The method's performance on MNIST is relatively mediocre. You might think 98.96% is amazing, but it's about relative performance. It is a relatively easy exerci

The method's performance on MNIST is relatively mediocre. You might think 98.96% is amazing, but it's about relative performance. It is a relatively easy exercise nowadays to get above 99% with neural nets. Even I can get that kind of performance with hand-written Python neural nets, on the CPU, with no convolutions. For the rest of the (non-image) datasets, it's already common knowledge that boosting methods are competitive with neural nets.