code: def inverse_transform(self, X):
      for column, lbl_params in self._convert_params.items():
          if (
              "unique_values" in lbl_params
              and "new_columns" in lbl_params
          ):
              # convert to one hot
              lbl = LabelBinarizer()
              lbl.from_json(lbl_params)
              X = lbl.inverse_transform(
                  X, column
              )  # should raise exception
          else:
              # convert to integer
              lbl = LabelEncoder()
              lbl.from_json(lbl_params)
              X.loc[:, column] = lbl.inverse_transform(X.loc[:, column])
  
      return X
  
file_path: mljar-supervised/supervised/preprocessing/preprocessing_categorical.py
imports: import json
  import os
  import numpy
  import pandas
  from supervised.preprocessing.label_binarizer import LabelBinarizer
  from supervised.preprocessing.label_encoder import LabelEncoder
  from supervised.preprocessing.loo_encoder import LooEncoder
  from supervised.preprocessing.preprocessing_utils import PreprocessingUtils
label_desc: Use image node_id 5 for calling the PreprocessingCategorical obj's underlying member method code with example usage: obj.inverse_transform(X) and returns: X