code: def test_evaluate_regressions():
      dataset = (
          foz.load_zoo_dataset("quickstart").select_fields().clone()
      )
  
      for idx, sample in enumerate(dataset, 1):
          ytrue = random.random() * idx
          ypred = ytrue + np.random.randn() * np.sqrt(ytrue)
          confidence = random.random()
          sample["ground_truth"] = fo.Regression(value=ytrue)
          sample["predictions"] = fo.Regression(
              value=ypred, confidence=confidence
          )
          sample["weather"] = random.choice(
              ["sunny", "cloudy", "rainy"]
          )
          sample.save()
  
      #
      # Simple regression
      #
  
      results = dataset.evaluate_regressions(
          "predictions", gt_field="ground_truth", eval_key="eval"
      )
  
      results.print_metrics()
  
      print(dataset.bounds("eval"))
  
      plot = results.plot_results(
          labels="weather", sizes="predictions.confidence"
      )
      plot.show()
  
      input("Press enter to continue...")
  
      #
      # Cleanup
      #
  
      dataset.delete_evaluations()
  
file_path: fiftyone/tests/intensive/evaluation_tests.py
imports: import random
  import unittest
  import numpy
  import eta.core.utils
  import pytest
  import fiftyone
  import fiftyone.zoo
  from fiftyone import ViewField
label_desc: Use image node_id 1 for calling a global function with example usage: test_evaluate_regressions() without return types