Description Usage Arguments Details Value Author(s) Examples
NLR of prediction
1 2 |
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. |
Negative Likelihood Ratio is (1-Sensitivity) / Specificity = PR(T-|D+)/PR(T-|D-)
By getting the predicted and real values or number of TP,TN,FP,FN return the Negative Likelihood Ratio of model
NLR
Babak Khorsand
1 | EvaluationMeasures.NLR(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))
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