class_docstr: Strategy for applying classification algorithms from Sklearn library 
class_docstr_tok: ["Strategy","for","applying","classification","algorithms","from","Sklearn","library"]
docstr: Predict method for classification task for predict stage
  
  :param trained_operation: model object
  :param predict_data: data used for prediction
  :return: prediction target
docstr_tok: ["Predict","method","for","classification","task","for","predict","stage",":","param","trained_operation",":","model","object",":","param","predict_data",":","data","used","for","prediction",":","return",":","prediction","target"]
code: def predict(
      self, trained_operation, predict_data: InputData
  ) -> OutputData:
      """
      Predict method for classification task for predict stage
  
      :param trained_operation: model object
      :param predict_data: data used for prediction
      :return: prediction target
      """
  
      prediction = self._sklearn_compatible_prediction(
          trained_operation=trained_operation,
          features=predict_data.features,
      )
      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 DecomposerClassImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_filters import IsolationForestClassImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_imbalanced_class import ResampleImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_selectors import LinearClassFSImplementation, NonLinearClassFSImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.discriminant_analysis import LDAImplementation, QDAImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.keras import FedotCNNImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.knn import FedotKnnClassImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.svc import FedotSVCImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.utilities.random import ImplementationRandomStateHandler
label_desc: Use image node_id 1 for calling the SkLearnClassificationStrategy obj's underlying member method code with example usage: obj.predict(trained_operation, predict_data) and returns: converted