Hubert Baniecki
Hubert Baniecki
closes #503 hopefully fixes our CI and conda CI
possibly the cause of broken CI in https://github.com/conda-forge/dalex-feedstock/pull/6 set a temporary requirement for the dependencies: `werkzeug` < 2.1
Some random `numpy` error breaks our Python 3.10 CI https://stackoverflow.com/questions/71448239/valueerror-numpy-ndarray-size-changed-may-indicate-binary-incompatibility-exp
...and possibly remove the conversion from pandas to numpy in ShapWrapper. Then, `explainer.model_info['arrays_accepted']` would become redundant, which in fact fixes https://github.com/ModelOriented/DALEX/issues/507 by making the scikit Pipeline fail gracefully in the...
update code for newer versions of `pandas`
if `model_type` is not None --> override guessing of `classification`/`regression` https://github.com/ModelOriented/DALEX/blob/daf33cbe54f0b624973722f4d208cb5edaa55cb4/python/dalex/dalex/_explainer/checks.py#L184
In a general case, it would be a possible fix to #109 while the issue might still be rather xgboost-specific.
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https://github.com/openjournals/joss-reviews/issues/3934 Hi, I hope these comments help in improving the paper. **Comments** 1. The paper's title could see a change. It says "PySS3: A new interpretable and simple machine learning...
AAAI 2022 https://arxiv.org/abs/2112.09669