code: def data(request):
      """
      Creates a random regression fixture that has a R2 score below 0.85 and several
      outliers that best demonstrate the effectiveness of influence visualizers.
      """
      X, y = make_regression(
          n_samples=100,
          n_features=14,
          n_informative=6,
          bias=1.2,
          noise=49.8,
          tail_strength=0.6,
          random_state=637,
      )
  
      request.cls.data = Dataset(X, y)
  
file_path: yellowbrick/tests/test_regressor/test_influence.py
imports: import pytest
  import numpy
  import matplotlib.pyplot
  from tests.base import VisualTestCase
  from tests.fixtures import Dataset
  from sklearn.datasets import make_regression
  from yellowbrick.regressor.influence import *
  from yellowbrick.datasets import load_concrete
label_desc: Use image node_id 1 for calling a global function with example usage: data(request) without return types