EvaluationMeasures.FOR

Description

FOR of prediction

Usage

1
2
EvaluationMeasures.FOR(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 Ommision Rate is What fraction of negative predicted are real positive.

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

Value

FOR

Author(s)

Babak Khorsand

Examples

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