Description Usage Arguments Details Value Author(s) Examples
Sensitivity of prediction
1 2 |
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. |
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
1 | EvaluationMeasures.Sensitivity(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))
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