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 _plot_roc(self, server=False, save_to_file=None, plot=True):
      if plot:
          plt = get_matplotlib_pyplot(server)
          if plt is None:
              return decorate_plot_result(figure=RAISE_ON_FIGURE_ACCESS)
          fig = plt.figure()
          plt.xlabel("False Positive Rate (FPR)")
          plt.ylabel("True Positive Rate (TPR)")
          plt.title("Receiver Operating Characteristic Curve")
          plt.text(
              0.5, 0.5, r"AUC={0:.4f}".format(self._metric_json["AUC"])
          )
          plt.plot(self.fprs, self.tprs, "b--")
          plt.axis([0, 1, 0, 1])
          plt.grid(True)
          plt.tight_layout()
          if not server:
              plt.show()
          if (
              save_to_file is not None
          ):  # only save when a figure is actually plotted
              fig.savefig(fname=save_to_file)
          return decorate_plot_result(
              res=(self.fprs, self.tprs), figure=fig
          )
      else:
          return decorate_plot_result(res=(self.fprs, self.tprs))
  
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 24 for calling the H2OBinomialModelMetrics obj's underlying member method code with example usage: obj._plot_roc(server, save_to_file, plot) and returns: decorate_plot_result, decorate_plot_result, decorate_plot_result