code: def get_cutoff_figure(tpr, fpr, thresholds, class_name):
      highest_youden_index = sensitivity_specificity_cutoff(tpr, fpr)
      hovertemplate = (
          f"Class: {class_name}"
          + "<br>TPR: %{y:.2%}<br>FPR: %{x:.2%}"
          + f"<br>Optimal Threshold: {thresholds[highest_youden_index]:.3}"
      )
      return go.Scatter(
          x=[fpr[highest_youden_index]],
          y=[tpr[highest_youden_index]],
          mode="markers",
          marker_size=15,
          hovertemplate=hovertemplate,
          showlegend=False,
          marker={"color": "black"},
      )
  
file_path: deepchecks/deepchecks/tabular/checks/model_evaluation/roc_report.py
imports: from typing import Dict, List
  import numpy
  import plotly.graph_objects
  import sklearn
  from deepchecks.core import CheckResult, ConditionResult
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.core.errors import DeepchecksNotSupportedError
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.tabular.utils.task_type import TaskType
  from deepchecks.utils.dict_funcs import get_dict_entry_by_value
  from deepchecks.utils.strings import format_number
label_desc: Use image node_id 1 for calling a global function with example usage: get_cutoff_figure(tpr, fpr, thresholds, class_name) and returns: go