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: Return a string representation of a dictionary
docstr_tok: ["Return","a","string","representation","of","a","dictionary"]
code: def _str_dict(
      self,
      d,
      line_feed_key_val="\n",
      line_feed_stats="\n\n",
      d_name=None,
  ):
      """
      Return a string representation of a dictionary
      """
      s = ""
      for i, (key, val) in enumerate(d.items()):
          name = self._name_from_dict(key, d_name)
          if i != 0:
              s = s + line_feed_stats
          s = s + "%s:%s%s" % (name, line_feed_key_val, val)
      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 25 for calling the ConfusionMatrixAbstract obj's underlying member method code with example usage: obj._str_dict(d, line_feed_key_val, line_feed_stats, d_name) and returns: s