Consider i have a classifier like A
and the result of its classification gives me the following table:
TP TN FP FN
A 225 100 175 100
This is impossible, because you only have a confusion matrix for a certain (unknown) threshold of your classifier. A ROC-Curve contains information about all possible thresholds.
The Confusion matrix corresponds to a single point on your ROC Curve:
Sensitivity = TP / (TP + FN)
1 - Specificy = TN / (TN + FP) .