code: def get_refinement_pipeline_with_polyfit():
      """Create 4-level pipeline with decompose operation"""
  
      node_polyfit = PipelineNode("polyfit")
      node_polyfit.parameters = {"degree": 2}
      node_lagged = PipelineNode("lagged")
      node_decompose = PipelineNode(
          "decompose", nodes_from=[node_lagged, node_polyfit]
      )
      node_dtreg = PipelineNode("dtreg", nodes_from=[node_decompose])
      node_dtreg.parameters = {"max_depth": 3}
  
      # Pipelines with different outputs
      pipeline_with_decompose_finish = Pipeline(node_dtreg)
      pipeline_with_main_finish = Pipeline(node_polyfit)
  
      # Combining branches with different targets (T and T_decomposed)
      final_node = PipelineNode(
          "ridge", nodes_from=[node_polyfit, node_dtreg]
      )
  
      pipeline = Pipeline(final_node)
      return (
          pipeline_with_main_finish,
          pipeline_with_decompose_finish,
          pipeline,
      )
  
file_path: FEDOT/examples/advanced/decompose/refinement_forecast_example.py
imports: import warnings
  import numpy
  import pandas
  from matplotlib import pyplot
  from sklearn.metrics import mean_squared_error, mean_absolute_error
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.ts_wrappers import in_sample_ts_forecast
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import TaskTypesEnum, Task, TsForecastingParams
  from fedot.core.utils import set_random_seed
label_desc: Use image node_id 1 for calling a global function with example usage: get_refinement_pipeline_with_polyfit() and returns: pipeline_with_main_finish,  pipeline_with_decompose_finish,  pipeline