code: def test_sklearn_linear():
      Ridge = pytest.importorskip("sklearn.linear_model").Ridge
  
      # train linear model
      X, y = shap.datasets.california(n_points=100)
      model = Ridge(0.1)
      model.fit(X, y)
  
      # explain the model's predictions using SHAP values
      explainer = shap.LinearExplainer(model, X)
      assert (
          np.abs(explainer.expected_value - model.predict(X).mean())
          < 1e-6
      )
      explainer.shap_values(X)
  
file_path: shap/tests/explainers/test_linear.py
imports: import numpy
  import pytest
  import scipy.special
  import shap
label_desc: Use image node_id 6 for calling a global function with example usage: test_sklearn_linear() without return types