code: def test_estimate_competence_diff_target(
      index, example_estimate_competence
  ):
      (
          _,
          _,
          neighbors,
          distances,
          dsel_processed,
          _,
      ) = example_estimate_competence
  
      mla_test = MLA()
      mla_test.n_classifiers_ = 3
  
      mla_test.DSEL_processed_ = dsel_processed
      mla_test.DSEL_target_ = np.ones(15, dtype=int) * 3
  
      neighbors = neighbors[index, :].reshape(1, -1)
      distances = distances[index, :].reshape(1, -1)
  
      expected = [0.0, 0.0, 0.0]
  
      predictions = np.array([[0, 1, 0]])
  
      competences = mla_test.estimate_competence(
          neighbors, distances=distances, predictions=predictions
      )
  
      assert np.isclose(competences, expected).all()
  
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 4 for calling a global function with example usage: test_estimate_competence_diff_target(index, example_estimate_competence) without return types