EvaluationMeasures.TPR {EvaluationMeasures} | R Documentation |
TPR of prediction
EvaluationMeasures.TPR(Real = NULL, Predicted = NULL, Positive = 1,
TP = NULL, TN = NULL, FP = NULL, FN = NULL)
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. |
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
TPR
Babak Khorsand
EvaluationMeasures.TPR(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))