explain() should now be MUCH faster at explaining a single observation, especially when nsim is relatively large (e.g., nsim >= 1000).The default method of explain() gained a new logical argument called adjust. When adjust = TRUE (and nsim > 1), the algorithm will adjust the sum of the estimated Shapley values to satisfy the efficiency property; that is, to equal the difference between the model’s prediction for that sample and the average prediction over all the training data. This option is experimental and we follow the same approach as in shap (#6).
New (experimental) function for constructing force plots (#7) to help visualize prediction explanations. The function is also a generic which means additional methods can be added.
Function explain() became a generic and gained a new logical argument, exact, for computing exact Shapley contributions for linear models (LinearSHAP, which assumes independent features) and boosted decision trees (TreeSHAP). Currently, only "lm", "glm", and "xgb.Booster" objects are supported (#2)(#3).
Minor improvements to package documentation.
Removed unnecessary legend from contribution plots.
Tweak imports (in particular, use @importFrom Rcpp sourceCpp tag).
Fixed a typo in the package description; Shapley was misspelled as Shapely (fixed by Dirk Eddelbuettel in (#1)).
You can now specify type = "contribution" in the call to autoplot.fastshap() to plot the explanation for a single instance (controlled by the row_num argument).
autoplot.fastshap() gained some useful new arguments:
color_by for specifying an additional feature to color by for dependence plots (i.e., whenever type = "dependence");
smooth, smooth_color, smooth_linetype, smooth_size, and smooth_alpha for adding/controlling a smoother in dependence plots (i.e., whenever type = "dependence").
... which can be used to pass on additional parameters to geom_col() (when type = "importance") or geom_point() (when type = "dependence").
Function fastshap() was renamed to explain().
Functions explain() and explain_column() (not currently exported) now throw an error whenever the inputs X and newdata do not inherit from the same class.
Fixed a bug in the C++ source that gave more weight to extreme permutations.
Fixed a bug in the C++ source that caused doubles to be incorrectly converted to integers.
Fixed a bug in autoplot.fastshap() when type = "importance"; in particular, the function incorrectly used sum(|Shapley value|) instead of mean(|Shapley value|).