code: def regression(fairness_metrics, fout, model_path):
      for k, v in fairness_metrics.items():
          if k == "fairness_optimization":
              continue
          fout.write(f"\n\n## Fairness metrics for {k} feature\n\n")
  
          fout.write(v["metrics"].to_markdown())
          fout.write("\n\n")
  
          fout.write(f'Privileged value: {v["privileged_value"]}\n\n')
          fout.write(
              f'Underprivileged value: {v["underprivileged_value"]}\n\n\n'
          )
          fout.write(
              f'Fairness metric: {v["fairness_metric_name"]}\n\n'
          )
          fout.write(f'{v["metric_name"]} Difference: {v["diff"]}\n\n')
          fout.write(f'{v["metric_name"]} Ratio: {v["ratio"]}\n\n')
  
          # add sentence about model fairness
          if v["is_fair"]:
              fout.write(f"Model is fair for {k} feature.\n")
              if "ratio" in v["fairness_metric_name"].lower():
                  fout.write(
                      f"The {v['fairness_metric_name']} value is above threshold {v['fairness_threshold']}.\n\n"
                  )
              else:
                  fout.write(
                      f"The {v['fairness_metric_name']} value is below threshold {v['fairness_threshold']}.\n\n"
                  )
          else:
              # model is not fair
              fout.write(f"Model is unfair for {k} feature.\n")
              if "ratio" in v["fairness_metric_name"].lower():
                  fout.write(
                      f"The {v['fairness_metric_name']} value is below threshold {v['fairness_threshold']}.\n\n"
                  )
              else:
                  fout.write(
                      f"The {v['fairness_metric_name']} value is above threshold {v['fairness_threshold']}.\n\n"
                  )
  
          for figure in v["figures"]:
              fout.write(f"\n\n### {figure['title']}\n\n")
              figure["figure"].savefig(
                  os.path.join(model_path, figure["fname"])
              )
              fout.write(f"\n![]({figure['fname']})\n\n")
  
imports: import os
label_desc: Use image node_id 2 for calling the FairnessReport obj's underlying member method code with example usage: obj.regression(fairness_metrics, fout, model_path) without return types