code: def __init__(self, model) -> None:
      raise_if_not(
          isinstance(model, BaseEnsemble),
          f"Scorer is expecting a model of type BaseEnsemble (from sklearn ensemble), \
              found type {type(model)}.",
      )
  
      self.model = model
      super().__init__()
  
file_path: darts/darts/ad/aggregators/ensemble_sklearn_aggregator.py
imports: from typing import Sequence
  import numpy
  from sklearn.ensemble import BaseEnsemble
  from darts import TimeSeries
  from darts.ad.aggregators.aggregators import FittableAggregator
  from darts.logging import raise_if_not
label_desc: Use image node_id 1 to create a new EnsembleSklearnAggregator object from inherited base classes: FittableAggregator with example: obj = EnsembleSklearnAggregator(model)