- 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 errors coming from the new reticulate version
- Adjust explain functions to DALEX 2.1
- 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.