class_docstr: Test the ClassificationScoreVisualizer base functionality
docstr: Test that string y can be decoded using classes and encoder
docstr_tok: ["Test","that","string","y","can","be","decoded","using","classes","and","encoder"]
code: def test_decode_labels_from_strings(self):
      """
      Test that string y can be decoded using classes and encoder
      """
      classes = np.array(["a", "b", "c", "d", "e"])
      decoded = classes[np.random.randint(0, 5, 100)]
      y = np.array([v.upper() for v in decoded])
  
      oz = ClassificationScoreVisualizer(GaussianNB, classes=classes)
      npt.assert_array_equal(oz._decode_labels(y), decoded)
  
      encoder = {c.upper(): c for c in classes}
      oz = ClassificationScoreVisualizer(GaussianNB, encoder=encoder)
      npt.assert_array_equal(oz._decode_labels(y), decoded)
  
      class L2UTransformer(object):
          def transform(self, y):
              return np.array([yi.upper() for yi in y])
  
          def inverse_transform(self, y):
              return np.array([yi.lower() for yi in y])
  
      oz = ClassificationScoreVisualizer(
          GaussianNB, encoder=L2UTransformer()
      )
      npt.assert_array_equal(oz._decode_labels(y), decoded)
  
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 9 for calling the TestClassificationScoreVisualizer obj's underlying member method code with example usage: obj.test_decode_labels_from_strings() and returns: np, np