code: def test_confusion_and_other_metrics():
      """
  
      >>> dataset = datasets.Phishing()
  
      >>> model = preprocessing.StandardScaler() | linear_model.LogisticRegression(
      ...     optimizer=optim.SGD(0.1)
      ... )
  
      >>> metric = metrics.ConfusionMatrix() + metrics.F1() + metrics.Accuracy()
  
      >>> evaluate.progressive_val_score(dataset, model, metric)
              False   True
      False     613     89
       True      49    499
      F1: 87.85%
      Accuracy: 88.96%
  
      """
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_confusion_and_other_metrics() without return types