def METHOD_NAME(self):
    # train model #1
    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)
    # create model #2
    lgb2 = LightgbmAlgorithm(self.params)
    # model #2 is set to None, while initialized
    self.assertTrue(lgb2.model is None)
    # do a copy and use it for predictions
    lgb2 = lgb.copy()
    self.assertEqual(type(lgb), type(lgb2))
    y_predicted = lgb2.predict(self.X)
    loss2 = metric(self.y, y_predicted)
    self.assertEqual(loss, loss2)