class_docstr: Test FeatureImportances visualizer
docstr: Test incorrectly using stack param on a dataset with two classes which
  does not return a coef_ array in the shape of (n_classes, n_features)
docstr_tok: ["Test","incorrectly","using","stack","param","on","a","dataset","with","two","classes","which","does","not","return","a","coef_","array","in","the","shape","of","(","n_classes",",","n_features",")"]
code: def test_stack_param_incorrectly_used_throws_error(self):
      """
      Test incorrectly using stack param on a dataset with two classes which
      does not return a coef_ array in the shape of (n_classes, n_features)
      """
      X, y = load_occupancy()
  
      viz = FeatureImportances(
          LogisticRegression(solver="liblinear", random_state=222),
          stack=True,
      )
  
      expected_error = "The model used does not return coef_ array"
  
      with pytest.raises(YellowbrickValueError, match=expected_error):
          viz.fit(X, y)
  
imports: import pytest
  import numpy
  import numpy.testing
  import matplotlib.pyplot
  from yellowbrick.exceptions import NotFitted
  from yellowbrick.model_selection.importances import *
  from yellowbrick.datasets import load_occupancy, load_concrete
  from sklearn.datasets import load_iris
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.ensemble import GradientBoostingClassifier
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.linear_model import LogisticRegression, Lasso
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import Pipeline
  from unittest import mock
  from tests.base import VisualTestCase
label_desc: Use image node_id 11 for calling the TestFeatureImportancesVisualizer obj's underlying member method code with example usage: obj.test_stack_param_incorrectly_used_throws_error() without return types