ingredients 1.3.1
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* 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](https://github.com/ModelOriented/ingredients/issues/120)
* `plot(ceteris_paribus)` change default `color` to _label_ or _ids_ if more than one profile is detected, this solves [#123](https://github.com/ModelOriented/ingredients/issues/123)
* `ceteris_paribus` has now argument `variable_splits_with_obs` which included values from `new_observations` in the `variable_splits`, this solves [#124](https://github.com/ModelOriented/ingredients/issues/124)

ingredients 1.3.0
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* deprecate `n_sample` argument in `feature_importance` (now it's `N`) [#113](https://github.com/ModelOriented/ingredients/issues/113)
* `plot_profile` now handles multilabel models

ingredients 1.2.0
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* `DALEX` is moved to Suggests as in  [#112](https://github.com/ModelOriented/ingredients/issues/112)
* `plot_categorical_ceteris_paribus` can plot bars (again)
* add `bind_plots` functions

ingredients 1.1.0
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* support `R v4.0` and depend on `R v3.5` to comply with `DALEX`
* new arguments `title` and `subtitle` in several plots

ingredients 1.0.0
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* change `dependency` to `dependence` [#103](https://github.com/ModelOriented/ingredients/issues/103)

ingredients 0.5.2
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* `ceteris_paribus` profiles are now working for categorical variables
* `show_profiles`, `show_observations`, `show_residuals` are now working for categorical variables

ingredients 0.5.1
---------------------------------------------------------------
* synchronisation with changes in DALEX 0.5
* new argument `desc_sorting` in `plot.variable_importance_explainer` [#94](https://github.com/ModelOriented/ingredients/issues/94)

ingredients 0.5.0
---------------------------------------------------------------
* `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](https://github.com/ModelOriented/ingredients/issues/82)

ingredients 0.4.2
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* `aggregate_profiles` use now gaussian kernel smoothing. Use the `span` argument for fine control over this parameter ([#79](https://github.com/ModelOriented/ingredients/issues/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](https://modeloriented.github.io/ingredients/news/index.html#ingredients-0-3-12))
* added Travis-CI for OSX

ingredients 0.4.1
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* fixed rounding problem in the describe function ([#76](https://github.com/ModelOriented/ingredients/issues/76))

ingredients 0.4
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* CRAN release

ingredients 0.3.12
---------------------------------------------------------------
* `aspect_importance` is moved to `DALEXtra` ([#66](https://github.com/ModelOriented/ingredients/issues/66))
* examples are updated in order to reflect changes in `titanic_imputed` from `DALEX` ([#65](https://github.com/ModelOriented/ingredients/issues/65))


ingredients 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


ingredients 0.3.10
---------------------------------------------------------------
* added `triplot` function that illustrates hierarchical `aspect_importance()` groupings
* changes in `aspect_importance()` functions
* added back the vigniette for `aspect_importance()`

ingredients 0.3.9
---------------------------------------------------------------
* change `only_numerical` parameter to `variable_type` in functions aggregated_profiles(),
cluster_profiles(), plot() and others, as requested in #15

ingredients 0.3.8
----------------------------------------------------------------
* Natural language description generated with `describe()` function for `ceteris_paribus()`, `feature_importance()` and `aggregate_profiles()` explanations. 


ingredients 0.3.7
----------------------------------------------------------------
* `aggregated_profiles_conditional` and `aggregated_profiles_accumulated` are rewritten with some code fixes

ingredients 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.

ingredients 0.3.5
----------------------------------------------------------------
* new feature [#29](https://github.com/ModelOriented/ingredients/issues/29). Feature importance now takes an argument `B` that replicates permutations `B` times and calculates average from drop loss.

ingredients 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](https://github.com/ModelOriented/ingredients/issues/27) for multiple rows 

ingredients 0.3.3
----------------------------------------------------------------
* `show_profiles` and `show_residuals` functions extend Ceteris Paribus Plots.
* `show_aggreagated_profiles` is renamed to `show_aggregated_profiles`
* centering of ggplot2 title

ingredients 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

ingredients 0.3.1
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* added references to PM VEE
* `partial_profiles()`, `accumulated_profiles()` and `conditional_profiles` for variable effects
* major changes in function names and file names

ingredients 0.3
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* `ceteris_paribus_2d` extends classical ceteris paribus profiles
* `ceteris_paribus_oscillations` calculates oscilations for ceteris paribus profiles
* fixed examples and file names

ingredients 0.2
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* `cluster_profiles` helps to identify interactions
* `partial_dependency` calculates partial dependency plots
* `aggregate_profiles` calculates partial dependency plots and much more

ingredients 0.1
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* port of `model_feature_importance` and `model_feature_response` from `DALEX` to `ingredients`
* added tests
