code: def _sampling_strategy_auto(y, sampling_type):
      """Returns sampling target auto for over-sampling and not-minority for
      under-sampling."""
      if sampling_type == "over-sampling":
          return _sampling_strategy_not_majority(y, sampling_type)
      elif (
          sampling_type == "under-sampling"
          or sampling_type == "clean-sampling"
      ):
          return _sampling_strategy_not_minority(y, sampling_type)
  
imports: import warnings
  from collections import OrderedDict
  from functools import wraps
  from inspect import Parameter, signature
  from numbers import Real
  from typing import Any, Dict
  import numpy
  from sklearn.utils import column_or_1d
  from sklearn.utils.multiclass import type_of_target
label_desc: Use image node_id 7 for calling a global function with example usage: _sampling_strategy_auto(y, sampling_type) and returns: _sampling_strategy_not_majority, _sampling_strategy_not_minority