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EvaluationMeasures (version 1.1.0)

EvaluationMeasures.TPR: EvaluationMeasures.TPR

Description

TPR of prediction

Usage

EvaluationMeasures.TPR(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

TPR

Details

True Positive Rate is Proportional of positives that are correctly identified

By getting the predicted and real values or number of TP,TN,FP,FN return the True Positive Rate or Sensitivity or Recall of model

Examples

Run this code
EvaluationMeasures.TPR(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))

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