code: def test_fit_predict(self):
      metric = Metric({"name": "logloss"})
      nn = MLPAlgorithm(self.params)
      nn.fit(self.X, self.y)
      y_predicted = nn.predict(self.X)
      loss = metric(self.y, y_predicted)
      self.assertLess(loss, 2)
  
imports: import unittest
  import tempfile
  import json
  import numpy
  import pandas
  import os
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from sklearn import preprocessing
  from supervised.algorithms.nn import MLPAlgorithm, MLPRegressorAlgorithm
  from supervised.utils.metric import Metric
label_desc: Use image node_id 2 for calling the MultiClassNeuralNetworkAlgorithmTest obj's underlying member method code with example usage: obj.test_fit_predict() without return types