code: def test_predict(example_static_selection, create_pool_classifiers):
      X, y, _ = example_static_selection
  
      static_selection_test = StaticSelection(
          create_pool_classifiers * 10, 0.25
      )
      static_selection_test.fit(X, y)
  
      predicted_labels = static_selection_test.predict(X)
      assert np.equal(predicted_labels, 0).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 3 for calling a global function with example usage: test_predict(example_static_selection, create_pool_classifiers) without return types