2 Each feature F i de-fines an associated random boolean variable where (X=x) takes the value 1 if X = x and 0 otherwise.
our classifier estimates a feature weight α i for each feature F i , that is used to define the prediction variable Z: The prediction made by the classifier is sign(Z) = Z/|Z|, i.e., −1 or +1 depending on the sign of Z.