v0.5.0
v0.5.0 (2020-06-10)
This version supports Python 3.6 and 3.7 as support for Python 3.5 is dropped.
Added
- New feature
TreeSHAP
explainer for white-box, tree based model SHAP value computation - New feature
ALE
explainer for computing feature effects for black-box, tabular data models - New feature
IntegratedGradients
explainer for computing feature attributions for TensorFlow and Keras models - Experimental
utils.visualization
module currently containing visualization functions forIntegratedGradients
on image datasets.The location, implementation and content of the module and functions therein are subject to change. - Extend
datasets.fetch_imagenet
to work with any class - Extend
utils.data.gen_category_map
to take a list of strings of column names
Changed
- Internal refactoring of
KernelSHAP
to reuse functionality forTreeSHAP
. Both SHAP wrappers
are now underexplainers.shap_wrappers
- Tests are now split into two runs, one with TensorFlow in eager mode which is necessary for using
IntegratedGradients
- Added
typing-extensions
library as a requirement to take advantage of more precise types - Pinned
scikit-image<0.17
due to a regression upstream - Pinned
Sphinx<3.0
for documentation builds due to some issues with them2r
plugin
Fixed
- Various improvements to documentation
- Some tests were importing old
keras
functions instead oftensorflow.keras