The above type of learning, in which a network is trained by providing examples alongside the correct answer, is called supervised learning (a human has supervised the learning process by providing the network with the correct answers). Many supervised learning methods are more complex than this, but the principle is the same: the correct answers are provided, and networks are tweaked using backpropagation to update weights until the categorization of input patterns is sufficiently accurate. This design has proven to work so generally that it is now applied to image recognition, natural
...more
