code: def plot_fairness_check_clf(
      fobject,
      title=None,
      other_objects=None,
      epsilon=None,
      verbose=True,
  ):
      data = utils._metric_ratios_2_df(fobject)
      n = 1
      if other_objects is not None:
          basic_checks.check_other_fairness_objects(
              fobject, other_objects
          )
          for other_obj in other_objects:
              other_data = utils._metric_ratios_2_df(other_obj)
              data = pd.concat([data, other_data])
              n += 1
  
      if epsilon is None:
          epsilon = fobject.epsilon
      else:
          checks.check_epsilon(epsilon)
  
      if any(data.score == 0):
          nan_models = set(data.label[data.score == 0])
          helper.verbose_cat(
              f"\nFound NaN's or 0's for models: {nan_models}\n"
              f"It is advisable to check 'metric_ratios'",
              verbose=verbose,
          )
  
      # change name of metrics
      data.loc[
          data.metric == "TPR", "metric"
      ] = "Equal opportunity ratio     TP/(TP + FN)"
      data.loc[
          data.metric == "ACC", "metric"
      ] = "Accuracy equality ratio    (TP + TN)/(TP + FP + TN + FN)"
      data.loc[
          data.metric == "PPV", "metric"
      ] = "Predictive parity ratio     TP/(TP + FP)"
      data.loc[
          data.metric == "FPR", "metric"
      ] = "Predictive equality ratio   FP/(FP + TN)"
      data.loc[
          data.metric == "STP", "metric"
      ] = "Statistical parity ratio   (TP + FP)/(TP + FP + TN + FN)"
  
      # without privileged
      data = data.loc[data.subgroup != fobject.privileged]
  
      fig = plot_fairness_check(data, n, fobject.epsilon, title)
  
      return fig
  
imports: import numpy
  import pandas
  import plotly.express
  import plotly.graph_objects
  from plotly.subplots import make_subplots
  from .None import checks
  from .None import utils
  from .._basics import checks
  from .._basics.exceptions import ParameterCheckError
  from ...None import _theme
  from ..._explainer import helper
label_desc: Use image node_id 2 for calling a global function with example usage: plot_fairness_check_clf(fobject, title, other_objects, epsilon, verbose) and returns: fig