1.25 (
) www Consider the generalization of the squared loss function (1.87) for a single target variable t to the case of multiple target variables described by the vector t given by E[L(t, y(x))] =



y(x) − t2p(x, t) dx dt. (1.151)

Using the calculus of variations, show that the function y(x) for which this expected loss is minimized is given by y(x) = Et[t|x]. Show that this result reduces to (1.89)

for the case of a single target variable t.