code: def load_covtype_subset():
      X_train, y_train, _, _ = load_covtype()
      cv = StratifiedShuffleSplit(
          y_train,
          train_size=100000,
          test_size=50000,
          n_iterations=1,
          random_state=0,
      )
      tr, te = iter(cv).next()
      return X_train[tr], y_train[tr], X_train[te], y_train[te]
  
imports: import os
  import numpy
  import scipy.sparse
  from sklearn.datasets.base import get_data_home
  from sklearn.utils import check_random_state
label_desc: Use image node_id 12 for calling a global function with example usage: load_covtype_subset() and returns: X_train,  y_train,  X_train,  y_train