class_docstr: Unit test class for testing scikit-learn converter.
class_docstr_tok: ["Unit","test","class","for","testing","scikit-learn","converter","."]
docstr: Check that the evaluation results are the same in scikit learn and coremltools
docstr_tok: ["Check","that","the","evaluation","results","are","the","same","in","scikit","learn","and","coremltools"]
code: def test_linear_regression_evaluation(self):
      """
      Check that the evaluation results are the same in scikit learn and coremltools
      """
      input_names = self.scikit_data.feature_names
      df = pd.DataFrame(self.scikit_data.data, columns=input_names)
  
      for normalize_value in (True, False):
          cur_model = LinearRegression(normalize=normalize_value)
          cur_model.fit(
              self.scikit_data["data"], self.scikit_data["target"]
          )
          spec = convert(cur_model, input_names, "target")
  
          df["prediction"] = cur_model.predict(self.scikit_data.data)
  
          metrics = evaluate_regressor(spec, df)
          self.assertAlmostEquals(metrics["max_error"], 0)
  
file_path: turicreate/src/external/coremltools_wrap/coremltools/coremltools/test/sklearn_tests/test_linear_regression.py
imports: import os
  import pandas
  import unittest
  from coremltools._deps import _HAS_SKLEARN
  from coremltools.models.utils import evaluate_regressor, _macos_version, _is_macos
label_desc: Use image node_id 4 for calling the LinearRegressionScikitTest obj's underlying member method code with example usage: obj.test_linear_regression_evaluation() without return types