code: def test_oneclass():
      y = np.array([0, 0, 0])
      mc = BlankClassifier()
      out = mc._one_hot(y=y, n_labels=1, dtype="float")
      expect = np.array([[1.0], [1.0], [1.0]])
      np.testing.assert_array_equal(expect, out)
  
imports: import numpy
  from mlxtend._base import _MultiClass
label_desc: Use image node_id 2 for calling a global function with example usage: test_oneclass() without return types