code: def test_missing_values(self):
      # Arrange
      t, p = _generate_classes_and_scores(
          3, n=100, hard_predictions=True
      )
      pm = [None if x == 2 else x for x in p]
      tm = [None if x == 2 else x for x in t]
  
      targets = turicreate.SArray(tm)
      predictions = turicreate.SArray(pm)
  
      # Act & Assert [accuracy]
      skl_score = accuracy_score(t, p)
      score = turicreate.toolkits.evaluation.accuracy(
          targets, predictions
      )
      self.assertAlmostEqual(skl_score, score)
  
      # Act & Assert [precision]
      skl_score = precision_score(t, p, average="macro")
      score = turicreate.toolkits.evaluation.precision(
          targets, predictions
      )
      self.assertAlmostEqual(skl_score, score)
  
      # Act & Assert [recall]
      skl_score = recall_score(t, p, average="macro")
      score = turicreate.toolkits.evaluation.recall(
          targets, predictions
      )
      self.assertAlmostEqual(skl_score, score)
  
      # Act & Assert [f1_score]
      skl_score = f1_score(t, p, average="macro")
      score = turicreate.toolkits.evaluation.f1_score(
          targets, predictions
      )
      self.assertAlmostEqual(skl_score, score)
  
      # Act & Assert [fbeta_score]
      skl_score = fbeta_score(t, p, beta=2.0, average="macro")
      score = turicreate.toolkits.evaluation.fbeta_score(
          targets, predictions, beta=2.0
      )
      self.assertAlmostEqual(skl_score, score)
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import turicreate
  from turicreate.toolkits._main import ToolkitError
  import math
  from numpy import inf
  import numpy
label_desc: Use image node_id 23 for calling the MetricsTest obj's underlying member method code with example usage: obj.test_missing_values() without return types