code: def test_fit_predict(self):
      metric = Metric({"name": "logloss"})
      lgb = LightgbmAlgorithm(self.params)
      lgb.fit(self.X, self.y)
      y_predicted = lgb.predict(self.X)
      loss = metric(self.y, y_predicted)
      self.assertTrue(loss < 0.7)
  
imports: import unittest
  import tempfile
  import json
  import copy
  import os
  import numpy
  import pandas
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from supervised.algorithms.lightgbm import LightgbmAlgorithm, additional
  from supervised.utils.metric import Metric
label_desc: Use image node_id 3 for calling the LightgbmAlgorithmTest obj's underlying member method code with example usage: obj.test_fit_predict() without return types