Machine learning does just fine with input. Supervised learning is very effective, but only if the dataset is very “complete” and the labeling has sufficient spacial accuracy in comparison to the detection features. The problem is that humans aren’t particularly good at either of those given the sub-second on/off signature detection windows that Sense uses. But smartplugs are pretty effective at both.
But as you suggest @andrewchong, perhaps a placebo train mode might make some people happier. Personally, I’m still betting on Sense’s approach.
ps: Both Neurio and Smappee have a train mode, but from everything I have heard from users, the train mode is worse than useless.