A simple neural network is composed of three layers, the Input layer, Hidden layer, and Output layer as shown in the following diagram:
A layer is a conceptual collection of nodes (also called units), which simulate neurons in a biological brain. The input layer represents the input features x and each node is a predictive feature x. The output layer represents the target variable(s). In binary classification, the output layer contains only one node, whose value is the probability of the positive class. In multiclass classification, the output layer consists of n nodes where n is the number of possible classes ...
