code: def fraud_detector(card_activity, categories, sensitivity):
      activity_range = random.randint(0, 100)
      drop_columns = [
          column
          for column in ["retail", "food", "other"]
          if column not in categories
      ]
      if len(drop_columns):
          card_activity.drop(columns=drop_columns, inplace=True)
      return (
          card_activity,
          card_activity,
          {
              "fraud": activity_range / 100.0,
              "not fraud": 1 - activity_range / 100.0,
          },
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: fraud_detector(card_activity, categories, sensitivity) and returns: card_activity,  card_activity,  dict