class_docstr: Binary confusion matrix class
docstr: true positive rate (TPR)
  eqv. with hit rate, recall, sensitivity
  TPR = TP / P = TP / (TP+FN)
docstr_tok: ["true","positive","rate","(","TPR",")","eqv",".","with","hit","rate",",","recall",",","sensitivity","TPR","=","TP","\/","P","=","TP","\/","(","TP+FN",")"]
code: def TPR(self):
      """
      true positive rate (TPR)
      eqv. with hit rate, recall, sensitivity
      TPR = TP / P = TP / (TP+FN)
      """
      # return(np.float64(self.TP) / (self.TP + self.FN))
      return np.float64(self.TP) / self.P
  
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 21 for calling the BinaryConfusionMatrix obj's underlying member method code with example usage: obj.TPR() and returns: unknown