Changes in version 2.3.1 (2026-01-14) - Adjust DALEXtra to the new xgboost package interface Changes in version 2.3.0 (2023-05-25) - Remove reticulate from imports. - Refactor create_env. Changes in version 2.2.1 (2022-06-14) - fixed explain_tidymodels to ignore residual_function for classification models. - fixed explain_h2o examples that might occasionally crash. Changes in version 2.2.0 (2022-04-23) - 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. Changes in version 2.1.1 (2021-05-09) - Fix CRAN results issues Changes in version 2.1 - Fix errors coming from the new reticulate version - Adjust explain functions to DALEX 2.1 Changes in version 2.0 (2020-09-07) - 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. Changes in version 1.3.2 (2020-07-28) - Fixed cran check results Changes in version 1.3.1 (2020-07-16) - In added yhat.GraphLearner() and model_info.GraphLearner() to handle GraphLearners mlr3 objects. - New examples. Changes in version 1.3.0 - 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 Changes in version 0.2.3 - 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. Changes in version 0.2.2 - explain_h2o() now supports model as H2OAutoML Changes in version 0.2.1 (2020-03-29) - 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!) Changes in version 0.2.0 (2019-11-18) - 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. Changes in version 0.1.11 - 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!). Changes in version 0.1.10 - Added aspect_importnace from ingredients (#19) - Support for mlr3 added - DALEXtra now depends DALEX (0.4.9) Changes in version 0.1.9 - Ceiling replaced with round in funnel_measure() Changes in version 0.1.8 (2019-09-23) - 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. Changes in version 0.1.7 (2019-09-19) - 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. Changes in version 0.1.6 - 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. Changes in version 0.1.5 - 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. Changes in version 0.1.4 - yhat.R created. Predict functions are stored there in order to be more accesible. - explain_h2o() and explain_mlr() rebuilded. Changes in version 0.1.3 - travis and codecov is now aviable available for DALEXtra. - tests added. Changes in version 0.1.2 - 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. Changes in version 0.1.1 - explain_mlr() function implemented. - explain_h2o() function implemented. Changes in version 0.1 - DALEXtra package is now public. - explain_scikitlearn() function implemented. - create_env() function implemented.