code: def test_compute_for_regression(self):
      target = np.array([0, 0, 0, 0, 1, 1, 1, 1])
      pred = np.array([0.01, 0.2, 0.1, 0.1, 0.8, 0.8, 0.8, 0.8])
      info = AdditionalMetrics.compute(target, pred, None, REGRESSION)
      all_metrics = list(info["max_metrics"]["Metric"].values)
      for m in ["MAE", "MSE", "RMSE", "R2"]:
          self.assertTrue(m in all_metrics)
  
file_path: mljar-supervised/tests/tests_utils/test_compute_additional_metrics.py
imports: import unittest
  import tempfile
  import json
  import numpy
  import pandas
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from supervised.utils.additional_metrics import AdditionalMetrics
  from supervised.utils.metric import Metric
  from supervised.algorithms.registry import BINARY_CLASSIFICATION, REGRESSION
label_desc: Use image node_id 3 for calling the ComputeAdditionalMetricsTest obj's underlying member method code with example usage: obj.test_compute_for_regression() without return types