code: def __init__(
      self, alpha, mode="fpr", score_func="chi2", 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 == "chi2":
          self.score_func = sklearn.feature_selection.chi2
      elif score_func == "f_classif":
          self.score_func = sklearn.feature_selection.f_classif
      elif score_func == "mutual_info_classif":
          self.score_func = partial(
              sklearn.feature_selection.mutual_info_classif,
              random_state=self.random_state,
          )
          # mutual info classif constantly crashes without mode percentile
          self.mode = "percentile"
      else:
          raise ValueError(
              "score_func must be in ('chi2, 'f_classif', 'mutual_info_classif') "
              "for classification "
              "but is: %s " % (score_func)
          )
  
file_path: auto-sklearn/autosklearn/pipeline/components/feature_preprocessing/select_rates_classification.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, SIGNED_DATA, SPARSE, UNSIGNED_DATA
label_desc: Use image node_id 1 to create a new SelectClassificationRates object from inherited base classes: AutoSklearnPreprocessingAlgorithm with example: obj = SelectClassificationRates(alpha, mode, score_func, random_state)