Changes in version 2.3.1 - Changes in default color theme as in #150 Changes in version 2.3.0 (2023-01-15) - breaking change: calculate_variable_splits() now treats integer variables as categorical. This change is propagated to ceteris_paribus(), partial_dependence(), accumulated_dependence(), conditional_dependence(), aggregate_profiles(), DALEX::predict_profile(), DALEX::model_profile() - fix an error in ceteris_paribus / calculate_variable_splits when tidymodels uses integer variables #145 - fix an error in show_observations #148. This change is propagated to DALEX::plot.predict_profile() #540. - fix #149 by replacing all class(x) = "y" with is(x, "y") Changes in version 2.2.1 - added facet_scales parameter to plot.aggregated_profiles_explainer ('free_x' by default) #138 and plot.ceteris_paribus_explainer ('free_x' or 'free_y' by default, depending on plot type) #136 Changes in version 2.2.0 (2021-04-10) - fixes explanations when data has one column #137 Changes in version 2.0.1 (2021-02-05) - code and documentation maintenance #130 - fixed an error when N = NULL in partial_dependence() etc. #134 Changes in version 2.0 (2020-09-01) - plot.ceteris_paribus_explainer now by default for categorical variables plots profiles (not lines -prev default- nor bars) - ALE plots are now centered around average y_hat #126 - colors from DrWhy color palette is used for CP #125 Changes in version 1.3.1 (2020-07-29) - default subtitle value in plot.fi changed to NULL from NA (unification) - now in the ceteris_paribus function one can specify how grid points shall be calculated, see variable_splits_type - ceteris_paribus and aggregates are now working with missing data, this solves #120 - plot(ceteris_paribus) change default color to label or ids if more than one profile is detected, this solves #123 - ceteris_paribus has now argument variable_splits_with_obs which included values from new_observations in the variable_splits, this solves #124 Changes in version 1.3.0 (2020-07-01) - deprecate n_sample argument in feature_importance (now it's N) #113 - plot_profile now handles multilabel models Changes in version 1.2.0 (2020-04-20) - DALEX is moved to Suggests as in #112 - plot_categorical_ceteris_paribus can plot bars (again) - add bind_plots function Changes in version 1.1.0 - support R v4.0 and depend on R v3.5 to comply with DALEX - new arguments title and subtitle in several plots Changes in version 1.0.0 - change dependency to dependence #103 Changes in version 0.5.2 - ceteris_paribus profiles are now working for categorical variables - show_profiles, show_observations, show_residuals are now working for categorical variables Changes in version 0.5.1 - synchronisation with changes in DALEX 0.5 - new argument desc_sorting in plot.variable_importance_explainer #94 Changes in version 0.5.0 (2019-12-20) - feature_importance now does 15 permutations on each variable by default. Use the B argument to change this number - added boxplots to plot.feature_importance and plotD3.feature_importance that showcase the permutation data - in aggregate_profiles: preserve _x_ column factor order and sort its values #82 Changes in version 0.4.2 - aggregate_profiles use now gaussian kernel smoothing. Use the span argument for fine control over this parameter (#79) - change variable_type and variables arguments usage in the aggregate_profiles, plot.ceteris_paribus and plotD3.ceteris_paribus - remove variable_type argument from plotD3.aggregated_profiles (now the same as in plot.aggregated_profiles) - Kasia Pekala is moved as contributor to the DALEXtra as aspect_importance is moved to DALEXtra as well (See v0.3.12 changelog) - added Travis-CI for OSX Changes in version 0.4.1 - fixed rounding problem in the describe function (#76) Changes in version 0.4 (2019-10-27) - CRAN release Changes in version 0.3.12 - aspect_importance is moved to DALEXtra (#66) - examples are updated in order to reflect changes in titanic_imputed from DALEX (#65) Changes in version 0.3.11 - modified plot.aspect_importance - it can plot more than single figure - modified triplot, plot.aspect_importance and plot_group_variables to add more clarity in plots and allow some parameterization Changes in version 0.3.10 - added triplot function that illustrates hierarchical aspect_importance() groupings - changes in aspect_importance() functions - added back the vigniette for aspect_importance() Changes in version 0.3.9 (2019-08-26) - change only_numerical parameter to variable_type in functions aggregated_profiles(), cluster_profiles(), plot() and others, as requested in #15 Changes in version 0.3.8 - Natural language description generated with describe() function for ceteris_paribus(), feature_importance() and aggregate_profiles() explanations. Changes in version 0.3.7 - aggregated_profiles_conditional and aggregated_profiles_accumulated are rewritten with some code fixes Changes in version 0.3.6 - a new version of lime is implemented in the lime()/aspect_importance() function. - Kasia Pekala and Huber Baniecki are added as contributors. Changes in version 0.3.5 - new feature #29. Feature importance now takes an argument B that replicates permutations B times and calculates average from drop loss. Changes in version 0.3.4 - plotD3 now supports Ceteris Paribus Profiles. - feature_importance now can take variable_grouping argument that assess importance of group of features - fix in ceteris_paribus, now it handles models with just one variable - fix #27 for multiple rows Changes in version 0.3.3 (2019-05-01) - show_profiles and show_residuals functions extend Ceteris Paribus Plots. - show_aggreagated_profiles is renamed to show_aggregated_profiles - centering of ggplot2 title Changes in version 0.3.2 - added new functions describe() and print.ceteris_paribus_descriptions() for text based descriptions of Ceteris Paribus explainers - plot.ceteris_paribus_explainer works now also for categorical variables. Use the only_numerical = FALSE to force bars Changes in version 0.3.1 (2019-04-09) - added references to PM VEE - partial_profiles(), accumulated_profiles() and conditional_profiles for variable effects - major changes in function names and file names Changes in version 0.3 - ceteris_paribus_2d extends classical ceteris paribus profiles - ceteris_paribus_oscillations calculates oscilations for ceteris paribus profiles - fixed examples and file names Changes in version 0.2 - cluster_profiles helps to identify interactions - partial_dependency calculates partial dependency plots - aggregate_profiles calculates partial dependency plots and much more Changes in version 0.1 - port of model_feature_importance and model_feature_response from DALEX to ingredients - added tests