code: def test_label_encoder_base_ensemble():
      from sklearn.ensemble import RandomForestClassifier
  
      X, y = make_classification()
      y[y == 1] = 2
      y = y.astype(float)
      pool = RandomForestClassifier().fit(X, y)
      sb = SingleBest(pool)
      sb.fit(X, y)
      pred = sb.predict(X)
      assert np.isin(sb.classes_, pred).all()
  
file_path: DESlib/deslib/tests/static/test_single_best.py
imports: from unittest.mock import MagicMock
  import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.ensemble import AdaBoostClassifier
  from sklearn.exceptions import NotFittedError
  from sklearn.metrics import roc_auc_score
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.static.single_best import SingleBest
label_desc: Use image node_id 8 for calling a global function with example usage: test_label_encoder_base_ensemble() without return types