code: def test_symbolic_classifier():
      """Check that SymbolicClassifier example works"""
  
      rng = check_random_state(0)
      cancer = load_breast_cancer()
      perm = rng.permutation(cancer.target.size)
      cancer.data = cancer.data[perm]
      cancer.target = cancer.target[perm]
  
      est = SymbolicClassifier(
          parsimony_coefficient=0.01,
          feature_names=cancer.feature_names,
          random_state=1,
      )
      est.fit(cancer.data[:400], cancer.target[:400])
  
      y_true = cancer.target[400:]
      y_score = est.predict_proba(cancer.data[400:])[:, 1]
      assert_almost_equal(
          roc_auc_score(y_true, y_score), 0.96937869822485212
      )
  
      dot_data = est._program.export_graphviz()
      expected = (
          'digraph program {\nnode [style=filled]\n0 [label="sub", '
          'fillcolor="#136ed4"] ;\n1 [label="div", fillcolor="#136ed4"] '
          ';\n2 [label="worst fractal dimension", fillcolor="#60a6f6"] '
          ';\n3 [label="mean concave points", fillcolor="#60a6f6"] '
          ';\n1 -> 3 ;\n1 -> 2 ;\n4 [label="mul", fillcolor="#136ed4"] '
          ';\n5 [label="mean concave points", fillcolor="#60a6f6"] ;\n6 '
          '[label="area error", fillcolor="#60a6f6"] ;\n4 -> 6 ;\n4 -> '
          "5 ;\n0 -> 4 ;\n0 -> 1 ;\n}"
      )
      assert dot_data == expected
  
file_path: gplearn/gplearn/tests/test_examples.py
imports: import numpy
  from sklearn.datasets import load_diabetes, load_breast_cancer
  from sklearn.datasets import make_moons, make_circles, make_classification
  from sklearn.linear_model import Ridge
  from sklearn.metrics import roc_auc_score
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils._testing import assert_almost_equal
  from sklearn.utils.validation import check_random_state
  from gplearn.genetic import SymbolicClassifier, SymbolicRegressor
  from gplearn.genetic import SymbolicTransformer
  from gplearn.functions import make_function
label_desc: Use image node_id 5 for calling a global function with example usage: test_symbolic_classifier() without return types