Recently, I built a classification model based on the imbalanced data set(positive sample is minority and negative sample is majority), and the model gave the following result for the test set:
True Positives = 0
True Negatives = 139
False Positives = 0
False Negatives = 10.
My question is: for the result, can Matthews correlation coefficient (MCC ) and F-measure be used for estimating the classifier?
Since the denominators for MCC and F-measure are zero, it seems meaningless. If so, MCC and F-measure is not always works for estimating the classifier, and sensitivity and specificity as well as g-mean should be better. Is that right?
Any help is appreciated.