class_docstr: Strategy for applying custom algorithms from FEDOT to preprocess data
  for regression task
class_docstr_tok: ["Strategy","for","applying","custom","algorithms","from","FEDOT","to","preprocess","data","for","regression","task"]
code: def __init__(
      self,
      operation_type: str,
      params: Optional[OperationParameters] = None,
  ):
      self.operation_impl = self._convert_to_operation(operation_type)
      super().__init__(operation_type, params)
  
imports: import warnings
  from typing import Optional
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.evaluation_interfaces import EvaluationStrategy, SkLearnEvaluationStrategy
  from fedot.core.operations.evaluation.operation_implementations.data_operations.decompose import DecomposerRegImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_filters import IsolationForestRegImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_filters import LinearRegRANSACImplementation, NonLinearRegRANSACImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_selectors import LinearRegFSImplementation, NonLinearRegFSImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.knn import FedotKnnRegImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.utilities.random import ImplementationRandomStateHandler
label_desc: Use image node_id 1 to create a new FedotRegressionPreprocessingStrategy object from inherited base classes: EvaluationStrategy with example: obj = FedotRegressionPreprocessingStrategy(operation_type, params)