code: def test_kernel_shap_with_call_method():
      """Test the __call__ method of the Kernel class"""
  
      # print the JS visualization code to the notebook
      shap.initjs()
  
      # train a SVM classifier
      (
          X_train,
          X_test,
          Y_train,
          _,
      ) = sklearn.model_selection.train_test_split(
          *shap.datasets.iris(), test_size=0.1, 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.KernelExplainer(
          svm.predict_proba, X_train, nsamples=100, link="logit"
      )
      shap_values = explainer(X_test)
  
      # plot the SHAP values for the Versicolour output of the first instance
      shap.force_plot(shap_values[0][:, 1])
  
file_path: shap/tests/explainers/test_kernel.py
imports: import numpy
  import pandas
  import scipy.sparse
  import sklearn
  import shap
label_desc: Use image node_id 5 for calling a global function with example usage: test_kernel_shap_with_call_method() without return types