code: def test_fit(create_pool_classifiers, create_X_y):
      X, y = create_X_y
  
      a_priori_test = APriori(create_pool_classifiers)
      a_priori_test.fit(X, y)
      expected = np.array([[0.5, 0.5], [1.0, 0.0], [0.33, 0.67]])
      expected = np.tile(expected, (15, 1, 1))
      assert np.array_equal(a_priori_test.dsel_scores_, expected)
  
file_path: DESlib/deslib/tests/dcs/test_a_priori.py
imports: import numpy
  import pytest
  from sklearn.linear_model import Perceptron
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.dcs.a_priori import APriori
label_desc: Use image node_id 5 for calling a global function with example usage: test_fit(create_pool_classifiers, create_X_y) without return types