Machine Learning for Data Mining

Why are weights important?

Weights are important for several reasons. First because all neurons in one layer are connected to every neuron in the next layer, this means that the layers are connected. It also means that a neural network model, unlike many other models, doesn't drop any predictors. So for example, you may start off with 20 predictors, and these 20 predictors will be kept. A second reason why weights are important is that they provide information on the impact or importance of each predictor to the prediction. As will be shown later, these weights start off randomly, however through multiple iterations, the weights are modified so as to provide meaningful information.