code: def get_knn_reg_pipeline(k_neighbors):
      """Function return pipeline with K-nn regression model in it"""
      node_scaling = PipelineNode("scaling")
      node_final = PipelineNode("knnreg", nodes_from=[node_scaling])
      node_final.parameters = {"n_neighbors": k_neighbors}
      pipeline = Pipeline(node_final)
      return pipeline
  
file_path: FEDOT/test/integration/models/test_models_params.py
imports: import numpy
  from fedot.core.data.data import InputData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.utilities.synth_dataset_generator import classification_dataset, regression_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: get_knn_reg_pipeline(k_neighbors) and returns: pipeline