Their dimensionality depends on the dimensionality of the last hidden layer (called O −1 ) and the number |Y | of different classes, i.e., H O ∈ R h O −1 ×|Y | and b O ∈ R 1×|Y | , respectively.
this layer computes a linear classification function with a softmax operator so thatŷ = sof tmax( In order to avoid over-fitting, two different regularization schemes are applied.