The key difference is the use of sets of (NXDomain) domains vs single domains. With a few additonal features, the boost in signal is sufficient to allow classification as individual DGAs with essentially no false positives.
OP's machine learning is arguably even more impressive, because it has a decent success rate based entirely on open source data and the domain names themselves, with no other corroborating information (like a NXDOMAIN response).
(I've worked with both Antonakakis and Yadav, and implemented the production version of Damballa's AGD classifier as per Antonakakis).
# I'm SURE there's a better way to store all the counts but not sure...
I'm seeing the progress with which this comment came to life.