ratively slow
???
It's sort of slower to train if you're training serial, but
if you paralyze it, it's often faster to train since it has
a much smaller model size. So the trees are usually not as
deep and you don't need as many because you're doing much
more focused learning where you try to correct the mistakes
of the other models. So usually it’s very fast to predict
because prediction can happen in parallel over all the
trees, while learning cannot happen in parallel over all the
trees necessarily. Us