class_docstr: Class for decomposing target for both binary and multiclass
  classification task
class_docstr_tok: ["Class","for","decomposing","target","for","both","binary","and","multiclass","classification","task"]
docstr: Method for modifying input_data for predict stage
  :param input_data: data with features, target and ids
  :return input_data: data with transformed features attribute
docstr_tok: ["Method","for","modifying","input_data","for","predict","stage",":","param","input_data",":","data","with","features",",","target","and","ids",":","return","input_data",":","data","with","transformed","features","attribute"]
code: def transform(self, input_data: InputData) -> OutputData:
      """
      Method for modifying input_data for predict stage
      :param input_data: data with features, target and ids
      :return input_data: data with transformed features attribute
      """
      prev_prediction, prev_features = self.divide_inputs(input_data)
      output_data = self._get_output_data(input_data, prev_features)
      return output_data
  
imports: from typing import Optional
  import numpy
  from sklearn.preprocessing import OneHotEncoder
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import DataOperationImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.repository.tasks import Task, TaskTypesEnum
label_desc: Use image node_id 2 for calling the DecomposerClassImplementation obj's underlying member method code with example usage: obj.transform(input_data) and returns: output_data