code: def test_estimate_competence_kuncheva_ex(example_kuncheva):
      example_kuncheva = example_kuncheva
  
      mla_test = MLA(k=example_kuncheva["k"])
      mla_test.n_classifiers_ = 2
  
      mla_test.DSEL_processed_ = np.repeat(
          example_kuncheva["dsel_processed"], 2, axis=1
      )
  
      mla_test.dsel_scores_ = example_kuncheva["dsel_scores"]
      mla_test.DSEL_target_ = example_kuncheva["y_dependent"]
      mla_test.n_classes_ = example_kuncheva["n_classes"]
  
      neighbors = example_kuncheva["neighbors"].reshape(1, -1)
      distances = example_kuncheva["distances"].reshape(1, -1)
  
      predictions = np.array([[1, 1]])
      competences = mla_test.estimate_competence(
          neighbors, distances=distances, predictions=predictions
      )
  
      assert np.allclose(competences, [0.95, 0.95], atol=0.01)
  
file_path: DESlib/deslib/tests/dcs/test_mla.py
imports: import numpy
  import pytest
  from sklearn.linear_model import Perceptron
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.dcs.mla import MLA
label_desc: Use image node_id 5 for calling a global function with example usage: test_estimate_competence_kuncheva_ex(example_kuncheva) without return types