ModelOriented / ModelOriented/DALEX

Check if `shap` accepts `pd.DataFrame` (and for which Explainers)

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long term 📆 maintenance 🔨 Python 🐍
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Description

...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 downstream package (with an appropriate exception message).

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Research direction

Inspect ShapWrapper and the explainer.model_info['arrays_accepted'] handling first. Check whether shap accepts pandas DataFrames for each relevant Explainer, then determine whether the conversion can be removed. Done means the supported Explainers are established and the scikit Pipeline failure is reported with an appropriate exception message.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Refactor
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

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