- Remove
reticulate
from imports.
- Refactor
create_env
.
- fixed
explain_tidymodels
to ignore
residual_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()
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
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.
- In added
yhat.GraphLearner()
and
model_info.GraphLearner()
to handle GraphLearners
mlr3
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()
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
.
explain_h2o()
now supports model
as
H2OAutoML
- 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()
and
plot.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 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.
- 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.