class_docstr: Base class to define the evaluation strategy of Operation object:
  the certain sklearn or any other operation with fit/predict methods.
  
  Args:
      operation_type: ``str`` of the operation defined in operation repository
      params: hyperparameters to fit the operation with
docstr: Method to predict the target data for fit stage.
  Allows to implement predict method different from main predict method
  if another behaviour for fit graph stage is needed.
  
  Args:
      trained_operation: trained operation object
      predict_data: data to predict
  Returns:
      passed data with new predicted target
docstr_tok: ["Method","to","predict","the","target","data","for","fit","stage",".","Allows","to","implement","predict","method","different","from","main","predict","method","if","another","behaviour","for","fit","graph","stage","is","needed",".","Args",":","trained_operation",":","trained","operation","object","predict_data",":","data","to","predict","Returns",":","passed","data","with","new","predicted","target"]
code: def predict_for_fit(
      self, trained_operation, predict_data: InputData
  ) -> OutputData:
      """Method to predict the target data for fit stage.
      Allows to implement predict method different from main predict method
      if another behaviour for fit graph stage is needed.
  
      Args:
          trained_operation: trained operation object
          predict_data: data to predict
      Returns:
          passed data with new predicted target
      """
      return self.predict(trained_operation, predict_data)
  
imports: import warnings
  from abc import abstractmethod
  from typing import Optional
  import numpy
  from golem.core.log import default_log
  from lightgbm.sklearn import LGBMClassifier, LGBMRegressor
  from sklearn.cluster import KMeans
  from sklearn.ensemble import AdaBoostRegressor, ExtraTreesRegressor, GradientBoostingRegressor, RandomForestClassifier, RandomForestRegressor
  from sklearn.linear_model import Lasso, LinearRegression, LogisticRegression, Ridge, SGDRegressor
  from sklearn.multioutput import MultiOutputClassifier, MultiOutputRegressor
  from sklearn.naive_bayes import BernoulliNB, MultinomialNB
  from sklearn.neural_network import MLPClassifier
  from sklearn.svm import LinearSVR
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from xgboost import XGBClassifier, XGBRegressor
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.operation_types_repository import OperationTypesRepository, get_operation_type_from_id
  from fedot.core.repository.tasks import TaskTypesEnum
  from fedot.utilities.custom_errors import AbstractMethodNotImplementError
  from fedot.utilities.random import ImplementationRandomStateHandler
label_desc: Use image node_id 5 for calling the EvaluationStrategy obj's underlying member method code with example usage: obj.predict_for_fit(trained_operation, predict_data) and returns: self