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Worth-Advance-1232 OP t1_j47drjb wrote

Reply to comment by ndemir in Why is Super Learning / Stacking used rather rarely in practice? [D] by Worth-Advance-1232

For me this doesn’t really make all that much sense. Stacking is not a tool in itself, it’s rather a modelling approach. Also from what I can tell in the h2o docs it seems that their Stacked Ensemble has only one level to it and no meta-model. Thus rather than using e. g. the outputs (or probability distribution) of each model to train a new model, it will only use the output for any given input directly to return its final prediction, doesn’t it?

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ndemir t1_j4820tc wrote

You can define meta learner:
https://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/stacked-ensembles.html

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Worth-Advance-1232 OP t1_j48mdcw wrote

I’ll look into it, thanks a lot! The main topic/question is still open for me tho.

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ndemir t1_j48mkuy wrote

In real world; stacking is used. It's usually behind the scenes -- as you have seen in this AutoML application.

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Worth-Advance-1232 OP t1_j48mrfn wrote

I‘ve used it in production as well, but thought that there is quite few research published about it lately. So I kind of assumed it’s similar in practice.

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