code: def ensemble():
      """Fit ensemble."""
      print("Fitting ENS...", end=" ", flush=True)
      time.sleep(SLEEP)
      t0 = time.time()
      ens = build_ensemble(shuffle=False, folds=2)
      ens.fit(X, y)
      print_time(t0, "Done", end="")
  
file_path: mlens/benchmarks/friedman_memory.py
imports: import numpy
  from mlens.utils import print_time
  from mlens.ensemble import SuperLearner
  from sklearn.datasets import make_friedman1
  from sklearn.linear_model import Lasso, ElasticNet
  from sklearn.neighbors import KNeighborsRegressor
  import time
label_desc: Use image node_id 2 for calling a global function with example usage: ensemble() without return types