 Added support for LightGBM.

SHAPforxgboost 0.0.5

  • Maintain documentations

SHAPforxgboost 0.0.4

CRAN release: 2020-05-14

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

SHAPforxgboost 0.0.3

CRAN release: 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.

SHAPforxgboost 0.0.2

CRAN release: 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.