EvaluationMeasures (version 1.1.0)

EvaluationMeasures.TNR: EvaluationMeasures.TNR

Description

TNR of prediction

Usage

EvaluationMeasures.TNR(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.

Value

TNR

Details

True Negative Rate is Proportional of negatives that are correctly identified

By getting the predicted and real values or number of TP,TN,FP,FN return the Specificity or True Negative Rate of model

Examples

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