EvaluationMeasures.PLR: EvaluationMeasures.PLR In EvaluationMeasures: Collection of Model Evaluation Measure Functions

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

PLR

Babak Khorsand

Examples

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

EvaluationMeasures documentation built on May 30, 2017, 5:22 a.m.