code: def test_predict_proba_IH_knn(
      index, example_estimate_competence, create_pool_classifiers
  ):
      (
          X,
          y,
          neighbors,
          distances,
          _,
          dsel_scores,
      ) = example_estimate_competence
      query = np.atleast_2d([1, 1])
      ds_test = BaseDS(
          create_pool_classifiers, with_IH=True, IH_rate=0.5
      )
      ds_test.fit(X, y)
      ds_test.DSEL_scores = dsel_scores
  
      neighbors = neighbors[index, :]
      distances = distances[index, :]
  
      ds_test.get_competence_region = MagicMock(
          return_value=(distances, neighbors)
      )
  
      ds_test.roc_algorithm_.predict_proba = MagicMock(
          return_value=np.atleast_2d([0.45, 0.55])
      )
      proba = ds_test.predict_proba(query)
      assert np.array_equal(proba, np.atleast_2d([0.45, 0.55]))
  
imports: import unittest.mock
  from unittest.mock import Mock, MagicMock
  import numpy
  import pytest
  from sklearn.exceptions import NotFittedError
  from sklearn.neighbors import KNeighborsClassifier
  from deslib.base import BaseDS
  from deslib.util.dfp import frienemy_pruning_preprocessed
  from .conftest import create_base_classifier
label_desc: Use image node_id 23 for calling a global function with example usage: test_predict_proba_IH_knn(index, example_estimate_competence, create_pool_classifiers) without return types