class_docstr: Test class for regression tests.
docstr: Test additional metrics in the results file for a regressor.
docstr_tok: ["Test","additional","metrics","in","the","results","file","for","a","regressor","."]
code: def test_additional_metrics(self):
      """Test additional metrics in the results file for a regressor."""
      train_fs, test_fs, _ = make_regression_data(
          num_examples=2000, num_features=3
      )
  
      # train a regression model using the train feature set
      learner = Learner("LinearRegression")
      learner.train(
          train_fs, grid_search=True, grid_objective="pearson"
      )
  
      # evaluate the trained model using the test feature set
      results = learner.evaluate(
          test_fs, output_metrics=["spearman", "kendall_tau"]
      )
  
      # check that the values for the additional metrics are as expected
      additional_scores_dict = results[-1]
      self.assertAlmostEqual(
          additional_scores_dict["spearman"], 0.9996, places=4
      )
      self.assertAlmostEqual(
          additional_scores_dict["kendall_tau"], 0.9847, places=4
      )
  
imports: import math
  import re
  import unittest
  import warnings
  from itertools import chain, product
  import numpy
  from numpy.testing import assert_allclose, assert_array_equal
  from scipy.stats import pearsonr
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.linear_model import LinearRegression, LogisticRegression
  from skll.config import _setup_config_parser
  from skll.data import FeatureSet, NDJReader, NDJWriter
  from skll.experiments import run_configuration
  from skll.learner import Learner
  from skll.learner.utils import rescaled
  from skll.utils.constants import CLASSIFICATION_ONLY_METRICS
  from skll.utils.testing import config_dir, fill_in_config_paths_for_fancy_output, make_regression_data, other_dir, output_dir, test_dir, train_dir, unlink
label_desc: Use image node_id 15 for calling the TestRegression obj's underlying member method code with example usage: obj.test_additional_metrics() without return types