EvaluationMeasures.Sensitivity {EvaluationMeasures} R Documentation

## EvaluationMeasures.Sensitivity

### Description

Sensitivity of prediction

### Usage

EvaluationMeasures.Sensitivity(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

Sensitivity is Proportional of positives that are correctly identified

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

Sensitivity

Babak Khorsand

### Examples

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


[Package EvaluationMeasures version 1.1.0 Index]