class_docstr: Base class for the tree ensemble builder class.  This should be instantiated
  either through the :py:class:`TreeEnsembleRegressor` or
  :py:class:`TreeEnsembleClassifier` classes.
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docstr: Set the default prediction value(s).
  
  The values given here form the base prediction value that the values
  at activated leaves are added to.  If values is a scalar, then
  the output of the tree must also be 1 dimensional; otherwise, values
  must be a list with length matching the dimension of values in the tree.
  
  Parameters
  ----------
  values: [int | double | list[double]]
      Default values for predictions.
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code: def set_default_prediction_value(self, values):
      """
      Set the default prediction value(s).
  
      The values given here form the base prediction value that the values
      at activated leaves are added to.  If values is a scalar, then
      the output of the tree must also be 1 dimensional; otherwise, values
      must be a list with length matching the dimension of values in the tree.
  
      Parameters
      ----------
      values: [int | double | list[double]]
          Default values for predictions.
  
      """
      if type(values) is not list:
          values = [float(values)]
      self.tree_parameters.numPredictionDimensions = len(values)
      for value in values:
          self.tree_parameters.basePredictionValue.append(value)
  
file_path: coremltools/coremltools/models/tree_ensemble.py
imports: import collections
  from ..None import SPECIFICATION_VERSION
  from ..proto import Model_pb2
  from ..proto import TreeEnsemble_pb2
  from ._interface_management import set_classifier_interface_params, set_regressor_interface_params
label_desc: Use image node_id 2 for calling the TreeEnsembleBase obj's underlying member method code with example usage: obj.set_default_prediction_value(values) without return types