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)
      ss = StaticSelection(pool)
      ss.fit(X, y)
      pred = ss.predict(X)
      assert np.isin(ss.classes_, pred).all()
  
imports: import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.ensemble import AdaBoostClassifier
  from sklearn.exceptions import NotFittedError
  from sklearn.metrics import log_loss
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.static.static_selection import StaticSelection
label_desc: Use image node_id 9 for calling a global function with example usage: test_label_encoder_base_ensemble() without return types