code: def inverse_transform_proba(self, y, as_pandas=False, as_pred=False):
      y_index = None
      if isinstance(y, DataFrame):
          y_index = y.index
          y = y.to_numpy()
      if self.invalid_class_count > 0:
          y_transformed = np.zeros(
              [len(y), len(self.ordered_class_labels)], dtype=np.float32
          )
          y_transformed[:, self.label_index_to_keep] = y
      else:
          y_transformed = y
      if as_pred:
          y_transformed = get_pred_from_proba(
              y_pred_proba=y_transformed, problem_type=MULTICLASS
          )
          y_transformed = self._convert_to_valid_series(y_transformed)
          y_transformed = y_transformed.map(
              self.cat_mappings_dependent_var_uncleaned
          )
          if y_index is not None:
              y_transformed.index = y_index
      if as_pandas and not as_pred:
          y_transformed = DataFrame(
              data=y_transformed,
              index=y_index,
              columns=self.ordered_class_labels,
              dtype=np.float32,
          )
      return y_transformed
  
imports: import copy
  import logging
  from typing import Union
  import numpy
  from pandas import DataFrame, Series
  from autogluon.core.constants import BINARY, MULTICLASS, QUANTILE, REGRESSION, SOFTCLASS
  from autogluon.core.utils import get_pred_from_proba, get_pred_from_proba_df
label_desc: Use image node_id 5 for calling the LabelCleanerMulticlass obj's underlying member method code with example usage: obj.inverse_transform_proba(y, as_pandas, as_pred) and returns: y_transformed