NEWS (original) (raw)

• Remove reticulate from imports.
• Refactor create_env.
• fixed explain_tidymodels to ignoreresidual_function for classification models.
• fixed explain_h2o examples that might occasionally crash.
• 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() whennew_observation has too many variables (e.g. target outcome).
• auto-convert the mlr3 learner-like objects withmlr3::as_learner() in explain_mlr3().
• Skip explain_keras and explain_scikitlearnexamples 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 inexplain_tidymodels if the model inherits frommodel_fit class.
• Add support for stacked tidymodels (stackspackage).
• 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
• 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.
• Fixed cran check results
• In added yhat.GraphLearner() andmodel_info.GraphLearner() to handle GraphLearnersmlr3 objects.
• New examples.
• 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() andtraining_test_comparison() recognizes type of the task and applies proper loss_function
• yhat.WrappedModel() returns factor response ifpredict.type is not prob.
• explain_h2o() now supports model asH2OAutoML
• 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.
• New plot function for funnel_measure() objects. (Thanks Anna Kozak, You are awesome!).
• New tests for funnel_measure() andplot.funnel_measure() (Once again You are awesome, Ania!).
• Added aspect_importnace from ingredients(#19)
• Support for mlr3 added
• DALEXtra now depends DALEX (0.4.9)
• Ceiling replaced with round in funnel_measure()
• 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.
• 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 totesting_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.
• yhat.R created. Predict functions are stored there in order to be more accesible.
• explain_h2o() and explain_mlr()rebuilded.
• 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.
• explain_mlr() function implemented.
• explain_h2o() function implemented.
• DALEXtra package is now public.
• explain_scikitlearn() function implemented.
• create_env() function implemented.