class_docstr: Binary confusion matrix class
docstr: false positive rate (FPR)
  eqv. with fall-out
  FPR = FP / N = FP / (FP + TN)
docstr_tok: ["false","positive","rate","(","FPR",")","eqv",".","with","fall-out","FPR","=","FP","\/","N","=","FP","\/","(","FP","+","TN",")"]
code: def FPR(self):
      """
      false positive rate (FPR)
      eqv. with fall-out
      FPR = FP / N = FP / (FP + TN)
      """
      # return(np.float64(self.FP)/(self.FP + self.TN))
      return np.float64(self.FP) / self.N
  
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 20 for calling the BinaryConfusionMatrix obj's underlying member method code with example usage: obj.FPR() and returns: unknown