class_docstr: Unit test class for testing scikit-learn converter.
class_docstr_tok: ["Unit","test","class","for","testing","scikit-learn","converter","."]
docstr: Failure testing for bad conversion.
docstr_tok: ["Failure","testing","for","bad","conversion","."]
code: def test_conversion_bad_inputs(self):
      """
      Failure testing for bad conversion.
      """
      # Error on converting an untrained model
      with self.assertRaises(TypeError):
          model = OneHotEncoder()
          spec = converter.convert(model, "data", "out", "regressor")
  
imports: import unittest
  import tempfile
  from coremltools.proto import FeatureTypes_pb2
  from coremltools._deps import _HAS_SKLEARN, _HAS_LIBSVM
  from coremltools.models.pipeline import PipelineRegressor, PipelineClassifier
  from coremltools.models.utils import evaluate_transformer
  import coremltools.models.datatypes
  from coremltools.models.feature_vectorizer import create_feature_vectorizer
label_desc: Use image node_id 3 for calling the LinearRegressionPipeline obj's underlying member method code with example usage: obj.test_conversion_bad_inputs() without return types