code: def test_auto_detect_categorical():
      """Assert that automatic selection of categorical features works as expected with a threshold of 10."""
      selected = auto_select_categorical_features(
          iris_data[0:16, :], threshold=10
      )
      expected = [False, False, True, True]
  
      assert_equal(selected, expected)
  
imports: import numpy
  import scipy.sparse
  from numpy.testing import assert_array_almost_equal
  from sklearn.datasets import load_iris, load_boston
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import make_pipeline
  from sklearn.model_selection import cross_val_score, KFold
  from nose.tools import assert_equal
  from tpot.builtins import OneHotEncoder, auto_select_categorical_features, _transform_selected
label_desc: Use image node_id 3 for calling a global function with example usage: test_auto_detect_categorical() without return types