weka - False Acceptance Rate and False Rejection Rate calculation using a n*n confusion matrix -

far , frr used express results of biometric devices. below confusion matrix produced biometric data produced in weka. couldn't find resources explaining procedure calculate far , frr using n*n confusion matrix. explaining procedure of great help. in advance!

weka gives these values, tp rate, fp rate, precision, recall, f-measure , roc area. please suggest if required values can calculated using these.

=== confusion matrix ===

a b c d e f g h j k l m n o   <-- classified  1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 | = user1  0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 | b = user2  0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 | c = user3  0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 | d = user4  0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 | e = user5  0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 | f = user6  0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 | g = user7  0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 | h = user9  1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 | = user10  0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 | j = user11  0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 | k = user14  0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 | l = user15  0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 | m = user16  0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 | n = user17  0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 | o = user19 

the accepted answer here user "chl" has reference biometrics literature: https://stats.stackexchange.com/questions/3489/calculating-false-acceptance-rate-for-a-gaussian-distribution-of-scores .

he says,

[the roc curve] plot of (tar=1-frr, false rejection rate) against false acceptance rate (far).

however, commonly roc curve happens plot of tp rate function of false positive rate (fp rate).
seems can use tp rate , fp rate.