EvaluationMeasures.FNR {EvaluationMeasures} | R Documentation |
FNR of prediction
EvaluationMeasures.FNR(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. |
False Negative Rate is Proportional of positives that predict as negative .
By getting the predicted and real values or number of TP,TN,FP,FN return the Miss Rate or False Negative Rate of model
FNR
Babak Khorsand
EvaluationMeasures.FNR(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))