Explaining instances of a machine learning regressor I trained an XGBoost regressor, and I'm looking for a way to interpret new instances that the model will receive in production.
There's a nice solution for classification models (Lime), but it doesn't offer explanations to regression problems. 

Does anyone know of an existing "explainer" for regressions?
Lime introduced support for regression problems in their latest version. A notebook with examples is available here.