class_docstr: Accessor to ``sklearn.metrics``.
code: def _curve_wraps(self, func, *args, **kwargs):
      decision = self._df.decision
      if util._is_1d_varray(decision):
          c1, c2, threshold = func(
              self._target.values, decision.values, *args, **kwargs
          )
          return c1, c2, threshold
  
      results = {}
      if self._df.has_multi_targets():
          for i, ((name, col), t) in enumerate(
              zip(decision.iteritems(), self._target.values.T)
          ):
              # results can have different length
              c1, c2, threshold = func(
                  t, col.values, pos_label=i, *args, **kwargs
              )
              results[name] = c1, c2, threshold
      else:
          for i, (name, col) in enumerate(decision.iteritems()):
              # results can have different length
              c1, c2, threshold = func(
                  self._target.values,
                  col.values,
                  pos_label=i,
                  *args,
                  **kwargs,
              )
              results[name] = c1, c2, threshold
      return results
  
imports: from pandas_ml.core.accessor import _AccessorMethods, _attach_methods, _wrap_target_pred_func, _wrap_target_pred_noargs
  import pandas_ml.util
label_desc: Use image node_id 10 for calling the MetricsMethods obj's underlying member method code with example usage: obj._curve_wraps(func) and returns: results, c1,  c2,  threshold