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Computers and Technology, 30.10.2019 04:31 s77969

Suppose we obtain n labeled samples {(xi , yi)} n i=1 from our underlying distribution d. suppose we break this into ntrain and ntest samples for our training and test set. recall our definition of the true least squares error (f) = e(x, y)∼d[(f(x) − y) 2 ] (the subscript (x, y) ∼ d makes clear that our input-output pairs are sampled according to d). our training and test losses are defined as: btrain(f) = 1 ntrain x (x, y)∈training set (f(x) − y) 2 btest(f) = 1 ntest x (x, y)∈test set (f(x) − y)

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Suppose we obtain n labeled samples {(xi , yi)} n i=1 from our underlying distribution d. suppose we...
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