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Science works because it posits models first, and then data is sought to confirm or disconfirm it. The benefit of having a model first is that it is much more likely to be general (and hence reproducible).

ML does completely opposite. Data first, and then the model is discovered using data. It's pretty easy to see why it would lead to non-reproducible models.




From this perspective, where is the line between ML and automated p-hacking?




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