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 Integral, Real
  import numpy
  from sklearn.base import clone
  from sklearn.neighbors import NearestNeighbors
  from sklearn.utils import check_array, column_or_1d
  from sklearn.utils.multiclass import type_of_target
  from sklearn.utils.validation import _num_samples
  from .fixes import _is_pandas_df
label_desc: Use image node_id 10 for calling a global function with example usage: _sampling_strategy_auto(y, sampling_type) and returns: _sampling_strategy_not_majority, _sampling_strategy_not_minority