code: def get_hyperparameter_search_space(
      feat_type: Optional[FEAT_TYPE_TYPE] = None,
      dataset_properties: Optional[DATASET_PROPERTIES_TYPE] = None,
  ) -> ConfigurationSpace:
      # TODO add replace by zero!
      strategy = CategoricalHyperparameter(
          "strategy", ["none", "weighting"], default_value="none"
      )
      cs = ConfigurationSpace()
      cs.add_hyperparameter(strategy)
      return cs
  
file_path: auto-sklearn/autosklearn/pipeline/components/data_preprocessing/balancing/balancing.py
imports: from typing import Any, Dict, List, Optional, Tuple, Union
  import numpy
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter
  from sklearn.base import BaseEstimator
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.base import DATASET_PROPERTIES_TYPE, PIPELINE_DATA_DTYPE
  from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
  from autosklearn.pipeline.constants import DENSE, INPUT, SIGNED_DATA, SPARSE, UNSIGNED_DATA
label_desc: Use image node_id 6 for calling the Balancing obj's underlying member method code with example usage: obj.get_hyperparameter_search_space(feat_type, dataset_properties) and returns: cs