To obtain p(y | x) above, we need to marginalize over a nuisance variable, the derivation of y.
the MAP decision rule becomes where is typically derived from a loglinear model as follows, where γ is a scaling factor to adjust the sharpness of the distribution, the score s(x, y, d) is a learned linear combination of features of the triple (x, y, d), and Z(x) is a normalization constant.