Learning Probabilistic Graphical Models in R

Probabilistic graphical models

In the last section of this chapter, we introduce probabilistic graphical models as a generic framework to build and use complex probabilistic models from simple building blocks. Such complex models are often necessary to represent the complexity of the task to solve. Complex doesn't mean complicated and often the simple things are the best and most efficient. Complex means that, in order to represent and solve tasks where we have a lot of inputs, components, or data, we need a model that is not completely trivial but reaches the necessary degree of complexity.

Such complex problems can be decomposed into simpler problems that will interact with each other. Ultimately, the most simple building block will be one variable. ...