EvaluationMeasures.PLR

Description

PLR of prediction

Usage

1
2
EvaluationMeasures.PLR(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

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

Value

PLR

Author(s)

Babak Khorsand

Examples

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