In this setting, the number of parameters K is equal to |Y | 2 ×|X| train , where |•| denotes the cardinal and |X| train refers to the number of configurations of x t observed during training.
even in moderate size applications, the number of parameters can be very large, mostly due to the introduction of sequential dependencies in the model.