code: def test_large_samples(self):
      X = np.array(["a", "b", "b", "c", "d"])
      y = np.array([1, 0, 1, 0, 0])
      out = encoders.JamesSteinEncoder(
          return_df=False, model="independent"
      ).fit_transform(X, y)
      self.assertNotEqual(
          [1, 0.5, 0.5, 0, 0],
          list(out),
          "Shrinkage should kick in with 4 or more unique values",
      )
      self.assertTrue(
          np.max(out) <= 1, "This should still be a probability"
      )
      self.assertTrue(
          np.min(out) >= 0, "This should still be a probability"
      )
  
imports: from unittest import TestCase
  import numpy
  import category_encoders
label_desc: Use image node_id 2 for calling the TestJamesSteinEncoder obj's underlying member method code with example usage: obj.test_large_samples() without return types