Number of Input Nodes and Its States

In this lesson, we cover the concept of input nodes. They represent the variables that serve as the starting points of the BN, which are often the observable variables in a dataset. The number of input nodes determines the initial complexity of the network. The input nodes, also known as root nodes or parentless nodes, are the nodes that have no incoming edges or connections from other nodes in the network. These nodes are typically used to model the initial or prior probabilities of certain events or variables.

Several networks for one problem

Let's say we want to model the different causes of lung cancer. Given different causes, and different possible ways of measuring these causes. For example, we can see whether a person is a smoker or not, but also we can add information on the frequency of smoking.

In the images below there are four different configurations to model this problem using a BN. Each one has a different number of input nodes and states of these nodes.