Suppose you are building a logistic regression model to determine whether a person has diabetes or not.

Following are the values of predicted probabilities of 10 patients.

Patient Probability(Diabetes)
A 0.82
B 0.37
C 0.04
D 0.41
E 0.55
F 0.62
G 0.20
H 0.91
I 0.74
J 0.33

Assuming you arbitrarily chose a cut-off of 0.4, wherein if the probability is greater than 0.4, you'd conclude that the patient has diabetes and if it is less than or equal to 0.4, you'd conclude that the patient doesn't have diabetes, how many of these patients would be classified as diabetic based on the table above?

The cut-off is given to be 0.4. Hence, for a patient to be classified as diabetic, Probability(Diabetes) needs to be greater than 0.4. As you can see in the table above, there are 6 patients who have Probability(Diabetes) > 0.4. These are:

A: 0.82, D: 0.41, E: 0.55, F: 0.62, H: 0.91, I: 0.74