code: def test_multiclass_positive_label_0():
      y_targ = [1, 1, 1, 0, 0, 2, 0, 3, 4]
      y_pred = [1, 0, 1, 0, 0, 2, 1, 3, 0]
      x = 1.5
      y = lift_score(y_targ, y_pred, binary=True, positive_label=0)
      assert_array_equal(x, y)
  
file_path: mlxtend/mlxtend/evaluate/tests/test_lift_score.py
imports: import numpy
  from numpy.testing import assert_array_equal, assert_raises
  from mlxtend.evaluate import lift_score
  from mlxtend.evaluate.lift_score import support
label_desc: Use image node_id 2 for calling a global function with example usage: test_multiclass_positive_label_0() without return types