DALEXtra 2.3.1
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* Adjust `DALEXtra` to the new `xgboost` package interface

DALEXtra 2.3.0
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* Remove `reticulate` from imports.
* Refactor `create_env`.

DALEXtra 2.2.1
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* fixed `explain_tidymodels` to ignore `residual_function` for classification models.
* fixed `explain_h2o` examples that might occasionally crash.

DALEXtra 2.2.0
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* bump the requirement for `DALEX` to 2.4.0.
* remove `randomForest` from suggest due to it enforcing R v4.1 (changed to `ranger`).
* fix `predict_surrogate()` when `new_observation` has too many variables (e.g. target outcome).
* auto-convert the `mlr3` learner-like objects with `mlr3::as_learner()` in `explain_mlr3()`.
* Skip `explain_keras` and `explain_scikitlearn` examples while running on macOS as they can rise false-positive errors during R CMD check for some versions of macOS. The very same code still executes properly in tests.
* Skip check if the model is trained in `explain_tidymodels` if the model inherits from `model_fit` class.
* Add support for stacked tidymodels (`stacks` package).
* Add `dalex_load_explainer` function.
* Clear up documentation.

DALEXtra 2.1.1
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* Fix CRAN results issues 

DALEXtra 2.1
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* Fix errors coming from the new reticulate version
* Adjust explain functions to DALEX 2.1

DALEXtra 2.0
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* `explain_tidymodels()` added as a support for tidymodels workflows.
* Removed aspect importance. It's available in triplot package https://cran.r-project.org/web/packages/triplot/index.html.
* `predict_surrogate()` function is added to provide easier interface of accessing lime/iml/localModel implementations of the LIME method.

DALEXtra 1.3.2
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* Fixed cran check results

DALEXtra 1.3.1
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* In added `yhat.GraphLearner()` and `model_info.GraphLearner()` to handle GraphLearners `mlr3` objects.
* New examples.

DALEXtra 1.3.0
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* In `explain_h2o()` data parameter will bo converted to data.frame if H2OFrame object was passed.
* Aspect importance related functions set deprecated. Will be removed with next release.
* `explain_xgboost()` function added

DALEXtra 0.2.3
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* DALEXtra now supports multiclass classification (accordingly to DALEX >= 1.3)
* `funnel_mesure()` and `training_test_comparison()` recognizes type of the task and applies proper loss_function
* `yhat.WrappedModel()` returns factor response if `predict.type` is not `prob`.

DALEXtra 0.2.2
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* `explain_h2o()` now supports `model` as `H2OAutoML`

DALEXtra 0.2.1
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* Removed h2o::init() from explain_h2o()
* Removed mljar support as mljar package is not available for R 3.6.2
* Ajusted to DALEX 1.0
* fixed `yhat.LearnerClassif()` returning wrong column of probabilities (PR #34, thanks Hubert!)

DALEXtra 0.2.0
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* Rebuilded `plot.overall_comparison()` (I lack words that could describe Your greatness, Ania!).
* New README and DESCRIPTION. They are more accurate now.
* Small fixes to `funnel_measure()` that imporves it's stability.

DALEXtra 0.1.11
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* New plot function for `funnel_measure()` objects. (Thanks Anna Kozak, You are awesome!).
* New tests for `funnel_measure()` and `plot.funnel_measure()` (Once again You are awesome, Ania!).

DALEXtra 0.1.10
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* Added `aspect_importnace` from `ingredients`  ([#19](https://github.com/ModelOriented/ingredients/issues/19))
* Support for `mlr3` added
* DALEXtra now depends DALEX (0.4.9)

DALEXtra 0.1.9
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* Ceiling replaced with round in `funnel_measure()`

DALEXtra 0.1.8
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* `champion_challenger()`.
* `overall_comparison()` added with generic plot and print functions. 
* `training_test_comparison()` added with generic plot and print functions. 
* `funnel_measure()` added with generic plot and print functions. 
* test for h2o rebuilded.

DALEXtra 0.1.7
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* `explain_keras()` added. 
* `explain_mljar()` added.
* documentation refreshed with links to functions.
* `explain_scikitlearn()` rebuilded. Some of the code was exported to inner functions (helper_functions.R).
* conda installation in `README.md`.
* `scikitlearn_unix.yml` file renamed to `testing_environment.yml`.

DALEXtra 0.1.6
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* `explain_scikitlearn()` rebuilded. Now class scikitlearn_model is a additional class for original Python object instead of another object.
* explainers created with `explain_scikitlearn()` have addidtional field `param_set`.
* `yhat()` is now generic.
* New examples in `README.md`.

DALEXtra 0.1.5
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* Now when you pass .yml that consist environment name that already exists one the machine, DALEXtra will not rise an error and contiune work with existing env.
* If condaenv is NULL when creating_env on unixlike OS, DALEXtra will try to find conda on his own.
* `on_attach()` function now checks if conda is installed. Alert is rised if not.

DALEXtra 0.1.4
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* yhat.R created. Predict functions are stored there in order to be more accesible.
* `explain_h2o()` and `explain_mlr()` rebuilded. 

DALEXtra 0.1.3
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* travis and codecov is now aviable available for DALEXtra.
* tests added.

DALEXtra 0.1.2
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* `scikitlearn_unix.yml` file added to external data. This helps testing using linuxlike OS.
* few minor updates in the documentation.
* message in `create_env()` changed.

DALEXtra 0.1.1
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* `explain_mlr()` function implemented.
* `explain_h2o()` function implemented.

DALEXtra 0.1
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* DALEXtra package is now public.
* `explain_scikitlearn()` function implemented.
* `create_env()` function implemented.

