EvaluationMeasures.TPR

Description

TPR of prediction

Usage

1
2
EvaluationMeasures.TPR(Real = NULL, Predicted = NULL, Positive = 1,
  TP = NULL, TN = NULL, FP = NULL, FN = NULL)

Arguments

Real

Real binary values of the class

Predicted

Predicted binary values of the class

Positive

Consider 1 label as Positive Class unless changing this parameter to 0

TP

Number of True Positives. Number of 1 in real which is 1 in predicted.

TN

Number of True Negatives. Number of 0 in real which is 0 in predicted.

FP

Number of False Positives. Number of 0 in real which is 1 in predicted.

FN

Number of False Negatives. Number of 1 in real which is 0 in predicted.

Details

True Positive Rate is Proportional of positives that are correctly identified

By getting the predicted and real values or number of TP,TN,FP,FN return the True Positive Rate or Sensitivity or Recall of model

Value

TPR

Author(s)

Babak Khorsand

Examples

1
EvaluationMeasures.TPR(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))