Open huangynn opened 6 years ago
I guess that the for loop right here allows for applying a parallel for. We only need to keep track somehow of which features are already taken by the process in previous trees. This can be done with a global lookup table.
Is there any plan to add this feature?
I couldn't parallelize the tree loop, but I was able to parallelize the inner variable loop using parallelfor. On the unit tests, it results in ~2x speedup for regression - maybe I'll try to clean things up and create a PR.
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Random forest training use single thread, which is not time efficient. Is there anyway to parallel training random forest.