class_docstr: Unit test class for testing scikit-learn converter.
code: def test_conversion_bad_inputs(self):
      # Error on converting an untrained model
      with self.assertRaises(Exception):
          # n_estimators default changed >= 0.22. Specify explicitly to match <0.22 behavior.
          model = RandomForestClassifier(n_estimators=10)
          spec = skl_converter.convert(model, "data", "out")
  
      # Check the expected class during conversion.
      with self.assertRaises(Exception):
          from sklearn.preprocessing import OneHotEncoder
  
          model = OneHotEncoder()
          spec = skl_converter.convert(model, "data", "out")
  
file_path: coremltools/coremltools/test/sklearn_tests/test_random_forest_classifier.py
imports: import unittest
  from coremltools._deps import _HAS_SKLEARN
label_desc: Use image node_id 3 for calling the RandomForestMultiClassClassifierScikitTest obj's underlying member method code with example usage: obj.test_conversion_bad_inputs() without return types