class_docstr: Class which contains abstract methods for data preprocessing.
class_docstr_tok: ["Class","which","contains","abstract","methods","for","data","preprocessing","."]
docstr: Applies inverse label encoding operation for target column if needed
  
  Args:
      column_to_transform: column to be encoded
  
  Returns:
      encoded or untouched column
docstr_tok: ["Applies","inverse","label","encoding","operation","for","target","column","if","needed","Args",":","column_to_transform",":","column","to","be","encoded","Returns",":","encoded","or","untouched","column"]
code: def apply_inverse_target_encoding(
      self, column_to_transform: np.ndarray
  ) -> np.ndarray:
      """
      Applies inverse label encoding operation for target column if needed
  
      Args:
          column_to_transform: column to be encoded
  
      Returns:
          encoded or untouched column
      """
      raise AbstractMethodNotImplementError
  
imports: from abc import ABC, abstractmethod
  from typing import Dict, Union, TYPE_CHECKING
  import numpy
  from sklearn.preprocessing import LabelEncoder
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.categorical_encoders import LabelEncodingImplementation, OneHotEncodingImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_transformations import ImputationImplementation
  from fedot.preprocessing.categorical import BinaryCategoricalPreprocessor
  from fedot.preprocessing.data_types import TableTypesCorrector
  from fedot.preprocessing.structure import DEFAULT_SOURCE_NAME
  from fedot.utilities.custom_errors import AbstractMethodNotImplementError
label_desc: Use image node_id 8 for calling the BasePreprocessor obj's underlying member method code with example usage: obj.apply_inverse_target_encoding(column_to_transform) without return types