• 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.
  • Fix CRAN results issues
  • Fix errors coming from the new reticulate version
  • Adjust explain functions to DALEX 2.1
  • Fixed cran check results
  • 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 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.
  • 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!)
  • 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.
  • Added aspect_importnace from ingredients (#19)
  • Support for mlr3 added
  • DALEXtra now depends DALEX (0.4.9)
  • 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.
  • 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.
  • 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.
  • travis and codecov is now aviable available for DALEXtra.
  • tests added.
  • 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.