[chestervonwinch]

The traditional way (that I'm aware of) of defining the false positive rate is derived from the conditional probability of a positive prediction given that the true underlying state is negative:

    False Pos. Rate = P(predict + | state -)
                    = P(predict + and state -) / P(state -)
                    = P(predict + and state -) / (P(predict + and state-) + P(predict - and state -))
                    ~ #FP/samplesize / (#FP/samplesize + #TN/samplesize)
                    = #FP / (#FP + #TN)

The latter quantity is usually given as the definition of false positive rate. Roughly speaking, it's the ratio of how often you predict positive when the state is negative versus how often the state is negative.