- bump the requirement for
DALEX to 2.4.0.
randomForest from suggest due to it enforcing R v4.1 (changed to
new_observation has too many variables (e.g. target outcome).
- auto-convert the
mlr3 learner-like objects with
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
- Add support for stacked tidymodels (
- Clear up documentation.
- Fix errors coming from the new reticulate version
- Adjust explain functions to DALEX 2.1
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)
training_test_comparison() recognizes type of the task and applies proper loss_function
yhat.WrappedModel() returns factor response if
predict.type is not
- 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
yhat.LearnerClassif() returning wrong column of probabilities (PR #34, thanks Hubert!)
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.
- Support for
- DALEXtra now depends DALEX (0.4.9)
- documentation refreshed with links to functions.
explain_scikitlearn() rebuilded. Some of the code was exported to inner functions (helper_functions.R).
- conda installation in
scikitlearn_unix.yml file renamed to
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
yhat() is now generic.
- New examples in
- 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