Releases · NorskRegnesentral/shapr

Spelling checking and other minor clean up #431)
Add extra_computation_args and output_args to explain_forecast() #428)
Rename vaeac plotting functions #428)
Move explain() arguments paired_shap_sampling and kernelSHAP_reweighting into extra_computation_args #428)
Improved and unified the documentation #427)
Remove seed argument from the boostrap function as its better handled by the mother function #427)
Renamed various internal functions to be consistent with names in the rest of the package #427)
Remove MSEv from explain_forecast (as it was only supported for horizon=1). Should return in a more general manner in the future #427)
Improve efficiency of coalition sampling code and move to string sampling #426)
Bugfix iterative = TRUE for explain_forecast() which was not using coalitions from previous iterations #426)
Bugfix the handling and output with the verbose argument for explain_forecast() #425)
Improved flexibility of the beeswarm plot functionality #424)
Bugfix edge case where the party package returns a constparty object #423)
Bugfix error due to extra comma in rarely used warning #422)
Shined up the vignettes a bit #421)
Bugfix keep_samp_for_vS with iterative approach #417)
[Python] Brought the python code base up to speed with essentially all functionality in explain() in R #416)
Please CRAN with dontrun on long running examples + skip_on_cran for the parallelized tests.

Added support for groupSHAP, including check of appropriate groups, examples and tests
Various modifications to input of internal functions to reflect that Shapley values may be
computed both feature-wise and group-wise
Fixed bug when passing non-named data to shapr() or explain() (e.g. shapr(data[,1:5],model...)

Patch to fix failing CRAN-tests on R-devel due to changed behavior of attach(): Fixed by changing how we simluate adding a function to .GlobalEnv in the failing test. Actual package not affected.

Patch to fix warning from development version of data.table due to the use of nomatch argument in merge(),
as requested from data.table developers.

NOTE: Use the files named shapr_0.2.1... (not source code)

Minor CRAN release
Added the new dependence modeling approach "ctree" which handles categorical features in addition
to numerical ones. For more information see our paper https://doi.org/10.1007/978-3-030-57321-8_7
Added support to explain models which take as input categorical features for model classes like xgboost
which originally takes only numeric input. On the user side, an additional call to the new make_dummies
function is required. See the vignette for details.
Slight change in the user procedure for explaining predictions from custom models. This now requires
only a single function predict_model.
Introduced a thorough system for extracting and checking the feature information in the model and the data
passed to shapr and explain. The features in the data are checked for consistency with what can be extracted
from the model object. If the model object is missing some of the necessary information, the info from the data
is used instead. The system checks feature labels, classes, and any factor levels.
Due to the previous point, the feature_labels option previously used for custom models is removed.
Added a manual testing script for custom model (currently cannot be handled by testthat due to environment issues).
A few under-the-hood changes for checking in the shapr function.

Patch to fulfill CRAN policy of using packages under Suggests conditionally (in tests and examples)

CRAN release
Removed unused clustering code
Removed several package dependencies
Moved automatic check and pkgdown site build from Circle CI to GitHub actions
Some minor efficiency fixes
Changed stopping threshold from 12 to 13 features for none-sampling version of
KernelSHAP for consistency with our recommendation
Changed package title (shortened)
Minor fixes to fulfill CRAN policy
Improved documentation
Revised internal/external and exported/non-exported functions, leading to far
fewer external functions and a cleaner manual.

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