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: Calculates difference between predictions (probabilities) and target
  for multiclass classification task
  
  :param target: class labels
  :param prev_prediction: predictions from previous classification model
  :return diff: difference between probabilities of classes
docstr_tok: ["Calculates","difference","between","predictions","(","probabilities",")","and","target","for","multiclass","classification","task",":","param","target",":","class","labels",":","param","prev_prediction",":","predictions","from","previous","classification","model",":","return","diff",":","difference","between","probabilities","of","classes"]
code: def _multi_difference(
      target: np.array, prev_prediction: np.array
  ) -> np.array:
      """Calculates difference between predictions (probabilities) and target
      for multiclass classification task
  
      :param target: class labels
      :param prev_prediction: predictions from previous classification model
      :return diff: difference between probabilities of classes
      """
  
      # Make one-hot encoding for target
      binary_enc = OneHotEncoder().fit_transform(target)
      probabilities_target = binary_enc.toarray()
      diff = probabilities_target - prev_prediction
  
      return diff
  
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 7 for calling the DecomposerClassImplementation obj's underlying member method code with example usage: obj._multi_difference(target, prev_prediction) and returns: diff