class_docstr: Test the LearningCurve visualizer
docstr: Test supplying an alternate CV methodology and train_sizes
docstr_tok: ["Test","supplying","an","alternate","CV","methodology","and","train_sizes"]
code: def test_reshape_scores(self, mock_draw):
      """
      Test supplying an alternate CV methodology and train_sizes
      """
      X, y = self.classification
  
      cv = ShuffleSplit(n_splits=12, test_size=0.2, random_state=14)
      oz = LearningCurve(
          LinearSVC(), cv=cv, train_sizes=[0.5, 0.75, 1.0]
      )
      oz.fit(X, y)
  
      assert oz.train_scores_.shape == (3, 12)
      assert oz.test_scores_.shape == (3, 12)
  
imports: import sys
  import pytest
  import numpy
  from unittest.mock import patch
  from tests.base import VisualTestCase
  from sklearn.svm import LinearSVC
  from sklearn.linear_model import Ridge
  from sklearn.naive_bayes import GaussianNB, MultinomialNB
  from sklearn.cluster import MiniBatchKMeans
  from sklearn.preprocessing import OneHotEncoder, LabelEncoder
  from sklearn.impute import SimpleImputer
  from sklearn.model_selection import ShuffleSplit
  from sklearn.model_selection import StratifiedKFold
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.pipeline import Pipeline
  from yellowbrick.datasets import load_mushroom, load_game
  from yellowbrick.model_selection.learning_curve import *
label_desc: Use image node_id 8 for calling the TestLearningCurve obj's underlying member method code with example usage: obj.test_reshape_scores(mock_draw) without return types