code: def test_remove_outlier(mocker):
      mock_outlier_detector = mocker.Mock()
      mock_outlier_detector.fit.return_value = None
      mock_outlier_detector.predict.return_value = np.array([-1])
      mocker.patch(
          "sklego.preprocessing.outlier_remover.clone"
      ).return_value = mock_outlier_detector
  
      outlier_remover = OutlierRemover(
          outlier_detector=mock_outlier_detector, refit=True
      )
      outlier_remover.fit(X=np.array([[5, 5]]))
      assert (
          len(outlier_remover.transform_train(np.array([[0, 0]]))) == 0
      )
  
file_path: scikit-lego/tests/test_preprocessing/test_outlier_remover.py
imports: import numpy
  import pytest
  from sklearn.cluster import KMeans
  from sklearn.ensemble import IsolationForest
  from sklearn.pipeline import Pipeline
  from sklearn.utils import estimator_checks
  from sklego.common import flatten
  from sklego.mixture import GMMOutlierDetector
  from sklego.preprocessing import OutlierRemover
label_desc: Use image node_id 3 for calling a global function with example usage: test_remove_outlier(mocker) without return types