code: def create_diabetes_data():
      """Create Diabetes dataset for regression.
  
      return: Tuple of X_train, X_test, y_train, y_test, feature_names.
      rtype: Tuple of numpy.ndarray, numpy.ndarray, numpy.ndarray,
             numpy.ndarray, list
      """
      diabetes_data = load_diabetes()
      X = diabetes_data.data
      y = diabetes_data.target
      feature_names = diabetes_data.feature_names
  
      X_train, X_test, y_train, y_test = train_test_split(
          X, y, test_size=0.2, random_state=0
      )
      return X_train, X_test, y_train, y_test, feature_names
  
imports: from sklearn.datasets import fetch_california_housing, load_diabetes
  from sklearn.model_selection import train_test_split
  from rai_test_utils.utilities import retrieve_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: create_diabetes_data() and returns: X_train,  X_test,  y_train,  y_test,  feature_names