EvaluationMeasures.MCC {EvaluationMeasures} | R Documentation |
MCC of prediction
EvaluationMeasures.MCC(Real = NULL, Predicted = NULL, Positive = 1,
TP = NULL, TN = NULL, FP = NULL, FN = NULL)
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. |
Matthews Correlation Coefficient is correlation coefficient between real and predicted.
Positive One means perfect prediction,Zero means random prediction, Negative one means total disagreement.
By getting the predicted and real values or number of TP,TN,FP,FN return the Matthews Correlation Coefficient of model
MCC
Babak Khorsand
EvaluationMeasures.MCC(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))