class_docstr: Abstract class for confusion matrix
  
  You shouldn't instantiate this class.
  You might instantiate ConfusionMatrix or BinaryConfusionMatrix classes
class_docstr_tok: ["Abstract","class","for","confusion","matrix","You","should","n't","instantiate","this","class",".","You","might","instantiate","ConfusionMatrix","or","BinaryConfusionMatrix","classes"]
docstr: Returns a string representation of statistics
docstr_tok: ["Returns","a","string","representation","of","statistics"]
code: def _str_stats(self, lst_stats=None):
      """
      Returns a string representation of statistics
      """
      d_stats_name = {
          "cm": "Confusion Matrix",
          "overall": "Overall Statistics",
          "class": "Class Statistics",
      }
  
      stats = self.stats(lst_stats)
  
      d_stats_str = collections.OrderedDict(
          [
              ("cm", str(stats["cm"])),
              (
                  "overall",
                  self._str_dict(
                      stats["overall"],
                      line_feed_key_val=" ",
                      line_feed_stats="\n",
                  ),
              ),
              ("class", str(stats["class"])),
          ]
      )
  
      s = self._str_dict(
          d_stats_str,
          line_feed_key_val="\n\n",
          line_feed_stats="\n\n\n",
          d_name=d_stats_name,
      )
      return s
  
imports: import numpy
  import pandas
  import collections
  import pandas_ml
  from pandas_ml.confusion_matrix.stats import binom_interval, class_agreement, prop_test
label_desc: Use image node_id 26 for calling the ConfusionMatrixAbstract obj's underlying member method code with example usage: obj._str_stats(lst_stats) and returns: s