code: def test_label_encoder():
      y = ["one", "one", "one", "zero", "zero", "two"]
      X = np.random.rand(6, 3)
      pool = [DecisionTreeClassifier().fit(X, y) for _ in range(5)]
      stacked = StackedClassifier(pool).fit(X, y)
      pred = stacked.predict(X)
      assert np.array_equal(pred, y)
  
file_path: DESlib/deslib/tests/static/test_stacked.py
imports: import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.linear_model import Perceptron
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.static.stacked import StackedClassifier
label_desc: Use image node_id 4 for calling a global function with example usage: test_label_encoder() without return types