class_docstr: Test the ClassificationScoreVisualizer base functionality
docstr: Assert fitted estimator can be scored without fit but warns
docstr_tok: ["Assert","fitted","estimator","can","be","scored","without","fit","but","warns"]
code: def test_score_with_fitted_estimator(self):
      """
      Assert fitted estimator can be scored without fit but warns
      """
      model = GaussianNB().fit(self.binary.X.train, self.binary.y.train)
  
      # NOTE that the wrapper will pass a call down to `classes_`
      oz = ClassificationScoreVisualizer(model)
      assert_not_fitted(oz, ["class_counts_", "score_"])
  
      msg = "could not determine class_counts_"
      with pytest.warns(YellowbrickWarning, match=msg):
          oz.score(self.binary.X.test, self.binary.y.test)
          assert_fitted(oz, ["classes_", "class_counts_", "score_"])
  
imports: import pytest
  import numpy
  import numpy.testing
  from yellowbrick.classifier.base import *
  from sklearn.naive_bayes import GaussianNB
  from sklearn.preprocessing import LabelEncoder
  from sklearn.linear_model import LinearRegression
  from .conftest import assert_fitted, assert_not_fitted
  from yellowbrick.exceptions import YellowbrickTypeError
label_desc: Use image node_id 4 for calling the TestClassificationScoreVisualizer obj's underlying member method code with example usage: obj.test_score_with_fitted_estimator() without return types