We have a set Eachx is an N -dimensional attribute vector, and y ∈ {1, ..., K} are classes.
a classifier, H, maps an attribute vector,x, to a class, y. H is parameterized by a K-by-N matrix of weights, W: whereW r is the rth row of W. the predicted label is the index of the row of W that has the highest inner-product with the attributes,x.