class_docstr: Base class for heterogeneous ensemble of learners.
  
  Parameters
  ----------
  estimators : list of (str, estimator) tuples
      The ensemble of estimators to use in the ensemble. Each element of the
      list is defined as a tuple of string (i.e. name of the estimator) and
      an estimator instance. An estimator can be set to `'drop'` using
      `set_params`.
  
  Attributes
  ----------
  estimators_ : list of estimators
      The elements of the estimators parameter, having been fitted on the
      training data. If an estimator has been set to `'drop'`, it will not
      appear in `estimators_`.
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docstr: Get the parameters of an estimator from the ensemble.
  
  Returns the parameters given in the constructor as well as the
  estimators contained within the `estimators` parameter.
  
  Parameters
  ----------
  deep : bool, default=True
      Setting it to True gets the various estimators and the parameters
      of the estimators as well.
  
  Returns
  -------
  params : dict
      Parameter and estimator names mapped to their values or parameter
      names mapped to their values.
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code: def get_params(self, deep=True):
      """
      Get the parameters of an estimator from the ensemble.
  
      Returns the parameters given in the constructor as well as the
      estimators contained within the `estimators` parameter.
  
      Parameters
      ----------
      deep : bool, default=True
          Setting it to True gets the various estimators and the parameters
          of the estimators as well.
  
      Returns
      -------
      params : dict
          Parameter and estimator names mapped to their values or parameter
          names mapped to their values.
      """
      return super()._get_params("estimators", deep=deep)
  
imports: from abc import ABCMeta, abstractmethod
  from typing import List
  import numpy
  from joblib import effective_n_jobs
  from ..base import BaseEstimator, MetaEstimatorMixin, clone, is_classifier, is_regressor
  from ..utils import Bunch, _print_elapsed_time, check_random_state
  from ..utils._tags import _safe_tags
  from ..utils.metaestimators import _BaseComposition
label_desc: Use image node_id 5 for calling the _BaseHeterogeneousEnsemble obj's underlying member method code with example usage: obj.get_params(deep) and returns: super