Two ways to train a set of class-specific generative models
				• Discriminative approach Train all of the parameters of both models to maximize the probability of getting the labels right.
	• Generative approach Train each model separately to fit the input vectors of that class. – Different models can be trained on different cores. – It is easy to add a new class without retraining all the other classes • These are significant advantages when the models are harder to train than the simple linear models considered here.