EvaluationMeasures.PLR {EvaluationMeasures} | R Documentation |
PLR of prediction
EvaluationMeasures.PLR(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. |
Positive Likelihood Ratio is Sensitivity / (1-Specificity) = PR(T+|D+)/PR(T+|D-)
By getting the predicted and real values or number of TP,TN,FP,FN return the Positive Likelihood Ratio of model
PLR
Babak Khorsand
EvaluationMeasures.PLR(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))