Two follow-ups, both about the generator rather than the data itself:
-
Is there a description anywhere of how the simulator decides which
transactions are fraudulent? The README doesn't cover it and I
couldn't find it in the ICASSP paper.
-
Related: online transactions ("ONLINE" merchant city) are 40x more
likely to be fraud in 2015-16, but 5x LESS likely in 2018-19. That
reversal is large enough that a model trained on the earlier period
learns an inverted rule. Did the generation logic change between
those periods?
Two follow-ups, both about the generator rather than the data itself:
Is there a description anywhere of how the simulator decides which
transactions are fraudulent? The README doesn't cover it and I
couldn't find it in the ICASSP paper.
Related: online transactions ("ONLINE" merchant city) are 40x more
likely to be fraud in 2015-16, but 5x LESS likely in 2018-19. That
reversal is large enough that a model trained on the earlier period
learns an inverted rule. Did the generation logic change between
those periods?