code: def dataset(request):
      """
      Creates a multiclass classification dataset fixture for RFECV
      """
      X, y = make_classification(
          n_samples=300,
          n_features=5,
          n_informative=3,
          n_repeated=0,
          n_classes=4,
          n_clusters_per_class=1,
          random_state=0,
      )
  
      dataset = Dataset(X, y)
      request.cls.dataset = dataset
  
imports: import sys
  import pytest
  import numpy
  import numpy.testing
  from unittest.mock import patch
  from tests.fixtures import Dataset
  from tests.base import VisualTestCase
  from yellowbrick.model_selection.rfecv import *
  from yellowbrick.datasets import load_occupancy
  from yellowbrick.exceptions import YellowbrickValueError
  from sklearn.svm import SVC
  from sklearn.datasets import make_classification
  from sklearn.model_selection import ShuffleSplit
  from sklearn.model_selection import StratifiedKFold
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import RandomForestClassifier
label_desc: Use image node_id 1 for calling a global function with example usage: dataset(request) without return types