class_docstr: Test the ClassificationScoreVisualizer base functionality
docstr: Test class and class counts identification
docstr_tok: ["Test","class","and","class","counts","identification"]
code: def test_class_counts(self):
      """
      Test class and class counts identification
      """
      oz = ClassificationScoreVisualizer(GaussianNB())
      oz.fit(self.multiclass.X.train, self.multiclass.y.train)
  
      unique, counts = np.unique(
          self.multiclass.y.train, return_counts=True
      )
      npt.assert_array_equal(oz.classes_, unique)
      npt.assert_array_equal(oz.class_counts_, counts)
  
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 2 for calling the TestClassificationScoreVisualizer obj's underlying member method code with example usage: obj.test_class_counts() without return types