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#1
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Hi everyone,
As I understood, noisy target is when we observe that for a same value of x we get different values of y. Then, we model this function as a distribution P(y|x) (instead of a deterministic one) But later on in the book, Yaser says: "This view suggests that a deterministic target function can be considered a special case of a noisy target, just with zero noise. Indeed, we can formally express any function f as a distribution P(y|x) by choosing P(y|x) to be zero for all y except y = f(x)". My question is: How we can consider a value of y is equal to f(x), since the function f is a distribution. Suppose we have two different values of y for the same input x, what of these two y's is different to f(x)? |
#2
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![]() Quote:
The case you mention, where there are two possible ![]() ![]()
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#3
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It is clear now. Thanks a lot!
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chapter 1, noisy target |
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