treeshap (development
version)
treeshap 0.4.0
- Cleanup in #52 (https://github.com/ModelOriented/treeshap/pull/52).
Thanks @kapsner
- Fixed xgboost api and add depends R>=4.1.0 as in #51
(https://github.com/ModelOriented/treeshap/pull/51). Thanks @kapsner
- Fix ranger.unify for probability forests as in #43
(https://github.com/ModelOriented/treeshap/pull/43). Thanks @ck37
- Added support for GPBoost as in #41
(https://github.com/ModelOriented/treeshap/pull/41). Thanks @fabsig
treeshap 0.3.1
- Fixed code examples in
lightgbm.unify.
treeshap 0.3.0
- Fixed
ranger_surv.unify operation for predictions in
form of survival and cumulative hazard functions.
- Added
model_unified_multioutput and
treeshap_multioutput classes for multi-output models and
their explanations.
- Improved documentation of
ranger_surv.unify.
treeshap 0.2.5
- Removed
catboost.unify function (as the
catboost package is not on CRAN); it is available on a
separate branch
- Fixed
randomForest.unify for classifiers (#12, #23)
- Implemented consolidated (generic)
unify function (#18)
- An error is thrown when the data passed to the
unify or
treeshap functions contain variables that are not used by
the model (#14)
- Added implementation for random survival forests created using
ranger (#22, #26)
- Fixed GitHub Actions, check and test issues (#25, #29)
- Fixed issues with documentation and examples
- Changed use of bitwise ‘|’ to logical ‘||’ with boolean operands in
C++ files
treeshap 0.1.1
- Fixed
plot_contribution when max_vars is
larger than the number of variables (#16)
treeshap 0.1.0
- Rebuilded treeshap function so it now stores observations and whole
dataset
- Rebuilded all unifiers so they require passing data.
treeshap 0.0.1
- Made package pass all checks
- Fixed infinite recursion issue in ranger (see
commit)
- If there is no missing value in the model, unifiers return
NA for Missing column (see
commit)
treeshap 0.0.0.9000
- treeshap is now public
- Implemented fast computations of tree ensemble shap values in
C++
- Implemented unifiers for catboost, lightgbm, xgboost, gbm, ranger
and randomForest