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SHAP values and treatment effect values for causal forest #527

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abdollahpouri opened this issue Jul 5, 2022 · 2 comments
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SHAP values and treatment effect values for causal forest #527

abdollahpouri opened this issue Jul 5, 2022 · 2 comments
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enhancement New feature or request

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@abdollahpouri
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Hello,
I have been following one of the examples (here) and I see the meta learners have a . get_shap_values and plot_shap_values methods for SHAP values. Also, I think they have a fit_predict method to get the individual treatment effects. But I don't see the same methods for the causal forest approach. Can I ask how we can get those for the causal forest?

@abdollahpouri abdollahpouri added the enhancement New feature or request label Jul 5, 2022
@alexander-pv
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alexander-pv commented Aug 8, 2022

Hi, CausalTreeRegressor and CausalRandomForestRegressor in #522 could be interpreted directly via shap (shap.TreeExplainer) with minor package update. See example.

I could open new PR for this feature and PR for causalml support in shap but #522 is still open. So we need some time to get it reviewed and merged.

@alexander-pv
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Hi, the related PR #536 is open now.

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