Added support for Spark (G)LMs.
Bux fixes.
Fixed bug in get_feature_names.ranger() s.t. it never returns NULL; it either returns the feature names or throws an error if they cannot be recovered from the model object (#43).
Added pkgdown site: https://github.com/koalaverse/vip.
Changed truncate_feature_names argument of vi() to abbreviate_feature_names which abbreviates all feature names, rather than just truncating them.
Added CRAN-related badges (#32).
New generic vi_permute() for constructing permutation-based variable importance scores (#19).
Fixed bug and unnecessary error check in vint() (#38).
New vignette on using vip with unsupported models (using the Keras API to TensorFlow as an example).
Added basic sparklyr support.
Added support for XGBoost models (i.e., objects of class "xgb.booster").
Added support for ranger models (i.e., objects of class "ranger").
Added support for random forest models from the party package (i.e., objects of class "RandomForest").
vip() gained a new argument, num_features, for specifying how many variable importance scores to plot. The default is set to 10.
. was changed to _ in all argument names.
vi() gained three new arguments: truncate_feature_names (for truncating feature names in the returned tibble), sort (a logical argument specifying whether or not the resulting variable importance scores should be sorted), and decreasing (a logical argument specifying whether or not the variable importance scores should be sorted in decreasing order).
vi_model.lm(), and hence vi(), contains an additional column called Sign that contains the sign of the original coefficients (#27).
vi() gained a new argument, scale, for scaling the variable importance scores so that the largest is 100. Default is FALSE (#24).
vip() gained two new arguments, size and shape, for controlling the size and shape of the points whenever bar = FALSE (#9).
Added support for "H2OBinomialModel", "H2OMultinomialModel", and, "H2ORegressionModel" objects (#8).