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There exist plenty of error measurements, however you should take care on their combinations. Typically you don't tell the true negative rate since it is implicitely covered in the other measurements, i.e.: precision & recall would be totally fine, as well as true positive & false positives would be. In some research areas sensitivity & specifity are more common than the other two. Furthermore you can a) plot your results in ROC-curves, b) give the area under the curve (AUC), and c) give the F1-measure (combination of precision & recall).
