class_docstr: Accessor to ``sklearn.metrics``.
docstr: Calcurate AUC of ROC curve or precision recall curve
  
  Parameters
  ----------
  kind : {'roc', 'precision_recall_curve'}
  
  Returns
  -------
  float : AUC
docstr_tok: ["Calcurate","AUC","of","ROC","curve","or","precision","recall","curve","Parameters","--","--","--","--","--","kind",":","{","'roc","'",",","'precision_recall_curve","'","}","Returns","--","--","--","-","float",":","AUC"]
code: def auc(self, kind="roc", reorder=False, **kwargs):
      """
      Calcurate AUC of ROC curve or precision recall curve
  
      Parameters
      ----------
      kind : {'roc', 'precision_recall_curve'}
  
      Returns
      -------
      float : AUC
      """
      if kind == "roc":
          return self.roc_auc_score(**kwargs)
      elif kind == "precision_recall_curve":
          return self.average_precision_score(**kwargs)
      else:
          msg = "Invalid kind: {0}, kind must be either 'roc' or 'precision_recall_curve'"
          raise ValueError(msg.format(kind))
  
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 1 for calling the MetricsMethods obj's underlying member method code with example usage: obj.auc(kind, reorder) and returns: self, self