code: def classification_svc_complex_pipeline():
      """
      Returns pipeline with the following structure:
  
      .. image:: img_classification_pipelines/svc_complex_pipeline.png
        :width: 55%
  
      Where svc - support vector classifier, logit - logistic regression, knn - K nearest neighbors classifier,
      rf - random forest classifier
  
      """
  
      svc_primary_node = PipelineNode("svc")
      svc_primary_node.parameters = dict(probability=True)
      logit_secondary_node = PipelineNode(
          "logit", nodes_from=[svc_primary_node]
      )
  
      svc_node_with_custom_params = PipelineNode("svc")
      svc_node_with_custom_params.parameters = dict(
          kernel="rbf", C=10, gamma=1, cache_size=2000, probability=True
      )
      logit_secondary_node_2 = PipelineNode(
          "logit", nodes_from=[svc_node_with_custom_params]
      )
  
      knn_primary_node = PipelineNode("knn")
      knn_secondary_node = PipelineNode(
          "knn", nodes_from=[knn_primary_node, logit_secondary_node]
      )
  
      rf_node = PipelineNode(
          "rf", nodes_from=[logit_secondary_node_2, knn_secondary_node]
      )
  
      preset_pipeline = Pipeline(rf_node)
  
      return preset_pipeline
  
file_path: FEDOT/examples/simple/classification/classification_pipelines.py
imports: from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
label_desc: Use image node_id 7 for calling a global function with example usage: classification_svc_complex_pipeline() and returns: preset_pipeline