code: def test_label_encoder_only_dsel():
      X_dsel_ex1 = np.array([[-1, 1], [-0.75, 0.5], [-1.5, 1.5]])
      y_dsel_ex1 = np.array(["cat", "dog", "plane"])
  
      query = np.atleast_2d([[1, 0], [-1, -1]])
      ds_test = BaseDS(create_pool_classifiers_dog_cat_plane(), k=2)
      ds_test.fit(X_dsel_ex1, y_dsel_ex1)
  
      ds_test.classify_with_ds = Mock()
      ds_test.classify_with_ds.return_value = [1, 0]
      predictions = ds_test.predict(query)
      assert np.array_equal(predictions, ["dog", "cat"])
  
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 28 for calling a global function with example usage: test_label_encoder_only_dsel() without return types