code: def make_synthetic_regression(
      n_samples=100, n_features=4, n_informative=2, random_state=42
  ):
      return sklearn.datasets.make_regression(
          n_samples=n_samples,
          n_features=n_features,
          n_informative=n_informative,
          random_state=random_state,
      )
  
imports: import pickle
  from functools import lru_cache
  from inspect import getfullargspec
  import cloudpickle
  import joblib
  import numpy
  import sklearn.datasets
  from sklearn.utils import check_random_state
  import lightgbm
label_desc: Use image node_id 6 for calling a global function with example usage: make_synthetic_regression(n_samples, n_features, n_informative, random_state) and returns: sklearn