code: def test_reproduce_fit_regression(self):
      metric = Metric({"name": "rmse"})
      params = {"max_depth": 1, "seed": 1, "ml_task": "regression"}
      prev_loss = None
      for _ in range(3):
          model = DecisionTreeRegressorAlgorithm(params)
          model.fit(self.X, self.y)
          y_predicted = model.predict(self.X)
          loss = metric(self.y, y_predicted)
          if prev_loss is not None:
              assert_almost_equal(prev_loss, loss)
          prev_loss = loss
  
file_path: mljar-supervised/tests/tests_algorithms/test_decision_tree.py
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 supervised.algorithms.decision_tree import DecisionTreeAlgorithm, DecisionTreeRegressorAlgorithm
  from supervised.utils.metric import Metric
  import tempfile
label_desc: Use image node_id 2 for calling the DecisionTreeTest obj's underlying member method code with example usage: obj.test_reproduce_fit_regression() without return types