What Data Can’t Do

Re:What Data Can’t Do by currymj on Wednesday March 31, 2021 @03:21PM (#26651801)

I don't disagree with any of that, but I still think a responsible, clear-thinking ML practitioner can avoid having to assume the form of the data-generating process, depending on their application.

In some cases if you care about PAC generalization bounds, it's even the case that the bounds do actually hold for all possible distributions.

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Re:What Data Can’t Do by dumb1224 on Wednesday March 31, 2021 @04:52PM (#26653032)

I think it's more meaningful to have the discussion in a specific problem domain since statistical inference or ML are just tools to better model a problem / phenomenon. The domain (prior) knowledge -- everything else that's not stats / ML, are the keys to build a more robust model. Leave the problem domain out we are left just with pure mathematical theories and the points can only be proved by simulated data.

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