Yinxi-Databricks

For a regression model explainer below ``` explainer = LimeTabularExplainer(X_train, feature_names, mode="regression") exp = explainer.explain_instance(X_test[0], model, num_features=11) ``` The returned explanation still has two intercept ``` print(exp.intercept) >>>{0: 6.051529868550603, 1:...