code: def _make_classification_data(n_samples, n_features, n_classes, seed):
      rnd = np.random.RandomState(seed)
  
      x = _make_features(n_samples, n_features, seed)
      y = rnd.binomial(n_classes - 1, 0.2, 100)
      return x, y
  
imports: from contextlib import ExitStack
  from contextlib import nullcontext
  from io import StringIO
  import os
  import tempfile
  import numpy
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  import pandas
  import pandas.testing
  import pytest
  import sksurv.datasets
  from sksurv.io import writearff
  from sksurv.testing import FixtureParameterFactory
label_desc: Use image node_id 4 for calling a global function with example usage: _make_classification_data(n_samples, n_features, n_classes, seed) and returns: x,  y