class_docstr: Strategy for applying custom regression models from FEDOT make predictions
class_docstr_tok: ["Strategy","for","applying","custom","regression","models","from","FEDOT","make","predictions"]
code: def predict(
      self, trained_operation, predict_data: InputData
  ) -> OutputData:
      prediction = trained_operation.predict(predict_data)
      converted = self._convert_to_output(prediction, predict_data)
      return converted
  
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 3 for calling the FedotRegressionStrategy obj's underlying member method code with example usage: obj.predict(trained_operation, predict_data) and returns: converted