EvaluationMeasures.FNR {EvaluationMeasures}

EvaluationMeasures.FNR

Description

FNR of prediction

Usage

EvaluationMeasures.FNR(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

False Negative Rate is Proportional of positives that predict as negative .

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

Value

FNR

Author(s)

Babak Khorsand

Examples

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