code: def test_predict_proba():
      mlp = MLP(
          epochs=20,
          eta=0.05,
          hidden_layers=[10],
          minibatches=1,
          random_seed=1,
      )
      mlp.fit(X, y)
  
      pred = mlp.predict_proba(X[0, np.newaxis])
      exp = np.array([[0.6, 0.2, 0.2]])
      np.testing.assert_almost_equal(pred, exp, decimal=1)
  
file_path: mlxtend/mlxtend/classifier/tests/test_multilayerperceptron.py
imports: import numpy
  from sklearn.base import clone
  from mlxtend.classifier import MultiLayerPerceptron
  from mlxtend.data import iris_data
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 5 for calling a global function with example usage: test_predict_proba() without return types