code: def continuous(request):
      """
      Creates a random continuous regression dataset fixture
      """
      X, y = make_regression(
          n_samples=500,
          n_features=22,
          n_informative=8,
          random_state=42,
          noise=0.2,
          bias=0.2,
      )
  
      X_train, X_test, y_train, y_test = tts(
          X, y, test_size=0.2, random_state=11
      )
  
      # Set a class attribute for regression
      request.cls.continuous = Dataset(
          Split(X_train, X_test), Split(y_train, y_test)
      )
  
imports: import pytest
  from io import BytesIO
  from tests.fixtures import Dataset, Split
  from tests.base import IS_WINDOWS_OR_CONDA, VisualTestCase
  from sklearn.naive_bayes import GaussianNB
  from sklearn.cluster import MiniBatchKMeans
  from sklearn.linear_model import LinearRegression
  from sklearn.model_selection import train_test_split
  from sklearn.datasets import make_classification, make_regression, make_blobs
  from yellowbrick.contrib.prepredict import *
  from yellowbrick.regressor import PredictionError
  from yellowbrick.classifier import ClassificationReport
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: continuous(request) without return types