code: def load_usps0_noisy():
      X_train, y_train, X_test, y_test = load_usps0()
      n_samples = X_train.shape[0]
      indices = np.arange(n_samples)
      random_state = check_random_state(0)
      random_state.shuffle(indices)
      n = n_samples / 10
      indices = indices[:n]
      y_train[indices] = np.logical_not(y_train[indices]).astype(int)
      return X_train, y_train, X_test, y_test
  
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 19 for calling a global function with example usage: load_usps0_noisy() and returns: X_train,  y_train,  X_test,  y_test