content: """
  The :mod:`sklearn.ensemble` module includes ensemble-based methods for
  classification, regression and anomaly detection.
  """
  import typing
  
  from ._base import BaseEnsemble
  from ._forest import RandomForestClassifier
  from ._forest import RandomForestRegressor
  from ._forest import RandomTreesEmbedding
  from ._forest import ExtraTreesClassifier
  from ._forest import ExtraTreesRegressor
  from ._bagging import BaggingClassifier
  from ._bagging import BaggingRegressor
  from ._iforest import IsolationForest
  from ._weight_boosting import AdaBoostClassifier
  from ._weight_boosting import AdaBoostRegressor
  from ._gb import GradientBoostingClassifier
  from ._gb import GradientBoostingRegressor
  from ._voting import VotingClassifier
  from ._voting import VotingRegressor
  from ._stacking import StackingClassifier
  from ._stacking import StackingRegressor
  
  if typing.TYPE_CHECKING:
      # Avoid errors in type checkers (e.g. mypy) for experimental estimators.
      # TODO: remove this check once the estimator is no longer experimental.
      from ._hist_gradient_boosting.gradient_boosting import (  # noqa
          HistGradientBoostingRegressor, HistGradientBoostingClassifier
      )
  
  __all__ = ["BaseEnsemble",
             "RandomForestClassifier", "RandomForestRegressor",
             "RandomTreesEmbedding", "ExtraTreesClassifier",
             "ExtraTreesRegressor", "BaggingClassifier",
             "BaggingRegressor", "IsolationForest", "GradientBoostingClassifier",
             "GradientBoostingRegressor", "AdaBoostClassifier",
             "AdaBoostRegressor", "VotingClassifier", "VotingRegressor",
             "StackingClassifier", "StackingRegressor",
             ]
  