code: def test_front_page_model_agnostic():
      sklearn = pytest.importorskip("sklearn")
      train_test_split = pytest.importorskip(
          "sklearn.model_selection"
      ).train_test_split
  
      # print the JS visualization code to the notebook
      shap.initjs()
  
      # train a SVM classifier
      X_train, X_test, Y_train, _ = train_test_split(
          *shap.datasets.iris(), test_size=0.2, random_state=0
      )
      svm = sklearn.svm.SVC(kernel="rbf", probability=True)
      svm.fit(X_train, Y_train)
  
      # use Kernel SHAP to explain test set predictions
      explainer = shap.SamplingExplainer(
          svm.predict_proba, X_train, nsamples=100
      )
      explainer.shap_values(X_test)
  
imports: import numpy
  import pytest
  import shap
label_desc: Use image node_id 4 for calling a global function with example usage: test_front_page_model_agnostic() without return types