code: def get_composite_pipeline():
      """
      The function returns prepared pipeline of 5 models
  
      :return: Pipeline object
      """
  
      node_1 = PipelineNode("lagged")
      node_1.parameters = {"window_size": 150}
      node_2 = PipelineNode("lagged")
      node_2.parameters = {"window_size": 100}
      node_linear_1 = PipelineNode("linear", nodes_from=[node_1])
      node_linear_2 = PipelineNode("linear", nodes_from=[node_2])
  
      node_final = PipelineNode(
          "ridge", nodes_from=[node_linear_1, node_linear_2]
      )
      pipeline = Pipeline(node_final)
      return pipeline
  
file_path: FEDOT/cases/time_series_gapfilling_case.py
imports: import os
  import matplotlib.pyplot
  import numpy
  import pandas
  from sklearn.metrics import mean_absolute_error, mean_squared_error, median_absolute_error
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.utils import fedot_project_root
  from fedot.utilities.ts_gapfilling import ModelGapFiller
label_desc: Use image node_id 3 for calling a global function with example usage: get_composite_pipeline() and returns: pipeline