DALEX 0.3

• pdp, factorMerger and ALEPlot are going to Suggested. (#60). In next releases they will be deprecated.
• added predict function that calls the predict_function hidden in the explainer object. (#58).

DALEX 0.2.9

• the titanic dataset is copied from stablelearner package. Some features are transformed (some NA replaced with 0, more numeric features).

DALEX 0.2.8

• DALEX is being prepared for tighter integration with iBreakDown and ingredients.
• temporally there is a duplicated single_variable and single_feature
• Added new theme_drwhy().
• New arguments in the plot.variable_importance_explainer(). Namely bar_width with widths of bars and show_baseline if baseline shall be included in these plots.
• New skin in the plot.variable_response_explainer().
• New skin in the plot.prediction_breakdown_explainer().

DALEX 0.2.7

• Test datasets are now named apartments_test and HR_test
• For binary classification we return just a second column. NOTE: this may cause some unexpected problems with code dependend on defaults for DALEX 0.2.6.

DALEX 0.2.6

• New versions of yhat for ranger and svm models.

DALEX 0.2.5

• Residual distribution plots for model performance are now more legible when multiple models are plotted. The styling of plot and axis titles have also been improved (@kevinykuo).
• The defaults of single_prediction() are now consistent with breakDown::broken(). Specifically, baseline is now 0 by default instead of "Intercept". The user can also specify the baseline and other arguments by passing them to single_prediction (@kevinykuo, #39). WARNING: Change in the default value of baseline.
• New yhat.* functions help to handle additional parameters to different predict() functions.
• Updated CITATION info

DALEX 0.2.4

• New dataset HR and HRTest. Target variable is a factor with three levels. Is used in examples for classification.
• The plot.model_performance() has now show_outliers parameter. Set it to anything >0 and observations with largest residuals will be presented in the plot. (#34)

DALEX 0.2.3

• Small fixes in variable_response() to better support of gbm models (c8393120ffb05e2f3c70b0143c4e92dc91f6c823).
• Better title for plot_model_performance() (e5e61d0398459b78ea38ccc980c4040fd853f449).
• Tested with breakDown v 0.1.6.

DALEX 0.2.2

• The single_variable() / variable_response() function uses predict_function from explainer (#17)

DALEX 0.2.1

• The explain() function converts tibbles to data.frame when specified as data argument (#15)
• The default generic explain.default() should help when explain() from dplyr is loaded after DALEX (#16)

DALEX 0.2.0

• New names for some functions: model_performance(), variable_importance(), variable_response(), outlier_detection(), prediction_breakdown(). Old names are now deprecated but still working. (#12)
• A new dataset apartments - will be used in examples
• variable_importance() allows work on full dataset if n_sample is negative
• plot_model_performance() uses ecdf or boxplots (depending on geom parameter).

DALEX 0.1.8

• Function single_variable() supports factor variables as well (with the use of factorMerger package). Remember to use type='factor' when playing with factors. (#10)
• Change in the function explain(). Old version has an argument predict.function, now it’s predict_function. New name is more consistent with other arguments. (#7)
• New vigniette for xgboost model (#11)

DALEX 0.1.1

• Support for global model structure explainers with variable_dropout() function

DALEX 0.1

• DALEX package is now public
• explain() function implemented
• single_prediction() function implemented
• single_variable() function implemented