class_docstr: This class is essentially an API for the AUC object.
  This class contains methods for inspecting the AUC for different criteria.
  To input the different criteria, use the static variable ``criteria``.
code: def _str_items_custom(self):
      items = []
      cm = self.confusion_matrix()
      if cm:
          items.append(cm)
      mcms = self._metric_json[
          "max_criteria_and_metric_scores"
      ]  # create a method to access this if it is that useful!
      if mcms:
          items.append(mcms)
      gl = self.gains_lift()
      if gl:
          items.append(gl)
      return items
  
imports: import h2o
  from h2o.model import MetricsBase, ConfusionMatrix
  from h2o.plot import get_matplotlib_pyplot, decorate_plot_result, RAISE_ON_FIGURE_ACCESS
  from h2o.utils.metaclass import deprecated_params
  from h2o.utils.shared_utils import List
  from h2o.utils.typechecks import assert_is_type, numeric, is_type, assert_satisfies
label_desc: Use image node_id 1 for calling the H2OBinomialModelMetrics obj's underlying member method code with example usage: obj._str_items_custom() and returns: items