Let's consider the most common method that's used to train a feedforward neural network: the error backpropagation method. It is related to supervised methods. Therefore, it requires target values in the training examples.
The idea of the algorithm is based on the use of the output error of a neural network. At each iteration of the algorithm, there are two network passes – forward and backward. On a forward pass, an input vector is propagated from the network inputs to its outputs and forms a specific output vector corresponding to the current (actual) state of the weights. Then, the neural network error is calculated. On the backward pass, this error propagates from the network output to its ...
