code: def convert(model, feature_names, target):
      """Convert a Nu Support Vector Regression (NuSVR) model to the protobuf spec.
      Parameters
      ----------
      model: NuSVR
          A trained NuSVR encoder model.
  
      feature_names: [str]
          Name of the input columns.
  
      target: str
          Name of the output column.
  
      Returns
      -------
      model_spec: An object of type Model_pb.
          Protobuf representation of the model
      """
      if not (_HAS_SKLEARN):
          raise RuntimeError(
              "scikit-learn not found. scikit-learn conversion API is disabled."
          )
  
      _sklearn_util.check_expected_type(model, _NuSVR)
      return _SVR.convert(model, feature_names, target)
  
imports: from .None import _SVR
  from ..._deps import _HAS_SKLEARN
  from ...models import MLModel
label_desc: Use image node_id 1 for calling a global function with example usage: convert(model, feature_names, target) and returns: _SVR