6.2 What Is a Neural Network?

Neural network softwares are programs designed to do what human brains have evolved to perform: learn from examples and recognize patterns. As a neural network is trained, it can gradually learn, for example, the patterns of behavior and the attributes of criminals; this is actually done through an adjustment of mathematical formulas that are continuously changing, eventually converging into a model.

This model, in most instances, is the end product of neural networks and is usually in the form of a formula or a series of equations, representing a set of input values and a predictive output. For example, Table 6.1 shows a model designed to predict fraud at an e-commerce Web site. When given the number of visits a person makes to a site (input 1), coupled with a dollar range (input 2) and a particular type of product bought (input 3), a network would then create a formula to compute a probability score (output) for classifying that transaction as being either legal or fraudulent.

Table 6.1: Model with Three Inputs, a Set of Formula Weights, and One Output
Input Types	Values	Network (Weights) Formula
Number of visits	2	Input => *.08766 x
Dollar range	(567–879)	Input => *.00934 x
Product category	4	Input => *.4956 x
		Output = 68% fraud probability score

Neural networks are software systems designed to do what a human brain does, which is to figure out how to find patterns in the environment in order to survive. Neural networks deal with the basic problems that our ancestors had in hunting, finding paths, knowing the seasons, recognizing prey and predators, and identifying threats to the tribe and village: pattern recognition.