class_docstr: Binary confusion matrix class
docstr: Returns an ordered dictionary of statistics
docstr_tok: ["Returns","an","ordered","dictionary","of","statistics"]
code: def stats(self, lst_stats=None):
      """
      Returns an ordered dictionary of statistics
      """
      if lst_stats is None:
          lst_stats = [
              "population",
              "P",
              "N",
              "PositiveTest",
              "NegativeTest",
              "TP",
              "TN",
              "FP",
              "FN",
              "TPR",
              "TNR",
              "PPV",
              "NPV",
              "FPR",
              "FDR",
              "FNR",
              "ACC",
              "F1_score",
              "MCC",
              "informedness",
              "markedness",
              "prevalence",
              "LRP",
              "LRN",
              "DOR",
              "FOR",
          ]
      d = map(lambda stat: (stat, getattr(self, stat)), lst_stats)
      return collections.OrderedDict(d)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import math
  import numpy
  import pandas
  import collections
  from pandas_ml.confusion_matrix.abstract import ConfusionMatrixAbstract
label_desc: Use image node_id 42 for calling the BinaryConfusionMatrix obj's underlying member method code with example usage: obj.stats(lst_stats) and returns: collections