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The presumption of ML is that compressions of X are representations of Y. This is just false. The compression of X, ie., f, isnt a representation of Y. Its an
by mjburgess 5y ago
The presumption of ML is that compressions of X are representations of Y. This is just false.
The compression of X, ie., f, isnt a representation of Y. Its an estimator of the value of Y within some domain of X,Y.
For it to be f to be a representation of Y, it needs to be able to stand-in for Y (at least). And compressions of X cannot. They lack, eg., the right counterfactual behaviour.
ie., A representation of a cat enables computing things about a cat in imaginative scenarios, eg., in a video game simulation. Compressions of pixels of cats do not.
- rualca 5y ago> The presumption of ML is that compressions of X are representations of Y. This is just false. The whole point of modeling is that without a doubt compressions of X are indeed representations of Y, because the whole reason X was picked was that it is clearly represents Y with an acceptable degree of accuracy for the use in mind. If a proposed model fails to reproduce and predict a model with acceptable accuracy, it's scrapped in favour of those that can. Why are we discussing this? I frankly do not understand why we are wasting time explaining the very basics of what a model is and why they are created and how they are used. This is not up for discussion. Just ask yourself why people, specially in engineering and physics, bother with models.