code: def test_estimate_competence_batch(example_estimate_competence):
      (
          _,
          y,
          neighbors,
          distances,
          dsel_processed,
          _,
      ) = example_estimate_competence
  
      expected = np.array(
          [
              [0.75000000, 0.66666667, 0.75000000],
              [0.80000000, 1.00000000, 0.80000000],
              [1.00000000, 0.60000000, 0.50000000],
          ]
      )
      lca_test = LCA()
      lca_test.DSEL_processed_ = dsel_processed
      lca_test.DSEL_target_ = y
  
      query = np.ones((3, 2))
  
      predictions = np.array([[0, 1, 0]])
      competences = lca_test.estimate_competence(
          neighbors,
          distances=distances,
          predictions=np.array(predictions),
      )
  
      assert np.isclose(competences, expected).all()
  
file_path: DESlib/deslib/tests/dcs/test_lca.py
imports: import numpy
  import pytest
  from sklearn.linear_model import Perceptron
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.dcs.lca import LCA
label_desc: Use image node_id 2 for calling a global function with example usage: test_estimate_competence_batch(example_estimate_competence) without return types