Tutorials

The tutorials section is a comprehensive user guide for all main features within the Hugin GUI. You will learn how to build Hugin Knowledge Bases using Bayesian networks and influence diagrams. Furthermore, you will learn how to use the major features.

Building Bayesian Networks

This tutorial shows how to implement a small Bayesian network in the Hugin GUI.

Building Influence Diagrams

This tutorial shows how to implement a small influence diagram in the Hugin GUI. It helps plantation owner Apple Jack decide whether or not to give his apple tree, which is losing its leaves, some treatment.

Using the Learning Facilities

Currently, the Hugin GUI supports two kinds of parameter learning: adaptation and EM. Parameter learning is the task of filling in the conditional probability tables after the structure of the knowledge base have been built.

Building Object Oriented Bayesian Networks

This tutorial shows how to implement a small object-oriented Bayesian network in the Hugin GUI.

Using the Table Generator

This tutorial shows how the table generator functionality can be used to simplify how tables are specified for discrete chance nodes.

Using the Case Generator

This tutorial shows how to generate a database of cases from an existing knowledge base.