Show that the regression function also has the following pointwise optimality property:
E |m(X) − Y | 2 |X = x = min f E |f(X) − Y | 2 |X = x
for µ-almost all x ∈ Rd.
Let (X, Y ) be an Rd×R-valued random variable with E|Y | <>∗ : Rd → R which minimizes the L1 risk, i.e., which satisfies
E{|f ∗(X) − Y |} = min f:Rd→R E{|f(X) − Y |}.
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