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py-why / EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
https://www.microsoft.com/en-us/research/project/alice/
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Fix `shap_values` compatibility with shap>=0.43.0 by adjusting `check_additivity` parameter handling for `TreeExplainer` #872

Closed jcreinhold closed 5 months ago

jcreinhold commented 5 months ago

This addresses the issue where the shap_values method in EconML did not correctly set check_additivity=False for shap>=0.43.0 due to a class name change from Tree to TreeExplainer​.

See #866 for details.

jcreinhold commented 5 months ago

Adding @kbattocchi for review.

jcreinhold commented 5 months ago

Great! I'm happy to add the seed functionality, but I think it's be best to add it to another PR. Ideally, I'll be able to add it within a week or so, but I might get pulled into something which will push back that timeline.