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"]
docstr: This method is used for operation training with the data provided
  :param InputData train_data: data used for operation training
  :return: trained data operation
docstr_tok: ["This","method","is","used","for","operation","training","with","the","data","provided",":","param","InputData","train_data",":","data","used","for","operation","training",":","return",":","trained","data","operation"]
code: def fit(self, train_data: InputData):
      """
      This method is used for operation training with the data provided
      :param InputData train_data: data used for operation training
      :return: trained data operation
      """
  
      warnings.filterwarnings("ignore", category=RuntimeWarning)
      operation_implementation = self.operation_impl(
          self.params_for_fit
      )
      with ImplementationRandomStateHandler(
          implementation=operation_implementation
      ):
          operation_implementation.fit(train_data)
      return operation_implementation
  
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 2 for calling the FedotRegressionPreprocessingStrategy obj's underlying member method code with example usage: obj.fit(train_data) and returns: operation_implementation