class_docstr: Meta-transformer for adding predictions and/or class probabilities as synthetic feature(s).
  
  Parameters
  ----------
  estimator : object
      The base estimator from which the transformer is built.
docstr: Create a StackingEstimator object.
  
  Parameters
  ----------
  estimator: object with fit, predict, and predict_proba methods.
      The estimator to generate synthetic features from.
code: def __init__(self, estimator):
      """Create a StackingEstimator object.
  
      Parameters
      ----------
      estimator: object with fit, predict, and predict_proba methods.
          The estimator to generate synthetic features from.
      """
      self.estimator = estimator
  
file_path: tpot/tpot/builtins/stacking_estimator.py
imports: import numpy
  from sklearn.base import BaseEstimator, TransformerMixin, is_classifier
  from sklearn.utils import check_array
label_desc: Use image node_id 1 to create a new StackingEstimator object from inherited base classes: BaseEstimator, TransformerMixin with example: obj = StackingEstimator(estimator)