ExplainerError

[hasan-sayeed]

For my dataset I'm getting this error:

ExplainerError: Additivity check failed in TreeExplainer! Please ensure the data matrix you passed to the explainer is the same
shape that the model was trained on. If your data shape is correct then please report this on GitHub. Consider retrying with the 
feature_perturbation='interventional' option. This check failed because for one of the samples the sum of the SHAP values was 
-0.577556, while the model output was -0.540311. If this difference is acceptable you can set check_additivity=False to disable 
this check.

I'm using it like this:

model = BoostRFE(regr_xgb, param_grid=param_dist, 
                               min_features_to_select=10, 
                               step=20, 
                               importance_type='shap_importances',
                               n_iter=5
                               )

Any suggestion how to solve this?

[cerlymarco]

Hi, thanks for your feedback.
This error comes from shap. I think a possible cause could be this one.
With the information you reported it's hard to say more. You should clarify more about your X_train/X_valid to have a better view (some data samples to reproduce the error should be perfect)

[hasan-sayeed]

I am using shap-hypetune for one of my works. How can I cite this?

[cerlymarco]

Hi @hasan-sayeed

From my point of view, you can simply cite the project reporting the link and the name of the library

If you support the project don't forget to leave a star ;-)