We are running into a weird issue in analyzing its SHAP values (by .setContribPredictionCol) from scala spark xgboost v0.81 on CDH. The issue is that:
- for classification, our model has 814 features, but output SHAP field has only 813 values, by default we should have 815 values (for bias term as the last one)
- for regression, we don’t have this issue.
Did we missed something for SHAP in classification? or is it a bug?