parameters: (model, features, target)
return_statement: return _MLModel(spec)
docstring: Convert a Support Vector Regressor (SVR) model to the protobuf spec.
      Parameters
      ----------
      model: SVR
          A trained SVR 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
docstring_summary: Convert a Support Vector Regressor (SVR) model to the protobuf spec.
      Parameters
      ----------
      model: SVR
          A trained SVR encoder model.
docstring_tokens: Convert a Support Vector Regressor ( SVR ) model to the protobuf spec . Parameters ---------- model : SVR A trained SVR encoder model .
function: def convert(model, features, target):
      """Convert a Support Vector Regressor (SVR) model to the protobuf spec.
      Parameters
      ----------
      model: SVR
          A trained SVR 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
      """
      spec = _generate_base_svm_regression_spec(model)
      spec = set_regressor_interface_params(spec, features, target)
      return _MLModel(spec)
function_tokens: def convert ( model , features , target ) : spec = _generate_base_svm_regression_spec ( model ) spec = set_regressor_interface_params ( spec , features , target ) return _MLModel ( spec )