class_docstr: Test the RFECV visualizer
class_docstr_tok: ["Test","the","RFECV","visualizer"]
docstr: Assert that fit returns self and creates expected properties with NB
docstr_tok: ["Assert","that","fit","returns","self","and","creates","expected","properties","with","NB"]
code: def test_fit(self, mock_draw):
      """
      Assert that fit returns self and creates expected properties with NB
      """
      X, y = self.dataset
      params = (
          "n_features_",
          "support_",
          "ranking_",
          "cv_scores_",
          "rfe_estimator_",
          "n_feature_subsets_",
      )
  
      rf = RandomForestClassifier()
      oz = RFECV(rf)
      for param in params:
          assert not hasattr(oz, param)
  
      # Assert original estimator is wrapped
      assert oz._wrapped is rf
  
      assert oz.fit(X, y) is oz
      mock_draw.assert_called_once()
  
      for param in params:
          assert hasattr(oz, param)
  
      # Assert rfe estimator is now wrapped
      assert oz._wrapped is not rf
      assert oz._wrapped is oz.rfe_estimator_
  
imports: import sys
  import pytest
  import numpy
  import numpy.testing
  from unittest.mock import patch
  from tests.fixtures import Dataset
  from tests.base import VisualTestCase
  from yellowbrick.model_selection.rfecv import *
  from yellowbrick.datasets import load_occupancy
  from yellowbrick.exceptions import YellowbrickValueError
  from sklearn.svm import SVC
  from sklearn.datasets import make_classification
  from sklearn.model_selection import ShuffleSplit
  from sklearn.model_selection import StratifiedKFold
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import RandomForestClassifier
label_desc: Use image node_id 1 for calling the TestRFECV obj's underlying member method code with example usage: obj.test_fit(mock_draw) without return types