code: def __init__(
      self,
      alpha,
      mode="percentile",
      score_func="f_regression",
      random_state=None,
  ):
      import sklearn.feature_selection
  
      self.random_state = random_state  # We don't use this
      self.alpha = alpha
      self.mode = mode
  
      if score_func == "f_regression":
          self.score_func = sklearn.feature_selection.f_regression
      elif score_func == "mutual_info_regression":
          self.score_func = partial(
              sklearn.feature_selection.mutual_info_regression,
              random_state=self.random_state,
          )
          # Mutual info consistently crashes if percentile is not the mode
          self.mode = "percentile"
      else:
          raise ValueError(
              "score_func must be in ('f_regression, 'mutual_info_regression') "
              "for task=regression "
              "but is: %s " % (score_func)
          )
  
file_path: auto-sklearn/autosklearn/pipeline/components/feature_preprocessing/select_rates_regression.py
imports: from typing import Optional
  from functools import partial
  from ConfigSpace import NotEqualsCondition
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, UniformFloatHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
  from autosklearn.pipeline.constants import DENSE, INPUT, SPARSE, UNSIGNED_DATA
label_desc: Use image node_id 1 to create a new SelectRegressionRates object from inherited base classes: AutoSklearnPreprocessingAlgorithm with example: obj = SelectRegressionRates(alpha, mode, score_func, random_state)