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
code: def implementation_info(self) -> str:
      return str(self._convert_to_operation(self.operation_type))
  
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 7 for calling the EvaluationStrategy obj's underlying member method code with example usage: obj.implementation_info() and returns: str