class_docstr: Binary confusion matrix class
docstr: false omission rate (FOR)
  FOR = FN / NegativeTest
docstr_tok: ["false","omission","rate","(","FOR",")","FOR","=","FN","\/","NegativeTest"]
code: def FOR(self):
      """
      false omission rate (FOR)
      FOR = FN / NegativeTest
      """
      return np.float64(self.FN) / self.NegativeTest
  
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 29 for calling the BinaryConfusionMatrix obj's underlying member method code with example usage: obj.FOR() and returns: unknown