How Neural Network Predicts?
Links in the network represent axons of biological counterparts. As each axon of neurons reacts differently, each link is assigned with a different weight. Weights of links are the essence of neural networks. With weights, networks make prediction as follows. First, known values of input fields are presented to the nodes of input layer. Then, values are propagated towards the nodes of the output layer. In this process, values are multiplied with weights, summed and, then, applied to a non-linear function. Note that this is exactly how neurons combine input signals. Weights are designed in such a way that for given input patterns, values of the output layer reflect the values of actual outcome.
