code: def get_hyperparameter_search_space(
      feat_type: Optional[FEAT_TYPE_TYPE] = None,
      dataset_properties=None,
  ):
      cs = ConfigurationSpace()
  
      n_estimators = UniformIntegerHyperparameter(
          name="n_estimators",
          lower=50,
          upper=500,
          default_value=50,
          log=False,
      )
      learning_rate = UniformFloatHyperparameter(
          name="learning_rate",
          lower=0.01,
          upper=2,
          default_value=0.1,
          log=True,
      )
      algorithm = CategoricalHyperparameter(
          name="algorithm",
          choices=["SAMME.R", "SAMME"],
          default_value="SAMME.R",
      )
      max_depth = UniformIntegerHyperparameter(
          name="max_depth",
          lower=1,
          upper=10,
          default_value=1,
          log=False,
      )
  
      cs.add_hyperparameters(
          [n_estimators, learning_rate, algorithm, max_depth]
      )
      return cs
  
file_path: auto-sklearn/autosklearn/pipeline/components/classification/adaboost.py
imports: from typing import Optional
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, UniformFloatHyperparameter, UniformIntegerHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnClassificationAlgorithm
  from autosklearn.pipeline.constants import DENSE, PREDICTIONS, SPARSE, UNSIGNED_DATA
label_desc: Use image node_id 6 for calling the AdaboostClassifier obj's underlying member method code with example usage: obj.get_hyperparameter_search_space(feat_type, dataset_properties) and returns: cs